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data-has-card-for-ri="10463" href="https://www.academia.edu/Documents/in/Model_Predictive_Control_MPC_">Model Predictive Control (MPC)</a>, <script data-card-contents-for-ri="10463" type="text/json">{"id":10463,"name":"Model Predictive Control (MPC)","url":"https://www.academia.edu/Documents/in/Model_Predictive_Control_MPC_?f_ri=22247","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="22247" href="https://www.academia.edu/Documents/in/Traffic_control">Traffic control</a>, <script data-card-contents-for-ri="22247" type="text/json">{"id":22247,"name":"Traffic control","url":"https://www.academia.edu/Documents/in/Traffic_control?f_ri=22247","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="116723" href="https://www.academia.edu/Documents/in/Accounting_and_Auditing">Accounting and Auditing</a>, <script data-card-contents-for-ri="116723" type="text/json">{"id":116723,"name":"Accounting and 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(MPC)","url":"https://www.academia.edu/Documents/in/Model_Predictive_Control_MPC_?f_ri=22247","nofollow":false},{"id":22247,"name":"Traffic control","url":"https://www.academia.edu/Documents/in/Traffic_control?f_ri=22247","nofollow":false},{"id":116723,"name":"Accounting and Auditing","url":"https://www.academia.edu/Documents/in/Accounting_and_Auditing?f_ri=22247","nofollow":false},{"id":220371,"name":"Traffic Flow","url":"https://www.academia.edu/Documents/in/Traffic_Flow?f_ri=22247","nofollow":false},{"id":224767,"name":"Prediction Model","url":"https://www.academia.edu/Documents/in/Prediction_Model?f_ri=22247"},{"id":1036170,"name":"Hybrid Control","url":"https://www.academia.edu/Documents/in/Hybrid_Control?f_ri=22247"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_19033026 coauthored" data-work_id="19033026" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/19033026/DRACULA_a_microscopic_day_to_day_dynamic_framework_for_modelling_traffic_networks">DRACULA: a microscopic, day-to-day dynamic framework for modelling traffic networks</a></div></div><div class="u-pb4x u-mt3x"></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/19033026" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="7933f3339c3af9a15332c7515ede3249" rel="nofollow" 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InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="19033026"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 19033026, container: ".js-paper-rank-work_19033026", }); });</script></li><li class="js-percentile-work_19033026 InlineList-item InlineList-item--bordered hidden u-tcGrayDark"><span class="percentile-widget hidden"><span class="u-mr2x percentile-widget" style="display: none">•</span><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 19033026; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-percentile-work_19033026"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); 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u-positionRelative">10</a>  </div><span class="InlineList-item-text u-textTruncate u-pl10x"><a class="InlineList-item-text" data-has-card-for-ri="3252" href="https://www.academia.edu/Documents/in/Traffic_Simulation">Traffic Simulation</a>, <script data-card-contents-for-ri="3252" type="text/json">{"id":3252,"name":"Traffic Simulation","url":"https://www.academia.edu/Documents/in/Traffic_Simulation?f_ri=22247","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="22247" href="https://www.academia.edu/Documents/in/Traffic_control">Traffic control</a>, <script data-card-contents-for-ri="22247" type="text/json">{"id":22247,"name":"Traffic control","url":"https://www.academia.edu/Documents/in/Traffic_control?f_ri=22247","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="35036" href="https://www.academia.edu/Documents/in/Real-Time_Strategy_RTS_games">Real-Time Strategy (RTS) games</a>, <script data-card-contents-for-ri="35036" type="text/json">{"id":35036,"name":"Real-Time Strategy (RTS) games","url":"https://www.academia.edu/Documents/in/Real-Time_Strategy_RTS_games?f_ri=22247","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="154543" href="https://www.academia.edu/Documents/in/Space_Time">Space Time</a><script data-card-contents-for-ri="154543" type="text/json">{"id":154543,"name":"Space Time","url":"https://www.academia.edu/Documents/in/Space_Time?f_ri=22247","nofollow":false}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=19033026]'), work: {"id":19033026,"title":"DRACULA: a microscopic, day-to-day dynamic framework for modelling traffic networks","created_at":"2015-11-26T02:24:10.191-08:00","url":"https://www.academia.edu/19033026/DRACULA_a_microscopic_day_to_day_dynamic_framework_for_modelling_traffic_networks?f_ri=22247","dom_id":"work_19033026","summary":null,"downloadable_attachments":[{"id":42113257,"asset_id":19033026,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":39196691,"first_name":"David","last_name":"Watling","domain_name":"leeds","page_name":"DavidWatling","display_name":"David Watling","profile_url":"https://leeds.academia.edu/DavidWatling?f_ri=22247","photo":"/images/s65_no_pic.png"},{"id":39299405,"first_name":"Dirck Van","last_name":"Vliet","domain_name":"independent","page_name":"DirckVanVliet","display_name":"Dirck Van Vliet","profile_url":"https://independent.academia.edu/DirckVanVliet?f_ri=22247","photo":"/images/s65_no_pic.png"}],"research_interests":[{"id":3252,"name":"Traffic Simulation","url":"https://www.academia.edu/Documents/in/Traffic_Simulation?f_ri=22247","nofollow":false},{"id":22247,"name":"Traffic control","url":"https://www.academia.edu/Documents/in/Traffic_control?f_ri=22247","nofollow":false},{"id":35036,"name":"Real-Time Strategy (RTS) games","url":"https://www.academia.edu/Documents/in/Real-Time_Strategy_RTS_games?f_ri=22247","nofollow":false},{"id":154543,"name":"Space Time","url":"https://www.academia.edu/Documents/in/Space_Time?f_ri=22247","nofollow":false},{"id":229390,"name":"Real Time","url":"https://www.academia.edu/Documents/in/Real_Time?f_ri=22247"},{"id":329733,"name":"Demand and Supply","url":"https://www.academia.edu/Documents/in/Demand_and_Supply?f_ri=22247"},{"id":841223,"name":"Road Traffic","url":"https://www.academia.edu/Documents/in/Road_Traffic?f_ri=22247"},{"id":871148,"name":"Network Model","url":"https://www.academia.edu/Documents/in/Network_Model?f_ri=22247"},{"id":874370,"name":"STATIC \u0026 DYNAMIC ROUTING","url":"https://www.academia.edu/Documents/in/STATIC_and_DYNAMIC_ROUTING?f_ri=22247"},{"id":1240818,"name":"Congestion Management","url":"https://www.academia.edu/Documents/in/Congestion_Management?f_ri=22247"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_71698692" data-work_id="71698692" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/71698692/Design_and_Development_of_an_Image_Processing_Based_Adaptive_Traffic_Control_System_with_GSM_Interface">Design and Development of an Image Processing Based Adaptive Traffic Control System with GSM Interface</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">With the increasing number of vehicles on the road, it has become difficult to properly control the flow of traffic especially in large cities like Lahore. The proposed system uses a digital camera mounted on a stepper motor to sense the... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_71698692" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">With the increasing number of vehicles on the road, it has become difficult to properly control the flow of traffic especially in large cities like Lahore. The proposed system uses a digital camera mounted on a stepper motor to sense the traffic on the road. The decision to open the lane is done after monitoring the traffic load. The heavily loaded side is turned on for a longer time. Thus the system is intelligent because it is not using the fixed time frame. The system is also integrated with GSM, thus the signals can also be ...</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/71698692" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="195765740" href="https://independent.academia.edu/HammadKhan395">Hammad Khan</a><script data-card-contents-for-user="195765740" type="text/json">{"id":195765740,"first_name":"Hammad","last_name":"Khan","domain_name":"independent","page_name":"HammadKhan395","display_name":"Hammad Khan","profile_url":"https://independent.academia.edu/HammadKhan395?f_ri=22247","photo":"https://0.academia-photos.com/195765740/58106387/46333156/s65_hammad.khan.png"}</script></span></span></li><li class="js-paper-rank-work_71698692 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="71698692"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 71698692, container: ".js-paper-rank-work_71698692", }); });</script></li><li class="js-percentile-work_71698692 InlineList-item InlineList-item--bordered hidden u-tcGrayDark"><span class="percentile-widget hidden"><span class="u-mr2x percentile-widget" style="display: none">•</span><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 71698692; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-percentile-work_71698692"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></li><li class="js-view-count-work_71698692 InlineList-item InlineList-item--bordered hidden"><div><span><span class="js-view-count view-count u-mr2x" data-work-id="71698692"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 71698692; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=71698692]").text(description); $(".js-view-count-work_71698692").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_71698692").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="71698692"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">10</a>  </div><span class="InlineList-item-text u-textTruncate u-pl10x"><a class="InlineList-item-text" data-has-card-for-ri="422" href="https://www.academia.edu/Documents/in/Computer_Science">Computer Science</a>, <script data-card-contents-for-ri="422" type="text/json">{"id":422,"name":"Computer Science","url":"https://www.academia.edu/Documents/in/Computer_Science?f_ri=22247","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="1185" href="https://www.academia.edu/Documents/in/Image_Processing">Image Processing</a>, <script data-card-contents-for-ri="1185" type="text/json">{"id":1185,"name":"Image Processing","url":"https://www.academia.edu/Documents/in/Image_Processing?f_ri=22247","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="2345" href="https://www.academia.edu/Documents/in/Wireless_Communications">Wireless Communications</a>, <script data-card-contents-for-ri="2345" type="text/json">{"id":2345,"name":"Wireless Communications","url":"https://www.academia.edu/Documents/in/Wireless_Communications?f_ri=22247","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="8422" href="https://www.academia.edu/Documents/in/Adaptive_Control">Adaptive Control</a><script data-card-contents-for-ri="8422" type="text/json">{"id":8422,"name":"Adaptive Control","url":"https://www.academia.edu/Documents/in/Adaptive_Control?f_ri=22247","nofollow":false}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=71698692]'), work: {"id":71698692,"title":"Design and Development of an Image Processing Based Adaptive Traffic Control System with GSM Interface","created_at":"2022-02-16T11:12:45.865-08:00","url":"https://www.academia.edu/71698692/Design_and_Development_of_an_Image_Processing_Based_Adaptive_Traffic_Control_System_with_GSM_Interface?f_ri=22247","dom_id":"work_71698692","summary":"With the increasing number of vehicles on the road, it has become difficult to properly control the flow of traffic especially in large cities like Lahore. The proposed system uses a digital camera mounted on a stepper motor to sense the traffic on the road. The decision to open the lane is done after monitoring the traffic load. The heavily loaded side is turned on for a longer time. Thus the system is intelligent because it is not using the fixed time frame. The system is also integrated with GSM, thus the signals can also be ...","downloadable_attachments":[],"ordered_authors":[{"id":195765740,"first_name":"Hammad","last_name":"Khan","domain_name":"independent","page_name":"HammadKhan395","display_name":"Hammad Khan","profile_url":"https://independent.academia.edu/HammadKhan395?f_ri=22247","photo":"https://0.academia-photos.com/195765740/58106387/46333156/s65_hammad.khan.png"}],"research_interests":[{"id":422,"name":"Computer Science","url":"https://www.academia.edu/Documents/in/Computer_Science?f_ri=22247","nofollow":false},{"id":1185,"name":"Image Processing","url":"https://www.academia.edu/Documents/in/Image_Processing?f_ri=22247","nofollow":false},{"id":2345,"name":"Wireless Communications","url":"https://www.academia.edu/Documents/in/Wireless_Communications?f_ri=22247","nofollow":false},{"id":8422,"name":"Adaptive Control","url":"https://www.academia.edu/Documents/in/Adaptive_Control?f_ri=22247","nofollow":false},{"id":22247,"name":"Traffic control","url":"https://www.academia.edu/Documents/in/Traffic_control?f_ri=22247"},{"id":413487,"name":"Design and Development","url":"https://www.academia.edu/Documents/in/Design_and_Development?f_ri=22247"},{"id":443642,"name":"Global System for Mobile Communication (GSM)","url":"https://www.academia.edu/Documents/in/Global_System_for_Mobile_Communication_GSM_?f_ri=22247"},{"id":627176,"name":"Adaptive Traffic Control System","url":"https://www.academia.edu/Documents/in/Adaptive_Traffic_Control_System?f_ri=22247"},{"id":1754849,"name":"Traffic Congestion","url":"https://www.academia.edu/Documents/in/Traffic_Congestion?f_ri=22247"},{"id":3701731,"name":"Digital camera","url":"https://www.academia.edu/Documents/in/Digital_camera?f_ri=22247"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_50024765" data-work_id="50024765" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/50024765/Sense_and_Nonsense_About_Shared_Space_For_an_Objective_View_of_a_Popular_Planning_Concept">Sense and Nonsense About Shared Space - For an Objective View of a Popular Planning Concept</a></div></div><div class="u-pb4x u-mt3x"></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/50024765" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="207f075cad969d64f4f980e37679ea44" rel="nofollow" data-download="{"attachment_id":68163588,"asset_id":50024765,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/68163588/download_file?st=MTczMjQyMjgxOCw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="32825391" href="https://rug.academia.edu/RobMethorst">Rob Methorst</a><script data-card-contents-for-user="32825391" type="text/json">{"id":32825391,"first_name":"Rob","last_name":"Methorst","domain_name":"rug","page_name":"RobMethorst","display_name":"Rob Methorst","profile_url":"https://rug.academia.edu/RobMethorst?f_ri=22247","photo":"/images/s65_no_pic.png"}</script></span></span></li><li class="js-paper-rank-work_50024765 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="50024765"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 50024765, container: ".js-paper-rank-work_50024765", }); 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$(".js-view-count[data-work-id=50024765]").text(description); $(".js-view-count-work_50024765").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_50024765").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="50024765"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">8</a>  </div><span class="InlineList-item-text u-textTruncate u-pl9x"><a class="InlineList-item-text" data-has-card-for-ri="7099" href="https://www.academia.edu/Documents/in/Case_Studies">Case Studies</a>, <script data-card-contents-for-ri="7099" type="text/json">{"id":7099,"name":"Case Studies","url":"https://www.academia.edu/Documents/in/Case_Studies?f_ri=22247","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="22247" href="https://www.academia.edu/Documents/in/Traffic_control">Traffic control</a>, <script data-card-contents-for-ri="22247" type="text/json">{"id":22247,"name":"Traffic control","url":"https://www.academia.edu/Documents/in/Traffic_control?f_ri=22247","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="71258" href="https://www.academia.edu/Documents/in/Traffic_Safety">Traffic Safety</a>, <script data-card-contents-for-ri="71258" type="text/json">{"id":71258,"name":"Traffic Safety","url":"https://www.academia.edu/Documents/in/Traffic_Safety?f_ri=22247","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="96047" href="https://www.academia.edu/Documents/in/Case_Study">Case Study</a><script data-card-contents-for-ri="96047" type="text/json">{"id":96047,"name":"Case Study","url":"https://www.academia.edu/Documents/in/Case_Study?f_ri=22247","nofollow":false}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=50024765]'), work: {"id":50024765,"title":"Sense and Nonsense About Shared Space - For an Objective View of a Popular Planning Concept","created_at":"2021-07-17T11:49:43.688-07:00","url":"https://www.academia.edu/50024765/Sense_and_Nonsense_About_Shared_Space_For_an_Objective_View_of_a_Popular_Planning_Concept?f_ri=22247","dom_id":"work_50024765","summary":null,"downloadable_attachments":[{"id":68163588,"asset_id":50024765,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":32825391,"first_name":"Rob","last_name":"Methorst","domain_name":"rug","page_name":"RobMethorst","display_name":"Rob Methorst","profile_url":"https://rug.academia.edu/RobMethorst?f_ri=22247","photo":"/images/s65_no_pic.png"}],"research_interests":[{"id":7099,"name":"Case Studies","url":"https://www.academia.edu/Documents/in/Case_Studies?f_ri=22247","nofollow":false},{"id":22247,"name":"Traffic control","url":"https://www.academia.edu/Documents/in/Traffic_control?f_ri=22247","nofollow":false},{"id":71258,"name":"Traffic Safety","url":"https://www.academia.edu/Documents/in/Traffic_Safety?f_ri=22247","nofollow":false},{"id":96047,"name":"Case Study","url":"https://www.academia.edu/Documents/in/Case_Study?f_ri=22247","nofollow":false},{"id":232629,"name":"Open Space","url":"https://www.academia.edu/Documents/in/Open_Space?f_ri=22247"},{"id":547785,"name":"Sea routes \u0026 land roads","url":"https://www.academia.edu/Documents/in/Sea_routes_and_land_roads?f_ri=22247"},{"id":733620,"name":"Signs","url":"https://www.academia.edu/Documents/in/Signs?f_ri=22247"},{"id":805035,"name":"Shared Space","url":"https://www.academia.edu/Documents/in/Shared_Space?f_ri=22247"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_78406800" data-work_id="78406800" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/78406800/Real_Time_Traffic_Management_System">Real-Time Traffic Management System</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">Monitoring traffic efficiently has been one of the biggest modern day problems. As population has exponentially increased in the last century, the same effect has been observed on vehicles. This has put tremendous pressure on the existent... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_78406800" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">Monitoring traffic efficiently has been one of the biggest modern day problems. As population has exponentially increased in the last century, the same effect has been observed on vehicles. This has put tremendous pressure on the existent traffic systems. Even today, several traffic systems work with the concept of fixed time slots attached to each traffic light while overlooking the density of traffic at that junction. This causes millions of people to waste their precious time in traffic while concurrently affecting the nature through air and noise pollution. Another consequence of this waiting is the toll on the mental health of the commuters. To overcome these problems, we propose a system that manages traffic by taking the primary factor of real time traffic density into consideration. This system utilizes cameras along with image processing to achieve its goal. It ensures that the lanes switch based on the number of vehicles, consequently cutting down waiting periods while reducing pollution substantially.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/78406800" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="ae7e666e66c3983510c99e179b0b19f4" rel="nofollow" data-download="{"attachment_id":85465479,"asset_id":78406800,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/85465479/download_file?st=MTczMjQyMjgxOCw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="6079060" href="https://independent.academia.edu/IJRASETPublication">IJRASET Publication</a><script data-card-contents-for-user="6079060" type="text/json">{"id":6079060,"first_name":"IJRASET","last_name":"Publication","domain_name":"independent","page_name":"IJRASETPublication","display_name":"IJRASET Publication","profile_url":"https://independent.academia.edu/IJRASETPublication?f_ri=22247","photo":"https://0.academia-photos.com/6079060/2549300/33111525/s65_ijraset.publication.jpg"}</script></span></span></li><li class="js-paper-rank-work_78406800 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="78406800"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 78406800, container: ".js-paper-rank-work_78406800", }); });</script></li><li class="js-percentile-work_78406800 InlineList-item InlineList-item--bordered hidden u-tcGrayDark"><span class="percentile-widget hidden"><span class="u-mr2x percentile-widget" style="display: none">•</span><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 78406800; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-percentile-work_78406800"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></li><li class="js-view-count-work_78406800 InlineList-item InlineList-item--bordered hidden"><div><span><span class="js-view-count view-count u-mr2x" data-work-id="78406800"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 78406800; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=78406800]").text(description); $(".js-view-count-work_78406800").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_78406800").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="78406800"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">3</a>  </div><span class="InlineList-item-text u-textTruncate u-pl9x"><a class="InlineList-item-text" data-has-card-for-ri="22247" href="https://www.academia.edu/Documents/in/Traffic_control">Traffic control</a>, <script data-card-contents-for-ri="22247" type="text/json">{"id":22247,"name":"Traffic control","url":"https://www.academia.edu/Documents/in/Traffic_control?f_ri=22247","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="47295" href="https://www.academia.edu/Documents/in/Traffic_Management">Traffic Management</a>, <script data-card-contents-for-ri="47295" type="text/json">{"id":47295,"name":"Traffic Management","url":"https://www.academia.edu/Documents/in/Traffic_Management?f_ri=22247","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="71848" href="https://www.academia.edu/Documents/in/Real_Time_Sensor_Surveillance">Real Time Sensor Surveillance</a><script data-card-contents-for-ri="71848" type="text/json">{"id":71848,"name":"Real Time Sensor Surveillance","url":"https://www.academia.edu/Documents/in/Real_Time_Sensor_Surveillance?f_ri=22247","nofollow":false}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=78406800]'), work: {"id":78406800,"title":"Real-Time Traffic Management System","created_at":"2022-05-04T02:34:40.576-07:00","url":"https://www.academia.edu/78406800/Real_Time_Traffic_Management_System?f_ri=22247","dom_id":"work_78406800","summary":"Monitoring traffic efficiently has been one of the biggest modern day problems. As population has exponentially increased in the last century, the same effect has been observed on vehicles. This has put tremendous pressure on the existent traffic systems. Even today, several traffic systems work with the concept of fixed time slots attached to each traffic light while overlooking the density of traffic at that junction. This causes millions of people to waste their precious time in traffic while concurrently affecting the nature through air and noise pollution. Another consequence of this waiting is the toll on the mental health of the commuters. To overcome these problems, we propose a system that manages traffic by taking the primary factor of real time traffic density into consideration. This system utilizes cameras along with image processing to achieve its goal. It ensures that the lanes switch based on the number of vehicles, consequently cutting down waiting periods while reducing pollution substantially.","downloadable_attachments":[{"id":85465479,"asset_id":78406800,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":6079060,"first_name":"IJRASET","last_name":"Publication","domain_name":"independent","page_name":"IJRASETPublication","display_name":"IJRASET Publication","profile_url":"https://independent.academia.edu/IJRASETPublication?f_ri=22247","photo":"https://0.academia-photos.com/6079060/2549300/33111525/s65_ijraset.publication.jpg"}],"research_interests":[{"id":22247,"name":"Traffic control","url":"https://www.academia.edu/Documents/in/Traffic_control?f_ri=22247","nofollow":false},{"id":47295,"name":"Traffic Management","url":"https://www.academia.edu/Documents/in/Traffic_Management?f_ri=22247","nofollow":false},{"id":71848,"name":"Real Time Sensor Surveillance","url":"https://www.academia.edu/Documents/in/Real_Time_Sensor_Surveillance?f_ri=22247","nofollow":false}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_72202684" data-work_id="72202684" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/72202684/Vehicle_Remote_Support_and_Surveillance_System">Vehicle Remote Support and Surveillance System</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">The proposed design offers a complete solution to support and surveillance vehicles remotely. The offered algorithm allows a monitoring center to track vehicles; diagnoses fault remotely, control the traffic and control CO emission. The... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_72202684" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">The proposed design offers a complete solution to support and surveillance vehicles remotely. The offered algorithm allows a monitoring center to track vehicles; diagnoses fault remotely, control the traffic and control CO emission. The system is programmed to scan the on-board diagnostic OBD periodically or based on request to check if there are any faults and read all the available sensors, then make an early fault prediction based on the sensor readings, an experience with the vehicle type and fault history. It is so useful for people who are not familiar with fault diagnosis as well as the maintenance center. The system offers tracking the vehicle remotely, which protects it against theft and warn the driver if it exceeds the speed limit according to its location. Finally, it allows the user to report any traffic congestion and allows a vehicle navigator to be up to date with the traffic condition based on the other system’s user feedback.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/72202684" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="78931b26a1b37962c07e65c14c2baaa8" rel="nofollow" data-download="{"attachment_id":81224164,"asset_id":72202684,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/81224164/download_file?st=MTczMjQyMjgxOCw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="180764997" href="https://piratesofthenet.academia.edu/RamzyRahalAli">Ramzy Rahal Ali</a><script data-card-contents-for-user="180764997" type="text/json">{"id":180764997,"first_name":"Ramzy","last_name":"Rahal Ali","domain_name":"piratesofthenet","page_name":"RamzyRahalAli","display_name":"Ramzy Rahal Ali","profile_url":"https://piratesofthenet.academia.edu/RamzyRahalAli?f_ri=22247","photo":"/images/s65_no_pic.png"}</script></span></span></li><li class="js-paper-rank-work_72202684 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="72202684"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 72202684, container: ".js-paper-rank-work_72202684", }); 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The offered algorithm allows a monitoring center to track vehicles; diagnoses fault remotely, control the traffic and control CO emission. The system is programmed to scan the on-board diagnostic OBD periodically or based on request to check if there are any faults and read all the available sensors, then make an early fault prediction based on the sensor readings, an experience with the vehicle type and fault history. It is so useful for people who are not familiar with fault diagnosis as well as the maintenance center. The system offers tracking the vehicle remotely, which protects it against theft and warn the driver if it exceeds the speed limit according to its location. Finally, it allows the user to report any traffic congestion and allows a vehicle navigator to be up to date with the traffic condition based on the other system’s user feedback.","downloadable_attachments":[{"id":81224164,"asset_id":72202684,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":180764997,"first_name":"Ramzy","last_name":"Rahal Ali","domain_name":"piratesofthenet","page_name":"RamzyRahalAli","display_name":"Ramzy Rahal Ali","profile_url":"https://piratesofthenet.academia.edu/RamzyRahalAli?f_ri=22247","photo":"/images/s65_no_pic.png"}],"research_interests":[{"id":422,"name":"Computer Science","url":"https://www.academia.edu/Documents/in/Computer_Science?f_ri=22247","nofollow":false},{"id":22247,"name":"Traffic control","url":"https://www.academia.edu/Documents/in/Traffic_control?f_ri=22247","nofollow":false},{"id":104188,"name":"Vehicle Tracking Systems","url":"https://www.academia.edu/Documents/in/Vehicle_Tracking_Systems?f_ri=22247","nofollow":false},{"id":161944,"name":"Tracking Vehicles in Real Time","url":"https://www.academia.edu/Documents/in/Tracking_Vehicles_in_Real_Time?f_ri=22247","nofollow":false},{"id":491363,"name":"Vehicle Tracking","url":"https://www.academia.edu/Documents/in/Vehicle_Tracking?f_ri=22247"},{"id":784872,"name":"Accident Reporting","url":"https://www.academia.edu/Documents/in/Accident_Reporting?f_ri=22247"},{"id":1182010,"name":"Electrical Electronic Engineering","url":"https://www.academia.edu/Documents/in/Electrical_Electronic_Engineering-1?f_ri=22247"},{"id":1332764,"name":"GPS Vehicle Tracking","url":"https://www.academia.edu/Documents/in/GPS_Vehicle_Tracking?f_ri=22247"},{"id":1717634,"name":"Emissions-related diagnostics","url":"https://www.academia.edu/Documents/in/Emissions-related_diagnostics?f_ri=22247"},{"id":1717635,"name":"Fault remotely diagnostic","url":"https://www.academia.edu/Documents/in/Fault_remotely_diagnostic?f_ri=22247"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_18083375 coauthored" data-work_id="18083375" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/18083375/Freeway_traffic_control_considering_capacity_drop_phenomena_comparison_of_different_MPC_schemes">Freeway traffic control considering capacity drop phenomena: comparison of different MPC schemes</a></div></div><div class="u-pb4x u-mt3x"></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" 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InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="38195960" href="https://independent.academia.edu/LorenzoMaggi2">Lorenzo Maggi</a><script data-card-contents-for-user="38195960" type="text/json">{"id":38195960,"first_name":"Lorenzo","last_name":"Maggi","domain_name":"independent","page_name":"LorenzoMaggi2","display_name":"Lorenzo Maggi","profile_url":"https://independent.academia.edu/LorenzoMaggi2?f_ri=22247","photo":"/images/s65_no_pic.png"}</script></span></span><span class="u-displayInlineBlock InlineList-item-text"> and <span class="u-textDecorationUnderline u-clickable InlineList-item-text js-work-more-authors-18083375">+2</span><div class="hidden js-additional-users-18083375"><div><span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a href="https://unige-it.academia.edu/SilviaSiri">Silvia Siri</a></span></div><div><span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a href="https://independent.academia.edu/SimonaSacone">Simona Sacone</a></span></div></div></span><script>(function(){ var popoverSettings = { el: $('.js-work-more-authors-18083375'), placement: 'bottom', hide_delay: 200, html: true, content: function(){ return $('.js-additional-users-18083375').html(); } } new HoverPopover(popoverSettings); })();</script></li><li class="js-paper-rank-work_18083375 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="18083375"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 18083375, container: ".js-paper-rank-work_18083375", }); });</script></li><li class="js-percentile-work_18083375 InlineList-item InlineList-item--bordered hidden u-tcGrayDark"><span class="percentile-widget 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$(".js-view-count[data-work-id=18083375]").text(description); $(".js-view-count-work_18083375").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_18083375").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="18083375"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">2</a>  </div><span class="InlineList-item-text u-textTruncate u-pl9x"><a class="InlineList-item-text" data-has-card-for-ri="10463" href="https://www.academia.edu/Documents/in/Model_Predictive_Control_MPC_">Model Predictive Control (MPC)</a>, <script data-card-contents-for-ri="10463" type="text/json">{"id":10463,"name":"Model Predictive Control (MPC)","url":"https://www.academia.edu/Documents/in/Model_Predictive_Control_MPC_?f_ri=22247","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="22247" href="https://www.academia.edu/Documents/in/Traffic_control">Traffic control</a><script data-card-contents-for-ri="22247" type="text/json">{"id":22247,"name":"Traffic control","url":"https://www.academia.edu/Documents/in/Traffic_control?f_ri=22247","nofollow":false}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=18083375]'), work: {"id":18083375,"title":"Freeway traffic control considering capacity drop phenomena: comparison of different MPC schemes","created_at":"2015-11-10T06:43:16.246-08:00","url":"https://www.academia.edu/18083375/Freeway_traffic_control_considering_capacity_drop_phenomena_comparison_of_different_MPC_schemes?f_ri=22247","dom_id":"work_18083375","summary":null,"downloadable_attachments":[{"id":39866326,"asset_id":18083375,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":38195960,"first_name":"Lorenzo","last_name":"Maggi","domain_name":"independent","page_name":"LorenzoMaggi2","display_name":"Lorenzo Maggi","profile_url":"https://independent.academia.edu/LorenzoMaggi2?f_ri=22247","photo":"/images/s65_no_pic.png"},{"id":29966050,"first_name":"Silvia","last_name":"Siri","domain_name":"unige-it","page_name":"SilviaSiri","display_name":"Silvia Siri","profile_url":"https://unige-it.academia.edu/SilviaSiri?f_ri=22247","photo":"https://0.academia-photos.com/29966050/8641847/9651715/s65_silvia.siri.jpg"},{"id":30910300,"first_name":"Simona","last_name":"Sacone","domain_name":"independent","page_name":"SimonaSacone","display_name":"Simona Sacone","profile_url":"https://independent.academia.edu/SimonaSacone?f_ri=22247","photo":"/images/s65_no_pic.png"}],"research_interests":[{"id":10463,"name":"Model Predictive Control (MPC)","url":"https://www.academia.edu/Documents/in/Model_Predictive_Control_MPC_?f_ri=22247","nofollow":false},{"id":22247,"name":"Traffic control","url":"https://www.academia.edu/Documents/in/Traffic_control?f_ri=22247","nofollow":false}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_5706624" data-work_id="5706624" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/5706624/Intelligent_System_for_Freeway_Ramp_Metering_Control">Intelligent System for Freeway Ramp Metering Control</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">The number of techniques implemented in subsystems of the Intelligent System of infrastructure in transportation system in terms of agents for signal control, ramp metering, detecting incidents is numerous. Challenges, however, are still... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_5706624" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">The number of techniques implemented in subsystems of the Intelligent System of infrastructure in transportation system in terms of agents for signal control, ramp metering, detecting incidents is numerous. Challenges, however, are still there for the researchers to optimize traffic operations. The aim of this paper is to prove the ability of artificial intelligence technique known as reinforcement learning implemented in intelligent system for freeway control. Intelligent agents are implemented as controllers in order to provide optimal performance on the freeway corridor via ramp metering control on a corridor. The algorithm used in the research was Q learning algorithm. The results are promising proving that the technique is capable for optimal control of entrance freeway ramps and suitable for building the intelligent system of the freeway.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/5706624" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="74c8b6c4275255dbe300bc30a5a0dde6" rel="nofollow" data-download="{"attachment_id":32750894,"asset_id":5706624,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/32750894/download_file?st=MTczMjQyMjgxOCw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="5117328" href="https://gacwnlk.academia.edu/ZoranGacovski">Zoran Gacovski</a><script data-card-contents-for-user="5117328" type="text/json">{"id":5117328,"first_name":"Zoran","last_name":"Gacovski","domain_name":"gacwnlk","page_name":"ZoranGacovski","display_name":"Zoran Gacovski","profile_url":"https://gacwnlk.academia.edu/ZoranGacovski?f_ri=22247","photo":"https://0.academia-photos.com/5117328/2242125/2622681/s65_zoran.gacovski.jpg"}</script></span></span></li><li class="js-paper-rank-work_5706624 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="5706624"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 5706624, container: ".js-paper-rank-work_5706624", }); 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$(".js-view-count[data-work-id=5706624]").text(description); $(".js-view-count-work_5706624").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_5706624").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="5706624"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">2</a>  </div><span class="InlineList-item-text u-textTruncate u-pl9x"><a class="InlineList-item-text" data-has-card-for-ri="1688" href="https://www.academia.edu/Documents/in/Reinforcement_Learning">Reinforcement Learning</a>, <script data-card-contents-for-ri="1688" type="text/json">{"id":1688,"name":"Reinforcement Learning","url":"https://www.academia.edu/Documents/in/Reinforcement_Learning?f_ri=22247","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="22247" href="https://www.academia.edu/Documents/in/Traffic_control">Traffic control</a><script data-card-contents-for-ri="22247" type="text/json">{"id":22247,"name":"Traffic control","url":"https://www.academia.edu/Documents/in/Traffic_control?f_ri=22247","nofollow":false}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=5706624]'), work: {"id":5706624,"title":"Intelligent System for Freeway Ramp Metering Control","created_at":"2014-01-13T19:48:08.772-08:00","url":"https://www.academia.edu/5706624/Intelligent_System_for_Freeway_Ramp_Metering_Control?f_ri=22247","dom_id":"work_5706624","summary":"The number of techniques implemented in subsystems of the Intelligent System of infrastructure in transportation system in terms of agents for signal control, ramp metering, detecting incidents is numerous. Challenges, however, are still there for the researchers to optimize traffic operations. The aim of this paper is to prove the ability of artificial intelligence technique known as reinforcement learning implemented in intelligent system for freeway control. Intelligent agents are implemented as controllers in order to provide optimal performance on the freeway corridor via ramp metering control on a corridor. The algorithm used in the research was Q learning algorithm. The results are promising proving that the technique is capable for optimal control of entrance freeway ramps and suitable for building the intelligent system of the freeway.","downloadable_attachments":[{"id":32750894,"asset_id":5706624,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":5117328,"first_name":"Zoran","last_name":"Gacovski","domain_name":"gacwnlk","page_name":"ZoranGacovski","display_name":"Zoran Gacovski","profile_url":"https://gacwnlk.academia.edu/ZoranGacovski?f_ri=22247","photo":"https://0.academia-photos.com/5117328/2242125/2622681/s65_zoran.gacovski.jpg"}],"research_interests":[{"id":1688,"name":"Reinforcement Learning","url":"https://www.academia.edu/Documents/in/Reinforcement_Learning?f_ri=22247","nofollow":false},{"id":22247,"name":"Traffic control","url":"https://www.academia.edu/Documents/in/Traffic_control?f_ri=22247","nofollow":false}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 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class="InlineList-item"><div class="download"><a id="74783fbe7e9951d2e2abb16236107996" rel="nofollow" data-download="{"attachment_id":49717991,"asset_id":4655457,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/49717991/download_file?st=MTczMjQyMjgxOCw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="5897792" href="https://independent.academia.edu/YangQ">QI Yang</a><script data-card-contents-for-user="5897792" type="text/json">{"id":5897792,"first_name":"QI","last_name":"Yang","domain_name":"independent","page_name":"YangQ","display_name":"QI Yang","profile_url":"https://independent.academia.edu/YangQ?f_ri=22247","photo":"/images/s65_no_pic.png"}</script></span></span></li><li class="js-paper-rank-work_4655457 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="4655457"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 4655457, container: ".js-paper-rank-work_4655457", }); });</script></li><li class="js-percentile-work_4655457 InlineList-item InlineList-item--bordered hidden u-tcGrayDark"><span class="percentile-widget hidden"><span class="u-mr2x percentile-widget" style="display: none">•</span><span class="u-mr2x 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});</script></span><script>$(function() { $(".js-view-count-work_4655457").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="4655457"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">14</a>  </div><span class="InlineList-item-text u-textTruncate u-pl10x"><a class="InlineList-item-text" data-has-card-for-ri="48" href="https://www.academia.edu/Documents/in/Engineering">Engineering</a>, <script data-card-contents-for-ri="48" type="text/json">{"id":48,"name":"Engineering","url":"https://www.academia.edu/Documents/in/Engineering?f_ri=22247","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="22247" href="https://www.academia.edu/Documents/in/Traffic_control">Traffic control</a>, <script data-card-contents-for-ri="22247" type="text/json">{"id":22247,"name":"Traffic control","url":"https://www.academia.edu/Documents/in/Traffic_control?f_ri=22247","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="47295" href="https://www.academia.edu/Documents/in/Traffic_Management">Traffic Management</a>, <script data-card-contents-for-ri="47295" type="text/json">{"id":47295,"name":"Traffic Management","url":"https://www.academia.edu/Documents/in/Traffic_Management?f_ri=22247","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="50201" href="https://www.academia.edu/Documents/in/Object_Oriented_Design">Object Oriented Design</a><script data-card-contents-for-ri="50201" type="text/json">{"id":50201,"name":"Object Oriented Design","url":"https://www.academia.edu/Documents/in/Object_Oriented_Design?f_ri=22247","nofollow":false}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=4655457]'), work: {"id":4655457,"title":"A Microscopic Traffic Simulator for evaluation of dynamic traffic management systems","created_at":"2013-10-02T10:38:08.660-07:00","url":"https://www.academia.edu/4655457/A_Microscopic_Traffic_Simulator_for_evaluation_of_dynamic_traffic_management_systems?f_ri=22247","dom_id":"work_4655457","summary":null,"downloadable_attachments":[{"id":49717991,"asset_id":4655457,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":5897792,"first_name":"QI","last_name":"Yang","domain_name":"independent","page_name":"YangQ","display_name":"QI Yang","profile_url":"https://independent.academia.edu/YangQ?f_ri=22247","photo":"/images/s65_no_pic.png"}],"research_interests":[{"id":48,"name":"Engineering","url":"https://www.academia.edu/Documents/in/Engineering?f_ri=22247","nofollow":false},{"id":22247,"name":"Traffic control","url":"https://www.academia.edu/Documents/in/Traffic_control?f_ri=22247","nofollow":false},{"id":47295,"name":"Traffic Management","url":"https://www.academia.edu/Documents/in/Traffic_Management?f_ri=22247","nofollow":false},{"id":50201,"name":"Object Oriented Design","url":"https://www.academia.edu/Documents/in/Object_Oriented_Design?f_ri=22247","nofollow":false},{"id":98503,"name":"Graphic User Interface Design","url":"https://www.academia.edu/Documents/in/Graphic_User_Interface_Design?f_ri=22247"},{"id":127114,"name":"Simulators","url":"https://www.academia.edu/Documents/in/Simulators?f_ri=22247"},{"id":198527,"name":"Motion","url":"https://www.academia.edu/Documents/in/Motion?f_ri=22247"},{"id":228734,"name":"Dynamical System","url":"https://www.academia.edu/Documents/in/Dynamical_System?f_ri=22247"},{"id":238655,"name":"Implementation","url":"https://www.academia.edu/Documents/in/Implementation?f_ri=22247"},{"id":403511,"name":"Route Choice","url":"https://www.academia.edu/Documents/in/Route_Choice?f_ri=22247"},{"id":509514,"name":"Surveillance System","url":"https://www.academia.edu/Documents/in/Surveillance_System?f_ri=22247"},{"id":514518,"name":"Microscopic Traffic Simulation","url":"https://www.academia.edu/Documents/in/Microscopic_Traffic_Simulation?f_ri=22247"},{"id":1009416,"name":"Real Time Traffic","url":"https://www.academia.edu/Documents/in/Real_Time_Traffic?f_ri=22247"},{"id":1208732,"name":"Simulation Model","url":"https://www.academia.edu/Documents/in/Simulation_Model?f_ri=22247"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_6061477" data-work_id="6061477" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/6061477/Managing_speed_at_school_and_playground_zones">Managing speed at school and playground zones</a></div></div><div class="u-pb4x u-mt3x"></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/6061477" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="77353769d88d6550cf8d835b05698ae3" rel="nofollow" data-download="{"attachment_id":49034380,"asset_id":6061477,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/49034380/download_file?st=MTczMjQyMjgxOCw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down 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href="https://www.academia.edu/Documents/in/Psychology">Psychology</a>, <script data-card-contents-for-ri="221" type="text/json">{"id":221,"name":"Psychology","url":"https://www.academia.edu/Documents/in/Psychology?f_ri=22247","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="2358" href="https://www.academia.edu/Documents/in/Road_safety">Road safety</a>, <script data-card-contents-for-ri="2358" type="text/json">{"id":2358,"name":"Road safety","url":"https://www.academia.edu/Documents/in/Road_safety?f_ri=22247","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="22247" href="https://www.academia.edu/Documents/in/Traffic_control">Traffic control</a>, <script data-card-contents-for-ri="22247" type="text/json">{"id":22247,"name":"Traffic control","url":"https://www.academia.edu/Documents/in/Traffic_control?f_ri=22247","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="49610" href="https://www.academia.edu/Documents/in/Schools">Schools</a><script data-card-contents-for-ri="49610" type="text/json">{"id":49610,"name":"Schools","url":"https://www.academia.edu/Documents/in/Schools?f_ri=22247","nofollow":false}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=6061477]'), work: {"id":6061477,"title":"Managing speed at school and playground zones","created_at":"2014-02-13T04:16:32.197-08:00","url":"https://www.academia.edu/6061477/Managing_speed_at_school_and_playground_zones?f_ri=22247","dom_id":"work_6061477","summary":null,"downloadable_attachments":[{"id":49034380,"asset_id":6061477,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":9117202,"first_name":"Lina","last_name":"Kattan","domain_name":"ucalgary","page_name":"LKattan","display_name":"Lina Kattan","profile_url":"https://ucalgary.academia.edu/LKattan?f_ri=22247","photo":"/images/s65_no_pic.png"}],"research_interests":[{"id":221,"name":"Psychology","url":"https://www.academia.edu/Documents/in/Psychology?f_ri=22247","nofollow":false},{"id":2358,"name":"Road safety","url":"https://www.academia.edu/Documents/in/Road_safety?f_ri=22247","nofollow":false},{"id":22247,"name":"Traffic control","url":"https://www.academia.edu/Documents/in/Traffic_control?f_ri=22247","nofollow":false},{"id":49610,"name":"Schools","url":"https://www.academia.edu/Documents/in/Schools?f_ri=22247","nofollow":false},{"id":64568,"name":"Humans","url":"https://www.academia.edu/Documents/in/Humans?f_ri=22247"},{"id":141099,"name":"Speed","url":"https://www.academia.edu/Documents/in/Speed?f_ri=22247"},{"id":356669,"name":"Alberta","url":"https://www.academia.edu/Documents/in/Alberta?f_ri=22247"},{"id":399641,"name":"Accident analysis and prevention","url":"https://www.academia.edu/Documents/in/Accident_analysis_and_prevention?f_ri=22247"},{"id":410370,"name":"Public health systems and services research","url":"https://www.academia.edu/Documents/in/Public_health_systems_and_services_research-1?f_ri=22247"},{"id":535415,"name":"Environment Design","url":"https://www.academia.edu/Documents/in/Environment_Design?f_ri=22247"},{"id":992851,"name":"Traffic Accident","url":"https://www.academia.edu/Documents/in/Traffic_Accident?f_ri=22247"},{"id":1231577,"name":"Accident Prevention","url":"https://www.academia.edu/Documents/in/Accident_Prevention?f_ri=22247"},{"id":2248971,"name":"Automobile driving","url":"https://www.academia.edu/Documents/in/Automobile_driving?f_ri=22247"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_70010280" data-work_id="70010280" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/70010280/A_Traffic_Object_Detection_System_for_Road_Traffic_Measurement_and_Management">A Traffic Object Detection System for Road Traffic Measurement and Management</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">OIS is a new Optical Information System for road traffic observation and management. The complete system architecture from the sonsor for automatic traffic detection up to the traffic light management for a wide area is designed under the... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_70010280" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">OIS is a new Optical Information System for road traffic observation and management. The complete system architecture from the sonsor for automatic traffic detection up to the traffic light management for a wide area is designed under the requirements of an interlligent transportation system. Particular features of this system are the vision sensors with intergrated computational and real-time capabilities, real-tim algorithms for image processing and a new approach for dynamic traffic light management for a single intersection as well as for a wide area. The developed real-time algorithms for image processing extract traffic data even at night and under bad weather conditions. This approach opens the opportunity to identify and specify each traffic object, its location, its speed and other important object information. Furthermore the algorithms are able to identify accidents, and non-motorized traffic like pedestrians and bicyclists. Combining all these single information the syst...</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/70010280" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="d3d81aa55fb80a9d5d43c6c3d684d1ac" rel="nofollow" data-download="{"attachment_id":79899937,"asset_id":70010280,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/79899937/download_file?st=MTczMjQyMjgxOCw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="47055331" href="https://independent.academia.edu/CarstenDalaff">Carsten Dalaff</a><script data-card-contents-for-user="47055331" type="text/json">{"id":47055331,"first_name":"Carsten","last_name":"Dalaff","domain_name":"independent","page_name":"CarstenDalaff","display_name":"Carsten Dalaff","profile_url":"https://independent.academia.edu/CarstenDalaff?f_ri=22247","photo":"/images/s65_no_pic.png"}</script></span></span></li><li class="js-paper-rank-work_70010280 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="70010280"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 70010280, container: ".js-paper-rank-work_70010280", }); 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Ioslovich","profile_url":"https://independent.academia.edu/IlyaIoslovich?f_ri=22247","photo":"https://0.academia-photos.com/53695950/15296890/15955685/s65_ilya.ioslovich.jpg"}],"research_interests":[{"id":60,"name":"Mechanical Engineering","url":"https://www.academia.edu/Documents/in/Mechanical_Engineering?f_ri=22247","nofollow":false},{"id":305,"name":"Applied Mathematics","url":"https://www.academia.edu/Documents/in/Applied_Mathematics?f_ri=22247","nofollow":false},{"id":2200,"name":"Optimal Control","url":"https://www.academia.edu/Documents/in/Optimal_Control?f_ri=22247","nofollow":false},{"id":4202,"name":"Control Engineering","url":"https://www.academia.edu/Documents/in/Control_Engineering?f_ri=22247","nofollow":false},{"id":6177,"name":"Modeling","url":"https://www.academia.edu/Documents/in/Modeling?f_ri=22247"},{"id":22247,"name":"Traffic control","url":"https://www.academia.edu/Documents/in/Traffic_control?f_ri=22247"},{"id":47295,"name":"Traffic 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js-work-card work_25243800" data-work_id="25243800" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/25243800/Gaze_Behavior_while_Crossing_Complex_Intersections">Gaze Behavior while Crossing Complex Intersections</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">ABSTRACT: Background. Crossing the street is a complex task that involves gathering, processing, and acting on information that is time dependent. The gaze behavior of subjects has been previously studied on increasingly complex and... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_25243800" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">ABSTRACT: Background. Crossing the street is a complex task that involves gathering, processing, and acting on information that is time dependent. The gaze behavior of subjects has been previously studied on increasingly complex and dynamic tasks such as making tea, walking indoors, and driving. The purpose of this study was to assess how normally sighted people use their vision to</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/25243800" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="f140929c4281c995d0cbe66e4b4259e4" rel="nofollow" data-download="{"attachment_id":45549791,"asset_id":25243800,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/45549791/download_file?st=MTczMjQyMjgxOCw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="48586965" href="https://independent.academia.edu/DuaneGeruschat">Duane Geruschat</a><script data-card-contents-for-user="48586965" type="text/json">{"id":48586965,"first_name":"Duane","last_name":"Geruschat","domain_name":"independent","page_name":"DuaneGeruschat","display_name":"Duane Geruschat","profile_url":"https://independent.academia.edu/DuaneGeruschat?f_ri=22247","photo":"/images/s65_no_pic.png"}</script></span></span></li><li class="js-paper-rank-work_25243800 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="25243800"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 25243800, container: ".js-paper-rank-work_25243800", }); 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$(".js-view-count[data-work-id=25243800]").text(description); $(".js-view-count-work_25243800").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_25243800").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="25243800"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">14</a>  </div><span class="InlineList-item-text u-textTruncate u-pl10x"><a class="InlineList-item-text" data-has-card-for-ri="22247" href="https://www.academia.edu/Documents/in/Traffic_control">Traffic control</a>, <script data-card-contents-for-ri="22247" type="text/json">{"id":22247,"name":"Traffic control","url":"https://www.academia.edu/Documents/in/Traffic_control?f_ri=22247","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="45666" href="https://www.academia.edu/Documents/in/Automobiles">Automobiles</a>, <script data-card-contents-for-ri="45666" type="text/json">{"id":45666,"name":"Automobiles","url":"https://www.academia.edu/Documents/in/Automobiles?f_ri=22247","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="64568" href="https://www.academia.edu/Documents/in/Humans">Humans</a>, <script data-card-contents-for-ri="64568" type="text/json">{"id":64568,"name":"Humans","url":"https://www.academia.edu/Documents/in/Humans?f_ri=22247","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="73118" href="https://www.academia.edu/Documents/in/Walking">Walking</a><script data-card-contents-for-ri="73118" type="text/json">{"id":73118,"name":"Walking","url":"https://www.academia.edu/Documents/in/Walking?f_ri=22247","nofollow":false}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=25243800]'), work: {"id":25243800,"title":"Gaze Behavior while Crossing Complex Intersections","created_at":"2016-05-11T13:03:12.441-07:00","url":"https://www.academia.edu/25243800/Gaze_Behavior_while_Crossing_Complex_Intersections?f_ri=22247","dom_id":"work_25243800","summary":"ABSTRACT: Background. Crossing the street is a complex task that involves gathering, processing, and acting on information that is time dependent. The gaze behavior of subjects has been previously studied on increasingly complex and dynamic tasks such as making tea, walking indoors, and driving. The purpose of this study was to assess how normally sighted people use their vision to","downloadable_attachments":[{"id":45549791,"asset_id":25243800,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":48586965,"first_name":"Duane","last_name":"Geruschat","domain_name":"independent","page_name":"DuaneGeruschat","display_name":"Duane Geruschat","profile_url":"https://independent.academia.edu/DuaneGeruschat?f_ri=22247","photo":"/images/s65_no_pic.png"}],"research_interests":[{"id":22247,"name":"Traffic control","url":"https://www.academia.edu/Documents/in/Traffic_control?f_ri=22247","nofollow":false},{"id":45666,"name":"Automobiles","url":"https://www.academia.edu/Documents/in/Automobiles?f_ri=22247","nofollow":false},{"id":64568,"name":"Humans","url":"https://www.academia.edu/Documents/in/Humans?f_ri=22247","nofollow":false},{"id":73118,"name":"Walking","url":"https://www.academia.edu/Documents/in/Walking?f_ri=22247","nofollow":false},{"id":108586,"name":"Gaze Direction","url":"https://www.academia.edu/Documents/in/Gaze_Direction?f_ri=22247"},{"id":143507,"name":"Eye Movements","url":"https://www.academia.edu/Documents/in/Eye_Movements?f_ri=22247"},{"id":220371,"name":"Traffic Flow","url":"https://www.academia.edu/Documents/in/Traffic_Flow?f_ri=22247"},{"id":250581,"name":"Optometry and Vision Science","url":"https://www.academia.edu/Documents/in/Optometry_and_Vision_Science?f_ri=22247"},{"id":277066,"name":"Head","url":"https://www.academia.edu/Documents/in/Head?f_ri=22247"},{"id":289271,"name":"Aged","url":"https://www.academia.edu/Documents/in/Aged?f_ri=22247"},{"id":295155,"name":"Middle Aged","url":"https://www.academia.edu/Documents/in/Middle_Aged?f_ri=22247"},{"id":382075,"name":"Adult","url":"https://www.academia.edu/Documents/in/Adult?f_ri=22247"},{"id":394477,"name":"Time Dependent","url":"https://www.academia.edu/Documents/in/Time_Dependent?f_ri=22247"},{"id":453610,"name":"Eye Movement","url":"https://www.academia.edu/Documents/in/Eye_Movement?f_ri=22247"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_18105349" data-work_id="18105349" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/18105349/Hardware_in_the_loop_simulation">Hardware-in-the-loop simulation</a></div></div><div class="u-pb4x u-mt3x"></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/18105349" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="c6218797c9e3e449a48405232b548057" rel="nofollow" data-download="{"attachment_id":39878238,"asset_id":18105349,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/39878238/download_file?st=MTczMjQyMjgxOCw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="38057781" href="https://independent.academia.edu/BullockDarcy">Darcy Bullock</a><script data-card-contents-for-user="38057781" type="text/json">{"id":38057781,"first_name":"Darcy","last_name":"Bullock","domain_name":"independent","page_name":"BullockDarcy","display_name":"Darcy Bullock","profile_url":"https://independent.academia.edu/BullockDarcy?f_ri=22247","photo":"/images/s65_no_pic.png"}</script></span></span></li><li class="js-paper-rank-work_18105349 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="18105349"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 18105349, container: ".js-paper-rank-work_18105349", }); 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$(".js-view-count[data-work-id=18105349]").text(description); $(".js-view-count-work_18105349").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_18105349").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="18105349"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">11</a>  </div><span class="InlineList-item-text u-textTruncate u-pl10x"><a class="InlineList-item-text" data-has-card-for-ri="48" href="https://www.academia.edu/Documents/in/Engineering">Engineering</a>, <script data-card-contents-for-ri="48" type="text/json">{"id":48,"name":"Engineering","url":"https://www.academia.edu/Documents/in/Engineering?f_ri=22247","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="8422" href="https://www.academia.edu/Documents/in/Adaptive_Control">Adaptive Control</a>, <script data-card-contents-for-ri="8422" type="text/json">{"id":8422,"name":"Adaptive Control","url":"https://www.academia.edu/Documents/in/Adaptive_Control?f_ri=22247","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="22247" href="https://www.academia.edu/Documents/in/Traffic_control">Traffic control</a>, <script data-card-contents-for-ri="22247" type="text/json">{"id":22247,"name":"Traffic control","url":"https://www.academia.edu/Documents/in/Traffic_control?f_ri=22247","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="165565" href="https://www.academia.edu/Documents/in/Cost_effectiveness">Cost effectiveness</a><script data-card-contents-for-ri="165565" type="text/json">{"id":165565,"name":"Cost effectiveness","url":"https://www.academia.edu/Documents/in/Cost_effectiveness?f_ri=22247","nofollow":false}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=18105349]'), work: {"id":18105349,"title":"Hardware-in-the-loop simulation","created_at":"2015-11-10T12:58:24.750-08:00","url":"https://www.academia.edu/18105349/Hardware_in_the_loop_simulation?f_ri=22247","dom_id":"work_18105349","summary":null,"downloadable_attachments":[{"id":39878238,"asset_id":18105349,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":38057781,"first_name":"Darcy","last_name":"Bullock","domain_name":"independent","page_name":"BullockDarcy","display_name":"Darcy Bullock","profile_url":"https://independent.academia.edu/BullockDarcy?f_ri=22247","photo":"/images/s65_no_pic.png"}],"research_interests":[{"id":48,"name":"Engineering","url":"https://www.academia.edu/Documents/in/Engineering?f_ri=22247","nofollow":false},{"id":8422,"name":"Adaptive Control","url":"https://www.academia.edu/Documents/in/Adaptive_Control?f_ri=22247","nofollow":false},{"id":22247,"name":"Traffic control","url":"https://www.academia.edu/Documents/in/Traffic_control?f_ri=22247","nofollow":false},{"id":165565,"name":"Cost effectiveness","url":"https://www.academia.edu/Documents/in/Cost_effectiveness?f_ri=22247","nofollow":false},{"id":229390,"name":"Real Time","url":"https://www.academia.edu/Documents/in/Real_Time?f_ri=22247"},{"id":235574,"name":"Model development","url":"https://www.academia.edu/Documents/in/Model_development?f_ri=22247"},{"id":703835,"name":"Statistical Test","url":"https://www.academia.edu/Documents/in/Statistical_Test?f_ri=22247"},{"id":765148,"name":"Numerical computation","url":"https://www.academia.edu/Documents/in/Numerical_computation?f_ri=22247"},{"id":988973,"name":"Hardware In the Loop Simulation","url":"https://www.academia.edu/Documents/in/Hardware_In_the_Loop_Simulation?f_ri=22247"},{"id":1208732,"name":"Simulation Model","url":"https://www.academia.edu/Documents/in/Simulation_Model?f_ri=22247"},{"id":1781752,"name":"Control Algorithm","url":"https://www.academia.edu/Documents/in/Control_Algorithm?f_ri=22247"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_28634266" data-work_id="28634266" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/28634266/Traffic_Signal_Timing_via_Deep_Reinforcement_Learning">Traffic Signal Timing via Deep Reinforcement Learning</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">In this paper, we propose a set of algorithms to design signal timing plans via deep reinforcement learning. The core idea of this approach is to set up a deep neural network (DNN) to learn the Q-function of reinforcement learning from... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_28634266" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">In this paper, we propose a set of algorithms to design signal<br />timing plans via deep reinforcement learning.  The core idea of<br />this approach is to set up a deep neural network (DNN) to learn<br />the Q-function of reinforcement learning from the sampled traffic<br />state/control inputs and the corresponding traffic system<br />performance output. Based on the obtained DNN, we can find the<br />appropriate signal timing policies by implicitly modeling the<br />control actions and the change of system states. We explain the<br />possible benefits and implementation tricks of this new approach.<br />The relationships between this new approach and some existing<br />approaches are also carefully discussed.<br /><br />Citation: Li Li, Yisheng Lv, Fei-Yue Wang. Traffic signal timing via deep reinforcement learning. IEEE/CAA Journal of Automatica Sinica, 2016, 3(3): 247-254<br /><br />Video abstract: YouTube: <a href="https://www.youtube.com/watch?v=0tlF35qJ0sE&feature=youtu.be" rel="nofollow">https://www.youtube.com/watch?v=0tlF35qJ0sE&feature=youtu.be</a>;<br />Youku: <a href="http://v.youku.com/v_show/id_XMTcxMDcwMzU2NA==.html?beta" rel="nofollow">http://v.youku.com/v_show/id_XMTcxMDcwMzU2NA==.html?beta</a>&</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/28634266" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="8dd644ed89aacd71b8660e3d167c3d3e" rel="nofollow" data-download="{"attachment_id":49000339,"asset_id":28634266,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/49000339/download_file?st=MTczMjQyMjgxOCw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="53180586" href="https://independent.academia.edu/IEEECAAJAS">IEEE/CAA J. Autom. Sinica</a><script data-card-contents-for-user="53180586" type="text/json">{"id":53180586,"first_name":"IEEE/CAA","last_name":"J. Autom. Sinica","domain_name":"independent","page_name":"IEEECAAJAS","display_name":"IEEE/CAA J. Autom. Sinica","profile_url":"https://independent.academia.edu/IEEECAAJAS?f_ri=22247","photo":"https://0.academia-photos.com/53180586/14177798/22465909/s65_ieee_caa.j._autom._sinica.jpg"}</script></span></span></li><li class="js-paper-rank-work_28634266 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="28634266"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 28634266, container: ".js-paper-rank-work_28634266", }); });</script></li><li class="js-percentile-work_28634266 InlineList-item InlineList-item--bordered hidden u-tcGrayDark"><span class="percentile-widget hidden"><span class="u-mr2x percentile-widget" style="display: none">•</span><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 28634266; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-percentile-work_28634266"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></li><li class="js-view-count-work_28634266 InlineList-item InlineList-item--bordered hidden"><div><span><span class="js-view-count view-count u-mr2x" data-work-id="28634266"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 28634266; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=28634266]").text(description); $(".js-view-count-work_28634266").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_28634266").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="28634266"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">4</a>  </div><span class="InlineList-item-text u-textTruncate u-pl9x"><a class="InlineList-item-text" data-has-card-for-ri="1688" href="https://www.academia.edu/Documents/in/Reinforcement_Learning">Reinforcement Learning</a>, <script data-card-contents-for-ri="1688" type="text/json">{"id":1688,"name":"Reinforcement Learning","url":"https://www.academia.edu/Documents/in/Reinforcement_Learning?f_ri=22247","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="22247" href="https://www.academia.edu/Documents/in/Traffic_control">Traffic control</a>, <script data-card-contents-for-ri="22247" type="text/json">{"id":22247,"name":"Traffic control","url":"https://www.academia.edu/Documents/in/Traffic_control?f_ri=22247","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="81182" href="https://www.academia.edu/Documents/in/Deep_Learning">Deep Learning</a>, <script data-card-contents-for-ri="81182" type="text/json">{"id":81182,"name":"Deep Learning","url":"https://www.academia.edu/Documents/in/Deep_Learning?f_ri=22247","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="2532663" href="https://www.academia.edu/Documents/in/Deep_Reinforcement_Learning">Deep Reinforcement Learning</a><script data-card-contents-for-ri="2532663" type="text/json">{"id":2532663,"name":"Deep Reinforcement Learning","url":"https://www.academia.edu/Documents/in/Deep_Reinforcement_Learning?f_ri=22247","nofollow":false}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=28634266]'), work: {"id":28634266,"title":"Traffic Signal Timing via Deep Reinforcement Learning","created_at":"2016-09-20T18:45:43.746-07:00","url":"https://www.academia.edu/28634266/Traffic_Signal_Timing_via_Deep_Reinforcement_Learning?f_ri=22247","dom_id":"work_28634266","summary":"In this paper, we propose a set of algorithms to design signal\ntiming plans via deep reinforcement learning. The core idea of\nthis approach is to set up a deep neural network (DNN) to learn\nthe Q-function of reinforcement learning from the sampled traffic\nstate/control inputs and the corresponding traffic system\nperformance output. Based on the obtained DNN, we can find the\nappropriate signal timing policies by implicitly modeling the\ncontrol actions and the change of system states. We explain the\npossible benefits and implementation tricks of this new approach.\nThe relationships between this new approach and some existing\napproaches are also carefully discussed.\n\nCitation: Li Li, Yisheng Lv, Fei-Yue Wang. Traffic signal timing via deep reinforcement learning. IEEE/CAA Journal of Automatica Sinica, 2016, 3(3): 247-254\n\nVideo abstract: YouTube: https://www.youtube.com/watch?v=0tlF35qJ0sE\u0026feature=youtu.be;\nYouku: http://v.youku.com/v_show/id_XMTcxMDcwMzU2NA==.html?beta\u0026","downloadable_attachments":[{"id":49000339,"asset_id":28634266,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":53180586,"first_name":"IEEE/CAA","last_name":"J. Autom. Sinica","domain_name":"independent","page_name":"IEEECAAJAS","display_name":"IEEE/CAA J. Autom. Sinica","profile_url":"https://independent.academia.edu/IEEECAAJAS?f_ri=22247","photo":"https://0.academia-photos.com/53180586/14177798/22465909/s65_ieee_caa.j._autom._sinica.jpg"}],"research_interests":[{"id":1688,"name":"Reinforcement Learning","url":"https://www.academia.edu/Documents/in/Reinforcement_Learning?f_ri=22247","nofollow":false},{"id":22247,"name":"Traffic control","url":"https://www.academia.edu/Documents/in/Traffic_control?f_ri=22247","nofollow":false},{"id":81182,"name":"Deep Learning","url":"https://www.academia.edu/Documents/in/Deep_Learning?f_ri=22247","nofollow":false},{"id":2532663,"name":"Deep Reinforcement Learning","url":"https://www.academia.edu/Documents/in/Deep_Reinforcement_Learning?f_ri=22247","nofollow":false}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_48472806" data-work_id="48472806" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/48472806/Optimizing_Traffic_Control_to_Reduce_Fuel_Consumption_and_Vehicular_Emissions">Optimizing Traffic Control to Reduce Fuel Consumption and Vehicular Emissions</a></div></div><div class="u-pb4x u-mt3x"></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/48472806" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="5869cf28cc2f650f08516b11cc85822e" rel="nofollow" data-download="{"attachment_id":67065872,"asset_id":48472806,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/67065872/download_file?st=MTczMjQyMjgxOCw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="72432611" href="https://independent.academia.edu/AleksandarStevanovic8">Aleksandar Stevanovic</a><script data-card-contents-for-user="72432611" type="text/json">{"id":72432611,"first_name":"Aleksandar","last_name":"Stevanovic","domain_name":"independent","page_name":"AleksandarStevanovic8","display_name":"Aleksandar Stevanovic","profile_url":"https://independent.academia.edu/AleksandarStevanovic8?f_ri=22247","photo":"https://0.academia-photos.com/72432611/70798344/59227275/s65_aleksandar.stevanovic.jpeg"}</script></span></span></li><li class="js-paper-rank-work_48472806 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="48472806"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 48472806, container: ".js-paper-rank-work_48472806", }); 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$(".js-view-count[data-work-id=48472806]").text(description); $(".js-view-count-work_48472806").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_48472806").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="48472806"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">9</a>  </div><span class="InlineList-item-text u-textTruncate u-pl9x"><a class="InlineList-item-text" data-has-card-for-ri="73" href="https://www.academia.edu/Documents/in/Civil_Engineering">Civil Engineering</a>, <script data-card-contents-for-ri="73" type="text/json">{"id":73,"name":"Civil Engineering","url":"https://www.academia.edu/Documents/in/Civil_Engineering?f_ri=22247","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="6177" href="https://www.academia.edu/Documents/in/Modeling">Modeling</a>, <script data-card-contents-for-ri="6177" type="text/json">{"id":6177,"name":"Modeling","url":"https://www.academia.edu/Documents/in/Modeling?f_ri=22247","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="7099" href="https://www.academia.edu/Documents/in/Case_Studies">Case Studies</a>, <script data-card-contents-for-ri="7099" type="text/json">{"id":7099,"name":"Case Studies","url":"https://www.academia.edu/Documents/in/Case_Studies?f_ri=22247","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="20436" href="https://www.academia.edu/Documents/in/Urban_And_Regional_Planning">Urban And Regional Planning</a><script data-card-contents-for-ri="20436" type="text/json">{"id":20436,"name":"Urban And Regional Planning","url":"https://www.academia.edu/Documents/in/Urban_And_Regional_Planning?f_ri=22247","nofollow":false}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=48472806]'), work: {"id":48472806,"title":"Optimizing Traffic Control to Reduce Fuel Consumption and Vehicular Emissions","created_at":"2021-05-04T19:52:02.144-07:00","url":"https://www.academia.edu/48472806/Optimizing_Traffic_Control_to_Reduce_Fuel_Consumption_and_Vehicular_Emissions?f_ri=22247","dom_id":"work_48472806","summary":null,"downloadable_attachments":[{"id":67065872,"asset_id":48472806,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":72432611,"first_name":"Aleksandar","last_name":"Stevanovic","domain_name":"independent","page_name":"AleksandarStevanovic8","display_name":"Aleksandar Stevanovic","profile_url":"https://independent.academia.edu/AleksandarStevanovic8?f_ri=22247","photo":"https://0.academia-photos.com/72432611/70798344/59227275/s65_aleksandar.stevanovic.jpeg"}],"research_interests":[{"id":73,"name":"Civil Engineering","url":"https://www.academia.edu/Documents/in/Civil_Engineering?f_ri=22247","nofollow":false},{"id":6177,"name":"Modeling","url":"https://www.academia.edu/Documents/in/Modeling?f_ri=22247","nofollow":false},{"id":7099,"name":"Case Studies","url":"https://www.academia.edu/Documents/in/Case_Studies?f_ri=22247","nofollow":false},{"id":20436,"name":"Urban And Regional Planning","url":"https://www.academia.edu/Documents/in/Urban_And_Regional_Planning?f_ri=22247","nofollow":false},{"id":22247,"name":"Traffic control","url":"https://www.academia.edu/Documents/in/Traffic_control?f_ri=22247"},{"id":43981,"name":"Optimization","url":"https://www.academia.edu/Documents/in/Optimization?f_ri=22247"},{"id":99915,"name":"Integration","url":"https://www.academia.edu/Documents/in/Integration?f_ri=22247"},{"id":431154,"name":"Fuel Consumption","url":"https://www.academia.edu/Documents/in/Fuel_Consumption?f_ri=22247"},{"id":1208732,"name":"Simulation Model","url":"https://www.academia.edu/Documents/in/Simulation_Model?f_ri=22247"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_9975353" data-work_id="9975353" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/9975353/A_distributed_wireless_sensor_network_system_for_transportation_safety_and_security">A distributed wireless sensor network system for transportation safety and security</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">Given the anticipated increases in highway traffic, the scale and complexity of the traffic infrastructure will continue to grow progressively in time and in distributed geographical areas. To assure transportation efficiency, safety, and... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_9975353" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">Given the anticipated increases in highway traffic, the scale and complexity of the traffic infrastructure will continue to grow progressively in time and in distributed geographical areas. To assure transportation efficiency, safety, and security in the presence of such growth, it is critical to identify an infrastructure development methodology that can adapt to expansions while assuring reliable operation for both centralized monitoring and distributed management. In this paper, a wireless sensor network design methodology is presented, aimed at providing effective distributed surveillance, anomaly detection, and coordinated response. The proposed methodology integrates state-of-the-art traffic sensors, with flexibly programmable controller devices that can integrate with the available traffic control equipments. The system methodology provides a paradigm in which sensors and controllers can be progressively incorporated and programmed to autonomously coordinate with peer sensors and a hierarchy of controllers to detect, notify, and react to anomalous events. Since the system can tolerate failure of parts of the system, as the network connectivity continues to increase, the proposed sensor network will have positive implications on evacuation plans during natural disasters or terrorist attacks. To illustrate the design methodology and usage, a simulated system along a freeway corridor in South Carolina was constructed in an integrated microscopic traffic and wireless sensor network simulation platform, in which distributed incident detection and response functions were implemented. The test results, including detection and false alarm rates and wireless communication latencies, are analyzed to identify insights of the system's operation and potential enhancement strategies.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/9975353" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="890459590698a8441a0647e7a1dc07a5" rel="nofollow" data-download="{"attachment_id":47585123,"asset_id":9975353,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/47585123/download_file?st=MTczMjQyMjgxOCw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="24252794" href="https://gatech.academia.edu/YongchangMa">Yongchang Ma</a><script data-card-contents-for-user="24252794" type="text/json">{"id":24252794,"first_name":"Yongchang","last_name":"Ma","domain_name":"gatech","page_name":"YongchangMa","display_name":"Yongchang Ma","profile_url":"https://gatech.academia.edu/YongchangMa?f_ri=22247","photo":"/images/s65_no_pic.png"}</script></span></span></li><li class="js-paper-rank-work_9975353 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="9975353"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 9975353, container: ".js-paper-rank-work_9975353", }); 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$(".js-view-count[data-work-id=9975353]").text(description); $(".js-view-count-work_9975353").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_9975353").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="9975353"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">11</a>  </div><span class="InlineList-item-text u-textTruncate u-pl10x"><a class="InlineList-item-text" data-has-card-for-ri="22247" href="https://www.academia.edu/Documents/in/Traffic_control">Traffic control</a>, <script data-card-contents-for-ri="22247" type="text/json">{"id":22247,"name":"Traffic control","url":"https://www.academia.edu/Documents/in/Traffic_control?f_ri=22247","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="31349" href="https://www.academia.edu/Documents/in/Anomaly_Detection">Anomaly Detection</a>, <script data-card-contents-for-ri="31349" type="text/json">{"id":31349,"name":"Anomaly Detection","url":"https://www.academia.edu/Documents/in/Anomaly_Detection?f_ri=22247","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="51188" href="https://www.academia.edu/Documents/in/Infrastructure_Development">Infrastructure Development</a>, <script data-card-contents-for-ri="51188" type="text/json">{"id":51188,"name":"Infrastructure Development","url":"https://www.academia.edu/Documents/in/Infrastructure_Development?f_ri=22247","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="91575" href="https://www.academia.edu/Documents/in/South_Carolina">South Carolina</a><script data-card-contents-for-ri="91575" type="text/json">{"id":91575,"name":"South Carolina","url":"https://www.academia.edu/Documents/in/South_Carolina?f_ri=22247","nofollow":false}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=9975353]'), work: {"id":9975353,"title":"A distributed wireless sensor network system for transportation safety and security","created_at":"2015-01-01T22:04:10.629-08:00","url":"https://www.academia.edu/9975353/A_distributed_wireless_sensor_network_system_for_transportation_safety_and_security?f_ri=22247","dom_id":"work_9975353","summary":"Given the anticipated increases in highway traffic, the scale and complexity of the traffic infrastructure will continue to grow progressively in time and in distributed geographical areas. To assure transportation efficiency, safety, and security in the presence of such growth, it is critical to identify an infrastructure development methodology that can adapt to expansions while assuring reliable operation for both centralized monitoring and distributed management. In this paper, a wireless sensor network design methodology is presented, aimed at providing effective distributed surveillance, anomaly detection, and coordinated response. The proposed methodology integrates state-of-the-art traffic sensors, with flexibly programmable controller devices that can integrate with the available traffic control equipments. The system methodology provides a paradigm in which sensors and controllers can be progressively incorporated and programmed to autonomously coordinate with peer sensors and a hierarchy of controllers to detect, notify, and react to anomalous events. Since the system can tolerate failure of parts of the system, as the network connectivity continues to increase, the proposed sensor network will have positive implications on evacuation plans during natural disasters or terrorist attacks. To illustrate the design methodology and usage, a simulated system along a freeway corridor in South Carolina was constructed in an integrated microscopic traffic and wireless sensor network simulation platform, in which distributed incident detection and response functions were implemented. The test results, including detection and false alarm rates and wireless communication latencies, are analyzed to identify insights of the system's operation and potential enhancement strategies.","downloadable_attachments":[{"id":47585123,"asset_id":9975353,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":24252794,"first_name":"Yongchang","last_name":"Ma","domain_name":"gatech","page_name":"YongchangMa","display_name":"Yongchang Ma","profile_url":"https://gatech.academia.edu/YongchangMa?f_ri=22247","photo":"/images/s65_no_pic.png"}],"research_interests":[{"id":22247,"name":"Traffic control","url":"https://www.academia.edu/Documents/in/Traffic_control?f_ri=22247","nofollow":false},{"id":31349,"name":"Anomaly Detection","url":"https://www.academia.edu/Documents/in/Anomaly_Detection?f_ri=22247","nofollow":false},{"id":51188,"name":"Infrastructure Development","url":"https://www.academia.edu/Documents/in/Infrastructure_Development?f_ri=22247","nofollow":false},{"id":91575,"name":"South Carolina","url":"https://www.academia.edu/Documents/in/South_Carolina?f_ri=22247","nofollow":false},{"id":158569,"name":"Sensor Network","url":"https://www.academia.edu/Documents/in/Sensor_Network?f_ri=22247"},{"id":158722,"name":"Natural disaster","url":"https://www.academia.edu/Documents/in/Natural_disaster?f_ri=22247"},{"id":159687,"name":"Design Methodology","url":"https://www.academia.edu/Documents/in/Design_Methodology?f_ri=22247"},{"id":960802,"name":"Distributed and Parallel Management of Data","url":"https://www.academia.edu/Documents/in/Distributed_and_Parallel_Management_of_Data?f_ri=22247"},{"id":978498,"name":"Network Connectivity","url":"https://www.academia.edu/Documents/in/Network_Connectivity?f_ri=22247"},{"id":1211847,"name":"Wireless Sensor Network","url":"https://www.academia.edu/Documents/in/Wireless_Sensor_Network?f_ri=22247"},{"id":1232975,"name":"Wireless Communication","url":"https://www.academia.edu/Documents/in/Wireless_Communication-1?f_ri=22247"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_35566657" data-work_id="35566657" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/35566657/Survey_on_Accident_Detection_System_and_Alert">Survey on Accident Detection System and Alert</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">— In extremely inhabited countries like Asian country, every 3.7 minutes a death swoops in. a number one explanation for the world burden of public health and fatalities is road accidents. The loss of human life attributable to accident... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_35566657" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">— In extremely inhabited countries like Asian country, every 3.7 minutes a death swoops in. a number one explanation for the world burden of public health and fatalities is road accidents. The loss of human life attributable to accident is to be avoided. Traffic jam and current are major facts that cause delay to car, as most of the countries follow planned sequence of traffic lights. Typically the accidents also are not detected in time that conjointly in several cases results in loss of life. The thought here is to produce an intelligent stoplight System, which might facilitate the car reach the destination in minimum doable time by providing an adequate route of passage. In conjunction with this a controller is to be work on vehicles, which might facilitate in totally automatic detection of the prevalence of accident and find the vehicle similarly.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/35566657" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="84fe03fade6fb24463855428d214462a" rel="nofollow" data-download="{"attachment_id":55432738,"asset_id":35566657,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/55432738/download_file?st=MTczMjQyMjgxOCw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="8163309" href="https://independent.academia.edu/IJSRD">IJSRD - International Journal for Scientific Research and Development</a><script data-card-contents-for-user="8163309" type="text/json">{"id":8163309,"first_name":"IJSRD","last_name":"International Journal for Scientific Research and Development","domain_name":"independent","page_name":"IJSRD","display_name":"IJSRD - International Journal for Scientific Research and Development","profile_url":"https://independent.academia.edu/IJSRD?f_ri=22247","photo":"https://0.academia-photos.com/8163309/3008173/12091840/s65_ijsrd.international_journal_for_scientific_research_and_development.jpg"}</script></span></span></li><li class="js-paper-rank-work_35566657 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="35566657"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 35566657, container: ".js-paper-rank-work_35566657", }); });</script></li><li class="js-percentile-work_35566657 InlineList-item InlineList-item--bordered hidden u-tcGrayDark"><span class="percentile-widget hidden"><span class="u-mr2x percentile-widget" style="display: none">•</span><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 35566657; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-percentile-work_35566657"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></li><li class="js-view-count-work_35566657 InlineList-item InlineList-item--bordered hidden"><div><span><span class="js-view-count view-count u-mr2x" data-work-id="35566657"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 35566657; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=35566657]").text(description); $(".js-view-count-work_35566657").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_35566657").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="35566657"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">5</a>  </div><span class="InlineList-item-text u-textTruncate u-pl9x"><a class="InlineList-item-text" data-has-card-for-ri="8216" href="https://www.academia.edu/Documents/in/Congestion_Control">Congestion Control</a>, <script data-card-contents-for-ri="8216" type="text/json">{"id":8216,"name":"Congestion Control","url":"https://www.academia.edu/Documents/in/Congestion_Control?f_ri=22247","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="9589" href="https://www.academia.edu/Documents/in/Intelligent_Transportation_Systems">Intelligent Transportation Systems</a>, <script data-card-contents-for-ri="9589" type="text/json">{"id":9589,"name":"Intelligent Transportation Systems","url":"https://www.academia.edu/Documents/in/Intelligent_Transportation_Systems?f_ri=22247","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="22247" href="https://www.academia.edu/Documents/in/Traffic_control">Traffic control</a>, <script data-card-contents-for-ri="22247" type="text/json">{"id":22247,"name":"Traffic control","url":"https://www.academia.edu/Documents/in/Traffic_control?f_ri=22247","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="55293" href="https://www.academia.edu/Documents/in/Air_traffic_control">Air traffic control</a><script data-card-contents-for-ri="55293" type="text/json">{"id":55293,"name":"Air traffic control","url":"https://www.academia.edu/Documents/in/Air_traffic_control?f_ri=22247","nofollow":false}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=35566657]'), work: {"id":35566657,"title":"Survey on Accident Detection System and Alert","created_at":"2018-01-03T04:21:13.300-08:00","url":"https://www.academia.edu/35566657/Survey_on_Accident_Detection_System_and_Alert?f_ri=22247","dom_id":"work_35566657","summary":"— In extremely inhabited countries like Asian country, every 3.7 minutes a death swoops in. a number one explanation for the world burden of public health and fatalities is road accidents. The loss of human life attributable to accident is to be avoided. Traffic jam and current are major facts that cause delay to car, as most of the countries follow planned sequence of traffic lights. Typically the accidents also are not detected in time that conjointly in several cases results in loss of life. The thought here is to produce an intelligent stoplight System, which might facilitate the car reach the destination in minimum doable time by providing an adequate route of passage. In conjunction with this a controller is to be work on vehicles, which might facilitate in totally automatic detection of the prevalence of accident and find the vehicle similarly.","downloadable_attachments":[{"id":55432738,"asset_id":35566657,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":8163309,"first_name":"IJSRD","last_name":"International Journal for Scientific Research and Development","domain_name":"independent","page_name":"IJSRD","display_name":"IJSRD - International Journal for Scientific Research and Development","profile_url":"https://independent.academia.edu/IJSRD?f_ri=22247","photo":"https://0.academia-photos.com/8163309/3008173/12091840/s65_ijsrd.international_journal_for_scientific_research_and_development.jpg"}],"research_interests":[{"id":8216,"name":"Congestion Control","url":"https://www.academia.edu/Documents/in/Congestion_Control?f_ri=22247","nofollow":false},{"id":9589,"name":"Intelligent Transportation Systems","url":"https://www.academia.edu/Documents/in/Intelligent_Transportation_Systems?f_ri=22247","nofollow":false},{"id":22247,"name":"Traffic control","url":"https://www.academia.edu/Documents/in/Traffic_control?f_ri=22247","nofollow":false},{"id":55293,"name":"Air traffic control","url":"https://www.academia.edu/Documents/in/Air_traffic_control?f_ri=22247","nofollow":false},{"id":82598,"name":"Accidents","url":"https://www.academia.edu/Documents/in/Accidents?f_ri=22247"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_19777472" data-work_id="19777472" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/19777472/A_REVIEW_OF_COMPUTER_VISION_SYSTEM_FOR_THE_VEHICLE_IDENTIFICATION_AND_CLASSIFICATION_FROM_ONLINE_AND_OFFLINE_VIDEOS">A REVIEW OF COMPUTER VISION SYSTEM FOR THE VEHICLE IDENTIFICATION AND CLASSIFICATION FROM ONLINE AND OFFLINE VIDEOS</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">The traffic on the roads is increasing day by day. There is dire need of developing an automation system that can effectively manage and control the traffic on roads. The traffic data of multiple vehicle types on roads is also important... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_19777472" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">The traffic on the roads is increasing day by day. There is dire need of developing an automation system that can effectively manage and control the traffic on roads. The traffic data of multiple vehicle types on roads is also important for taking various decisions related to traffic. A video based traffic data collection system for multiple vehicle types is helpful for monitoring vehicles under homogenous and heterogeneous traffic conditions. In this paper, we have studied different methods for the identification, classification and counting vehicles from online and offline videos in India as well as other countries. The paper also discusses the various applications of video based automatic traffic control system. The various challenges faced by the researchers for developing such systems are also discussed.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/19777472" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="ba6dc8e67b0ca7e45b7260047e97ec91" rel="nofollow" data-download="{"attachment_id":40839417,"asset_id":19777472,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/40839417/download_file?st=MTczMjQyMjgxOCw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="16710091" href="https://independent.academia.edu/SIPIJJOURNAL">Signal & Image Processing : An International Journal (SIPIJ) - WJCI Indexed</a><script data-card-contents-for-user="16710091" type="text/json">{"id":16710091,"first_name":"Signal \u0026 Image Processing : An International Journal","last_name":"(SIPIJ) - WJCI Indexed","domain_name":"independent","page_name":"SIPIJJOURNAL","display_name":"Signal \u0026 Image Processing : An International Journal (SIPIJ) - WJCI Indexed","profile_url":"https://independent.academia.edu/SIPIJJOURNAL?f_ri=22247","photo":"https://0.academia-photos.com/16710091/4565741/114312448/s65_signal_image_processing_an_international_journal._sipij_-_wjci_indexed.jpg"}</script></span></span></li><li class="js-paper-rank-work_19777472 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="19777472"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 19777472, container: ".js-paper-rank-work_19777472", }); });</script></li><li class="js-percentile-work_19777472 InlineList-item InlineList-item--bordered hidden u-tcGrayDark"><span class="percentile-widget hidden"><span class="u-mr2x percentile-widget" style="display: none">•</span><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 19777472; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-percentile-work_19777472"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></li><li class="js-view-count-work_19777472 InlineList-item InlineList-item--bordered hidden"><div><span><span class="js-view-count view-count u-mr2x" data-work-id="19777472"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 19777472; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=19777472]").text(description); $(".js-view-count-work_19777472").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_19777472").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="19777472"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">4</a>  </div><span class="InlineList-item-text u-textTruncate u-pl9x"><a class="InlineList-item-text" data-has-card-for-ri="22247" href="https://www.academia.edu/Documents/in/Traffic_control">Traffic control</a>, <script data-card-contents-for-ri="22247" type="text/json">{"id":22247,"name":"Traffic control","url":"https://www.academia.edu/Documents/in/Traffic_control?f_ri=22247","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="164861" href="https://www.academia.edu/Documents/in/Vehicle_counting">Vehicle counting</a>, <script data-card-contents-for-ri="164861" type="text/json">{"id":164861,"name":"Vehicle counting","url":"https://www.academia.edu/Documents/in/Vehicle_counting?f_ri=22247","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="742635" href="https://www.academia.edu/Documents/in/Vehicle_Classification">Vehicle Classification</a>, <script data-card-contents-for-ri="742635" type="text/json">{"id":742635,"name":"Vehicle Classification","url":"https://www.academia.edu/Documents/in/Vehicle_Classification?f_ri=22247","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="1316698" href="https://www.academia.edu/Documents/in/Vehicle_Identification">Vehicle Identification</a><script data-card-contents-for-ri="1316698" type="text/json">{"id":1316698,"name":"Vehicle Identification","url":"https://www.academia.edu/Documents/in/Vehicle_Identification?f_ri=22247","nofollow":false}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=19777472]'), work: {"id":19777472,"title":"A REVIEW OF COMPUTER VISION SYSTEM FOR THE VEHICLE IDENTIFICATION AND CLASSIFICATION FROM ONLINE AND OFFLINE VIDEOS","created_at":"2015-12-21T22:06:30.682-08:00","url":"https://www.academia.edu/19777472/A_REVIEW_OF_COMPUTER_VISION_SYSTEM_FOR_THE_VEHICLE_IDENTIFICATION_AND_CLASSIFICATION_FROM_ONLINE_AND_OFFLINE_VIDEOS?f_ri=22247","dom_id":"work_19777472","summary":"The traffic on the roads is increasing day by day. There is dire need of developing an automation system that can effectively manage and control the traffic on roads. The traffic data of multiple vehicle types on roads is also important for taking various decisions related to traffic. A video based traffic data collection system for multiple vehicle types is helpful for monitoring vehicles under homogenous and heterogeneous traffic conditions. In this paper, we have studied different methods for the identification, classification and counting vehicles from online and offline videos in India as well as other countries. The paper also discusses the various applications of video based automatic traffic control system. The various challenges faced by the researchers for developing such systems are also discussed. ","downloadable_attachments":[{"id":40839417,"asset_id":19777472,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":16710091,"first_name":"Signal \u0026 Image Processing : An International Journal","last_name":"(SIPIJ) - WJCI Indexed","domain_name":"independent","page_name":"SIPIJJOURNAL","display_name":"Signal \u0026 Image Processing : An International Journal (SIPIJ) - WJCI Indexed","profile_url":"https://independent.academia.edu/SIPIJJOURNAL?f_ri=22247","photo":"https://0.academia-photos.com/16710091/4565741/114312448/s65_signal_image_processing_an_international_journal._sipij_-_wjci_indexed.jpg"}],"research_interests":[{"id":22247,"name":"Traffic control","url":"https://www.academia.edu/Documents/in/Traffic_control?f_ri=22247","nofollow":false},{"id":164861,"name":"Vehicle counting","url":"https://www.academia.edu/Documents/in/Vehicle_counting?f_ri=22247","nofollow":false},{"id":742635,"name":"Vehicle Classification","url":"https://www.academia.edu/Documents/in/Vehicle_Classification?f_ri=22247","nofollow":false},{"id":1316698,"name":"Vehicle Identification","url":"https://www.academia.edu/Documents/in/Vehicle_Identification?f_ri=22247","nofollow":false}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_6466776" data-work_id="6466776" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/6466776/Modelling_and_Optimisation_of_a_Traffic_Intersection_Based_on_Queue_Theory_and_Markov_Decision_Control_Methods">Modelling and Optimisation of a Traffic Intersection Based on Queue Theory and Markov Decision Control Methods</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">Traffic models play an important role in both today's traffic research and in many traffic applications such as traffic flow prediction, incident detection and traffic control. Modelling traffic dynamics and optimising the control signal... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_6466776" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">Traffic models play an important role in both today's traffic research and in many traffic applications such as traffic flow prediction, incident detection and traffic control. Modelling traffic dynamics and optimising the control signal are two interrelated problems. Modelling provides fundamental understanding of traffic dynamics and behaviour. In this paper, traffic signal is modelled as a M/M/l queueing theory. The validation of a simulation model (M/M/l queue) with different arrival rates is presented. From the result, a traffic light model was developed by applying M/M/l queue theory for single intersection. In the optimisation strategy, the Markov decision control is applied to minimize queue length and waiting time. Simulation results show the excellent potential of this approach</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/6466776" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="ac13dd1cd4767dd67872a1a8532134aa" rel="nofollow" data-download="{"attachment_id":33255607,"asset_id":6466776,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/33255607/download_file?st=MTczMjQyMjgxOCw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="10246969" href="https://independent.academia.edu/azurachesoh">azura che soh</a><script data-card-contents-for-user="10246969" type="text/json">{"id":10246969,"first_name":"azura","last_name":"che soh","domain_name":"independent","page_name":"azurachesoh","display_name":"azura che soh","profile_url":"https://independent.academia.edu/azurachesoh?f_ri=22247","photo":"/images/s65_no_pic.png"}</script></span></span></li><li class="js-paper-rank-work_6466776 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="6466776"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 6466776, container: ".js-paper-rank-work_6466776", }); 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$(".js-view-count[data-work-id=6466776]").text(description); $(".js-view-count-work_6466776").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_6466776").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="6466776"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">12</a>  </div><span class="InlineList-item-text u-textTruncate u-pl10x"><a class="InlineList-item-text" data-has-card-for-ri="8050" href="https://www.academia.edu/Documents/in/Vehicle_Dynamics">Vehicle Dynamics</a>, <script data-card-contents-for-ri="8050" type="text/json">{"id":8050,"name":"Vehicle Dynamics","url":"https://www.academia.edu/Documents/in/Vehicle_Dynamics?f_ri=22247","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="8422" href="https://www.academia.edu/Documents/in/Adaptive_Control">Adaptive Control</a>, <script data-card-contents-for-ri="8422" type="text/json">{"id":8422,"name":"Adaptive Control","url":"https://www.academia.edu/Documents/in/Adaptive_Control?f_ri=22247","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="10817" href="https://www.academia.edu/Documents/in/Markov_Processes">Markov Processes</a>, <script data-card-contents-for-ri="10817" type="text/json">{"id":10817,"name":"Markov Processes","url":"https://www.academia.edu/Documents/in/Markov_Processes?f_ri=22247","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="10918" href="https://www.academia.edu/Documents/in/Queueing_theory">Queueing theory</a><script data-card-contents-for-ri="10918" type="text/json">{"id":10918,"name":"Queueing theory","url":"https://www.academia.edu/Documents/in/Queueing_theory?f_ri=22247","nofollow":false}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=6466776]'), work: {"id":6466776,"title":"Modelling and Optimisation of a Traffic Intersection Based on Queue Theory and Markov Decision Control Methods","created_at":"2014-03-18T21:02:11.546-07:00","url":"https://www.academia.edu/6466776/Modelling_and_Optimisation_of_a_Traffic_Intersection_Based_on_Queue_Theory_and_Markov_Decision_Control_Methods?f_ri=22247","dom_id":"work_6466776","summary":"Traffic models play an important role in both today's traffic research and in many traffic applications such as traffic flow prediction, incident detection and traffic control. Modelling traffic dynamics and optimising the control signal are two interrelated problems. Modelling provides fundamental understanding of traffic dynamics and behaviour. In this paper, traffic signal is modelled as a M/M/l queueing theory. The validation of a simulation model (M/M/l queue) with different arrival rates is presented. From the result, a traffic light model was developed by applying M/M/l queue theory for single intersection. In the optimisation strategy, the Markov decision control is applied to minimize queue length and waiting time. Simulation results show the excellent potential of this approach","downloadable_attachments":[{"id":33255607,"asset_id":6466776,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":10246969,"first_name":"azura","last_name":"che soh","domain_name":"independent","page_name":"azurachesoh","display_name":"azura che soh","profile_url":"https://independent.academia.edu/azurachesoh?f_ri=22247","photo":"/images/s65_no_pic.png"}],"research_interests":[{"id":8050,"name":"Vehicle Dynamics","url":"https://www.academia.edu/Documents/in/Vehicle_Dynamics?f_ri=22247","nofollow":false},{"id":8422,"name":"Adaptive Control","url":"https://www.academia.edu/Documents/in/Adaptive_Control?f_ri=22247","nofollow":false},{"id":10817,"name":"Markov Processes","url":"https://www.academia.edu/Documents/in/Markov_Processes?f_ri=22247","nofollow":false},{"id":10918,"name":"Queueing theory","url":"https://www.academia.edu/Documents/in/Queueing_theory?f_ri=22247","nofollow":false},{"id":22247,"name":"Traffic control","url":"https://www.academia.edu/Documents/in/Traffic_control?f_ri=22247"},{"id":25660,"name":"Decision Theory","url":"https://www.academia.edu/Documents/in/Decision_Theory?f_ri=22247"},{"id":204472,"name":"Predictive models","url":"https://www.academia.edu/Documents/in/Predictive_models?f_ri=22247"},{"id":220371,"name":"Traffic Flow","url":"https://www.academia.edu/Documents/in/Traffic_Flow?f_ri=22247"},{"id":290548,"name":"Simulation modelling","url":"https://www.academia.edu/Documents/in/Simulation_modelling?f_ri=22247"},{"id":1158716,"name":"Waiting Time","url":"https://www.academia.edu/Documents/in/Waiting_Time?f_ri=22247"},{"id":1208732,"name":"Simulation Model","url":"https://www.academia.edu/Documents/in/Simulation_Model?f_ri=22247"},{"id":1682786,"name":"Control Method","url":"https://www.academia.edu/Documents/in/Control_Method?f_ri=22247"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_19519878" data-work_id="19519878" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/19519878/Adaptive_Traffic_Control_System_based_on_Bayesian_Probability_Interpretation">Adaptive Traffic Control System based on Bayesian Probability Interpretation</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">Traffic control (TC) is a challenging problem in today’s modern society. This is due to several factors including the huge number of vehicles, the high dynamics of the system, and the nonlinear behavior exhibited by the different... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_19519878" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">Traffic control (TC) is a challenging problem in today’s modern society. This is due to several factors including the huge number of vehicles, the high dynamics of the system, and the nonlinear behavior exhibited by the different components of the system. Poor traffic management inflicts considerable cost due to the high rate of accidents, time losses, and negative impact on the economy as well as the environment. In this paper, we develop a traffic control system based on the Bayesian interpretation of probability that is adaptive to the high dynamics and non-stationarity of the road network. In order to simulate the traffic non-stationarity, we extend the Green Light District (GLD) vehicle traffic simulator. The change in road conditions is modeled by varying vehicle spawning probability distributions. We also implement the acceleration and lane changing models in GLD based on the Intelligent Driver Model (IDM).<br />Index Terms—reinforcement learning, traffic control, traffic simulation, multi agent systems, driver behavior</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/19519878" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="15b90eb26e7d3b1a79c4a9a22a74253a" rel="nofollow" data-download="{"attachment_id":40666411,"asset_id":19519878,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/40666411/download_file?st=MTczMjQyMjgxOCw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="37877592" href="https://ejust.academia.edu/walid_gomaa">Walid Gomaa</a><script data-card-contents-for-user="37877592" type="text/json">{"id":37877592,"first_name":"Walid","last_name":"Gomaa","domain_name":"ejust","page_name":"walid_gomaa","display_name":"Walid Gomaa","profile_url":"https://ejust.academia.edu/walid_gomaa?f_ri=22247","photo":"https://0.academia-photos.com/37877592/10632393/11942071/s65_walid.gomaa.png"}</script></span></span></li><li class="js-paper-rank-work_19519878 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="19519878"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 19519878, container: ".js-paper-rank-work_19519878", }); 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$(".js-view-count[data-work-id=19519878]").text(description); $(".js-view-count-work_19519878").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_19519878").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="19519878"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">15</a>  </div><span class="InlineList-item-text u-textTruncate u-pl10x"><a class="InlineList-item-text" data-has-card-for-ri="1688" href="https://www.academia.edu/Documents/in/Reinforcement_Learning">Reinforcement Learning</a>, <script data-card-contents-for-ri="1688" type="text/json">{"id":1688,"name":"Reinforcement Learning","url":"https://www.academia.edu/Documents/in/Reinforcement_Learning?f_ri=22247","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="2008" href="https://www.academia.edu/Documents/in/Machine_Learning">Machine Learning</a>, <script data-card-contents-for-ri="2008" type="text/json">{"id":2008,"name":"Machine Learning","url":"https://www.academia.edu/Documents/in/Machine_Learning?f_ri=22247","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="2534" href="https://www.academia.edu/Documents/in/Multiagent_Systems">Multiagent Systems</a>, <script data-card-contents-for-ri="2534" type="text/json">{"id":2534,"name":"Multiagent Systems","url":"https://www.academia.edu/Documents/in/Multiagent_Systems?f_ri=22247","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="3252" href="https://www.academia.edu/Documents/in/Traffic_Simulation">Traffic Simulation</a><script data-card-contents-for-ri="3252" type="text/json">{"id":3252,"name":"Traffic Simulation","url":"https://www.academia.edu/Documents/in/Traffic_Simulation?f_ri=22247","nofollow":false}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=19519878]'), work: {"id":19519878,"title":"Adaptive Traffic Control System based on Bayesian Probability Interpretation","created_at":"2015-12-06T06:11:35.678-08:00","url":"https://www.academia.edu/19519878/Adaptive_Traffic_Control_System_based_on_Bayesian_Probability_Interpretation?f_ri=22247","dom_id":"work_19519878","summary":"Traffic control (TC) is a challenging problem in today’s modern society. This is due to several factors including the huge number of vehicles, the high dynamics of the system, and the nonlinear behavior exhibited by the different components of the system. Poor traffic management inflicts considerable cost due to the high rate of accidents, time losses, and negative impact on the economy as well as the environment. In this paper, we develop a traffic control system based on the Bayesian interpretation of probability that is adaptive to the high dynamics and non-stationarity of the road network. In order to simulate the traffic non-stationarity, we extend the Green Light District (GLD) vehicle traffic simulator. The change in road conditions is modeled by varying vehicle spawning probability distributions. We also implement the acceleration and lane changing models in GLD based on the Intelligent Driver Model (IDM).\nIndex Terms—reinforcement learning, traffic control, traffic simulation, multi agent systems, driver behavior","downloadable_attachments":[{"id":40666411,"asset_id":19519878,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":37877592,"first_name":"Walid","last_name":"Gomaa","domain_name":"ejust","page_name":"walid_gomaa","display_name":"Walid Gomaa","profile_url":"https://ejust.academia.edu/walid_gomaa?f_ri=22247","photo":"https://0.academia-photos.com/37877592/10632393/11942071/s65_walid.gomaa.png"}],"research_interests":[{"id":1688,"name":"Reinforcement Learning","url":"https://www.academia.edu/Documents/in/Reinforcement_Learning?f_ri=22247","nofollow":false},{"id":2008,"name":"Machine Learning","url":"https://www.academia.edu/Documents/in/Machine_Learning?f_ri=22247","nofollow":false},{"id":2534,"name":"Multiagent Systems","url":"https://www.academia.edu/Documents/in/Multiagent_Systems?f_ri=22247","nofollow":false},{"id":3252,"name":"Traffic Simulation","url":"https://www.academia.edu/Documents/in/Traffic_Simulation?f_ri=22247","nofollow":false},{"id":15084,"name":"Statistical machine learning","url":"https://www.academia.edu/Documents/in/Statistical_machine_learning?f_ri=22247"},{"id":22247,"name":"Traffic control","url":"https://www.academia.edu/Documents/in/Traffic_control?f_ri=22247"},{"id":26813,"name":"MultiAgent Systems (Computer Science)","url":"https://www.academia.edu/Documents/in/MultiAgent_Systems_Computer_Science_?f_ri=22247"},{"id":27224,"name":"Multiagent Systems (Intelligence)","url":"https://www.academia.edu/Documents/in/Multiagent_Systems_Intelligence_?f_ri=22247"},{"id":28846,"name":"Bayesian Probabilistic Analysis","url":"https://www.academia.edu/Documents/in/Bayesian_Probabilistic_Analysis?f_ri=22247"},{"id":103411,"name":"Traffic management and control","url":"https://www.academia.edu/Documents/in/Traffic_management_and_control?f_ri=22247"},{"id":193953,"name":"Driver Behavior","url":"https://www.academia.edu/Documents/in/Driver_Behavior?f_ri=22247"},{"id":280565,"name":"Traffic Signal Control","url":"https://www.academia.edu/Documents/in/Traffic_Signal_Control?f_ri=22247"},{"id":357007,"name":"Machine Learning, Reinforcement Learning","url":"https://www.academia.edu/Documents/in/Machine_Learning_Reinforcement_Learning?f_ri=22247"},{"id":1032783,"name":"Bayesian Probability","url":"https://www.academia.edu/Documents/in/Bayesian_Probability?f_ri=22247"},{"id":2215017,"name":"Bayesian probability interpretation","url":"https://www.academia.edu/Documents/in/Bayesian_probability_interpretation?f_ri=22247"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_4227333" data-work_id="4227333" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/4227333/Modelling_Control_and_Perception_for_an_Autonomous_Robotic_Airship">Modelling, Control and Perception for an Autonomous Robotic Airship</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">Robotic unmanned aerial vehicles have an enormous potential as observation and data-gathering platforms for a wide variety of applications. These applications include environmental and biodiversity research and monitoring, urban planning... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_4227333" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">Robotic unmanned aerial vehicles have an enormous potential as observation and data-gathering platforms for a wide variety of applications. These applications include environmental and biodiversity research and monitoring, urban planning and traffic control, inspection of man-made structures, mineral and archaeological prospecting, surveillance and law enforcement, communications, and many others. Robotic airships, in particular, are of great interest as observation platforms, due to their potential for extended mission times, low platform vibration characteristics, and hovering capability. In this paper we provide an overview of Project AURORA (Autonomous Unmanned Remote Monitoring Robotic Airship), a research effort that focusses on the development of the technologies required for substantially autonomous robotic airships. We discuss airship modelling and control, autonomous navigation, and sensor-based flight control. We also present the hardware and software architectures developed for the airship. Additionally, we discuss our current research in airborne perception and monitoring, including mission-specific target acquisition, discrimination and identification tasks. The paper also presents experimental results from our work.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/4227333" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="1c1ebbbe466f2f50b0931cf77954ad35" rel="nofollow" data-download="{"attachment_id":49979032,"asset_id":4227333,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/49979032/download_file?st=MTczMjQyMjgxOCw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="5118405" href="https://independent.academia.edu/RamosJosue">Josue Ramos</a><script data-card-contents-for-user="5118405" type="text/json">{"id":5118405,"first_name":"Josue","last_name":"Ramos","domain_name":"independent","page_name":"RamosJosue","display_name":"Josue Ramos","profile_url":"https://independent.academia.edu/RamosJosue?f_ri=22247","photo":"/images/s65_no_pic.png"}</script></span></span></li><li class="js-paper-rank-work_4227333 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="4227333"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 4227333, container: ".js-paper-rank-work_4227333", }); 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$(".js-view-count[data-work-id=4227333]").text(description); $(".js-view-count-work_4227333").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_4227333").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="4227333"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">10</a>  </div><span class="InlineList-item-text u-textTruncate u-pl10x"><a class="InlineList-item-text" data-has-card-for-ri="4808" href="https://www.academia.edu/Documents/in/Urban_Planning">Urban Planning</a>, <script data-card-contents-for-ri="4808" type="text/json">{"id":4808,"name":"Urban Planning","url":"https://www.academia.edu/Documents/in/Urban_Planning?f_ri=22247","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="9270" href="https://www.academia.edu/Documents/in/Software_Architecture">Software Architecture</a>, <script data-card-contents-for-ri="9270" type="text/json">{"id":9270,"name":"Software Architecture","url":"https://www.academia.edu/Documents/in/Software_Architecture?f_ri=22247","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="22247" href="https://www.academia.edu/Documents/in/Traffic_control">Traffic control</a>, <script data-card-contents-for-ri="22247" type="text/json">{"id":22247,"name":"Traffic control","url":"https://www.academia.edu/Documents/in/Traffic_control?f_ri=22247","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="37778" href="https://www.academia.edu/Documents/in/Law_Enforcement">Law Enforcement</a><script data-card-contents-for-ri="37778" type="text/json">{"id":37778,"name":"Law Enforcement","url":"https://www.academia.edu/Documents/in/Law_Enforcement?f_ri=22247","nofollow":false}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=4227333]'), work: {"id":4227333,"title":"Modelling, Control and Perception for an Autonomous Robotic Airship","created_at":"2013-08-12T19:53:27.949-07:00","url":"https://www.academia.edu/4227333/Modelling_Control_and_Perception_for_an_Autonomous_Robotic_Airship?f_ri=22247","dom_id":"work_4227333","summary":"Robotic unmanned aerial vehicles have an enormous potential as observation and data-gathering platforms for a wide variety of applications. These applications include environmental and biodiversity research and monitoring, urban planning and traffic control, inspection of man-made structures, mineral and archaeological prospecting, surveillance and law enforcement, communications, and many others. Robotic airships, in particular, are of great interest as observation platforms, due to their potential for extended mission times, low platform vibration characteristics, and hovering capability. In this paper we provide an overview of Project AURORA (Autonomous Unmanned Remote Monitoring Robotic Airship), a research effort that focusses on the development of the technologies required for substantially autonomous robotic airships. We discuss airship modelling and control, autonomous navigation, and sensor-based flight control. We also present the hardware and software architectures developed for the airship. Additionally, we discuss our current research in airborne perception and monitoring, including mission-specific target acquisition, discrimination and identification tasks. The paper also presents experimental results from our work.","downloadable_attachments":[{"id":49979032,"asset_id":4227333,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":5118405,"first_name":"Josue","last_name":"Ramos","domain_name":"independent","page_name":"RamosJosue","display_name":"Josue Ramos","profile_url":"https://independent.academia.edu/RamosJosue?f_ri=22247","photo":"/images/s65_no_pic.png"}],"research_interests":[{"id":4808,"name":"Urban Planning","url":"https://www.academia.edu/Documents/in/Urban_Planning?f_ri=22247","nofollow":false},{"id":9270,"name":"Software Architecture","url":"https://www.academia.edu/Documents/in/Software_Architecture?f_ri=22247","nofollow":false},{"id":22247,"name":"Traffic control","url":"https://www.academia.edu/Documents/in/Traffic_control?f_ri=22247","nofollow":false},{"id":37778,"name":"Law Enforcement","url":"https://www.academia.edu/Documents/in/Law_Enforcement?f_ri=22247","nofollow":false},{"id":115002,"name":"Autonomous navigation","url":"https://www.academia.edu/Documents/in/Autonomous_navigation?f_ri=22247"},{"id":277273,"name":"Flight Control","url":"https://www.academia.edu/Documents/in/Flight_Control?f_ri=22247"},{"id":491368,"name":"Remote Monitoring","url":"https://www.academia.edu/Documents/in/Remote_Monitoring?f_ri=22247"},{"id":705780,"name":"MEMS Based Gas Sensor","url":"https://www.academia.edu/Documents/in/MEMS_Based_Gas_Sensor?f_ri=22247"},{"id":1303555,"name":"Unmanned Aerial Vehicle","url":"https://www.academia.edu/Documents/in/Unmanned_Aerial_Vehicle?f_ri=22247"},{"id":2108071,"name":"Data Gathering","url":"https://www.academia.edu/Documents/in/Data_Gathering?f_ri=22247"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_28267163" data-work_id="28267163" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/28267163/A_survey_on_service_oriented_middleware_for_wireless_sensor_networks">A survey on service-oriented middleware for wireless sensor networks</a></div></div><div class="u-pb4x u-mt3x"></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/28267163" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="8344dc536d26e32977c0b0c7d1aec6c4" rel="nofollow" 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class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/23739314/A_new_method_to_calculate_emissions_with_simulated_traffic_conditions">A new method to calculate emissions with simulated traffic conditions</a></div></div><div class="u-pb4x u-mt3x"></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/23739314" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="6cb58e824d62538127d98b141f7b8ce7" rel="nofollow" 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class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/24815444/The_Cell_Transmission_Model_Part_I_A_Simple_Dynamic_Representation_Of_Highway_Traffic">The Cell Transmission Model. Part I: A Simple Dynamic Representation Of Highway Traffic</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">This paper presents a simple representation of traffic on a highway with a single entrance and exit. The representation can be used to predict traffic&#x27;s evolution over time and space, including transient phenomena such as the... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_24815444" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">This paper presents a simple representation of traffic on a highway with a single entrance and exit. The representation can be used to predict traffic&#x27;s evolution over time and space, including transient phenomena such as the building, propagation and dissipation of queues. The easy-to-solve difference equations used to predict traffic&#x27;s evolution are shown to be the discrete analog of the differential equations arising from a special case of the hydrodynamic model of traffic flow. The proposed method automatically generates appropriate changes in density at locations where the hydrodynamic theory would call for a shockwave; i.e. a jump in density such as those typically seen at the end of every queue. The complex side calculations required by classical methods to keep track of shockwaves are thus eliminated. The paper also shows how the equations can mimic the real-life development of stop-and-go traffic within moving queues. The model predicts that the oscillation patter...</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/24815444" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="324caf9071c6035f26ba9bc957862d3a" rel="nofollow" data-download="{"attachment_id":45141828,"asset_id":24815444,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/45141828/download_file?st=MTczMjQyMjgxOSw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="47722141" href="https://berkeley.academia.edu/CarlosDaganzo">Carlos Daganzo</a><script data-card-contents-for-user="47722141" type="text/json">{"id":47722141,"first_name":"Carlos","last_name":"Daganzo","domain_name":"berkeley","page_name":"CarlosDaganzo","display_name":"Carlos Daganzo","profile_url":"https://berkeley.academia.edu/CarlosDaganzo?f_ri=22247","photo":"/images/s65_no_pic.png"}</script></span></span></li><li class="js-paper-rank-work_24815444 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="24815444"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 24815444, container: ".js-paper-rank-work_24815444", }); 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The proposed method automatically generates appropriate changes in density at locations where the hydrodynamic theory would call for a shockwave; i.e. a jump in density such as those typically seen at the end of every queue. The complex side calculations required by classical methods to keep track of shockwaves are thus eliminated. The paper also shows how the equations can mimic the real-life development of stop-and-go traffic within moving queues. 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u-pv7x u-mb0x js-work-card work_25487824 coauthored" data-work_id="25487824" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/25487824/A_Traffic_Object_Detection_System_for_Road_Traffic_Measurement_and_Management">A Traffic Object Detection System for Road Traffic Measurement and Management</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">OIS is a new Optical Information System for road traffic observation and management. The complete system architecture from the sensor for automatic traffic detection up to the traffic light management for a wide area is designed under the... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_25487824" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">OIS is a new Optical Information System for road traffic observation and management. The complete system architecture from the sensor for automatic traffic detection up to the traffic light management for a wide area is designed under the requirements of an intelligent transportation system. Particular features of this system are the vision sensors with integrated computational and real-time capabilities, real-time</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/25487824" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="0d364fbe7e18bb677acf9c7007504e53" rel="nofollow" data-download="{"attachment_id":45805002,"asset_id":25487824,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/45805002/download_file?st=MTczMjQyMjgxOSw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="38381689" href="https://hu-berlin.academia.edu/RalfReulke">Ralf Reulke</a><script data-card-contents-for-user="38381689" type="text/json">{"id":38381689,"first_name":"Ralf","last_name":"Reulke","domain_name":"hu-berlin","page_name":"RalfReulke","display_name":"Ralf Reulke","profile_url":"https://hu-berlin.academia.edu/RalfReulke?f_ri=22247","photo":"/images/s65_no_pic.png"}</script></span></span><span class="u-displayInlineBlock InlineList-item-text"> and <span class="u-textDecorationUnderline u-clickable InlineList-item-text js-work-more-authors-25487824">+3</span><div class="hidden js-additional-users-25487824"><div><span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a href="https://independent.academia.edu/CarstenDalaff">Carsten Dalaff</a></span></div><div><span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a href="https://independent.academia.edu/AdrianSchischmanow">Adrian Schischmanow</a></span></div><div><span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a href="https://independent.academia.edu/GeraldSchlotzhauer">Gerald Schlotzhauer</a></span></div></div></span><script>(function(){ var popoverSettings = { el: $('.js-work-more-authors-25487824'), placement: 'bottom', hide_delay: 200, html: true, content: function(){ return $('.js-additional-users-25487824').html(); 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The developed signal control... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_3479682" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">Rapid urbanization and the growing demand for faster transportation has led to heavy congestion in road traffic networks, necessitating the need for traffic-responsive intelligent signal control systems. The developed signal control system must be capable of determining the green time that minimizes the network-wide travel time delay based on limited information of the environment. This paper adopts a distributed multiagent-based approach to develop a traffic-responsive signal control system, i.e., the geometric fuzzy multiagent system (GFMAS), which is based on a geometric type-2 fuzzy inference system. GFMAS is capable of handling the various levels of uncertainty found in the inputs and rule base of the traffic signal controller. Simulation models of the agents designed in PARAMICS were tested on virtual road network replicating a section of the central business district in Singapore. A comprehensive analysis and comparison was performed against the existing traffic-control algorithms green link determining (GLIDE) and hierarchical multiagent system (HMS). The proposed GFMAS signal control outperformed both the benchmarks when tested for typical traffic-flow scenarios. Further tests show the superior performance of the proposed GFMAS in handling unplanned and planned incidents and obstructions. The promising results demonstrate the efficiency of the proposed multiagent architecture and scope for future development.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/3479682" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="d5e1471c71a7220d1016e87726476241" rel="nofollow" data-download="{"attachment_id":50267404,"asset_id":3479682,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/50267404/download_file?st=MTczMjQyMjgxOSw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="4080160" href="https://independent.academia.edu/BalajiParasumanna">Balaji Parasumanna</a><script data-card-contents-for-user="4080160" type="text/json">{"id":4080160,"first_name":"Balaji","last_name":"Parasumanna","domain_name":"independent","page_name":"BalajiParasumanna","display_name":"Balaji Parasumanna","profile_url":"https://independent.academia.edu/BalajiParasumanna?f_ri=22247","photo":"https://0.academia-photos.com/4080160/157100970/146736015/s65_balaji.parasumanna.jpeg"}</script></span></span></li><li class="js-paper-rank-work_3479682 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="3479682"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 3479682, container: ".js-paper-rank-work_3479682", }); 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Further tests show the superior performance of the proposed GFMAS in handling unplanned and planned incidents and obstructions. The promising results demonstrate the efficiency of the proposed multiagent architecture and scope for future development.","downloadable_attachments":[{"id":50267404,"asset_id":3479682,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":4080160,"first_name":"Balaji","last_name":"Parasumanna","domain_name":"independent","page_name":"BalajiParasumanna","display_name":"Balaji Parasumanna","profile_url":"https://independent.academia.edu/BalajiParasumanna?f_ri=22247","photo":"https://0.academia-photos.com/4080160/157100970/146736015/s65_balaji.parasumanna.jpeg"}],"research_interests":[{"id":73,"name":"Civil Engineering","url":"https://www.academia.edu/Documents/in/Civil_Engineering?f_ri=22247","nofollow":false},{"id":456,"name":"Type Theory","url":"https://www.academia.edu/Documents/in/Type_Theory?f_ri=22247","nofollow":false},{"id":465,"name":"Artificial 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href="https://www.academia.edu/51373816/Optimizing_Traffic_Control_to_Reduce_Fuel_Consumption_and_Vehicular_Emissions">Optimizing Traffic Control to Reduce Fuel Consumption and Vehicular Emissions</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">One way to reduce excessive fuel consumption and vehicular emissions on urban streets is to optimize signal timings. Historically, signal timing optimization tools were used to reduce traffic delay and stops. The concept of optimizing... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_51373816" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">One way to reduce excessive fuel consumption and vehicular emissions on urban streets is to optimize signal timings. Historically, signal timing optimization tools were used to reduce traffic delay and stops. The concept of optimizing signal timings to reduce fuel consumption and emissions was addressed decades ago with tools that are now considered outdated. This study advocates a fresh approach to integrating existing state-of-the-art tools for reassessing and ultimately minimizing fuel consumption and emissions. VISSIM, CMEM, and VISGAOST were linked to optimize signal timings and minimize fuel consumption and CO2 emissions. As a case study, a 14-intersection network in Park City, Utah, was used. Signal timings were optimized for seven optimization objective functions to find the lowest fuel consumption and CO2 emissions. Findings show that a formula commonly used to estimate fuel consumption in traffic simulation tools inadequately estimates fuel consumption and cannot be used a...</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/51373816" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="8915db984f1e8fc56667875e25dba0f5" rel="nofollow" data-download="{"attachment_id":69125349,"asset_id":51373816,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/69125349/download_file?st=MTczMjQyMjgxOSw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="106025346" href="https://independent.academia.edu/JelkaStevanovic">Jelka Stevanovic</a><script data-card-contents-for-user="106025346" type="text/json">{"id":106025346,"first_name":"Jelka","last_name":"Stevanovic","domain_name":"independent","page_name":"JelkaStevanovic","display_name":"Jelka Stevanovic","profile_url":"https://independent.academia.edu/JelkaStevanovic?f_ri=22247","photo":"/images/s65_no_pic.png"}</script></span></span></li><li class="js-paper-rank-work_51373816 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="51373816"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 51373816, container: ".js-paper-rank-work_51373816", }); 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Historically, signal timing optimization tools were used to reduce traffic delay and stops. The concept of optimizing signal timings to reduce fuel consumption and emissions was addressed decades ago with tools that are now considered outdated. This study advocates a fresh approach to integrating existing state-of-the-art tools for reassessing and ultimately minimizing fuel consumption and emissions. VISSIM, CMEM, and VISGAOST were linked to optimize signal timings and minimize fuel consumption and CO2 emissions. As a case study, a 14-intersection network in Park City, Utah, was used. Signal timings were optimized for seven optimization objective functions to find the lowest fuel consumption and CO2 emissions. 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type="text/json">{"id":22247,"name":"Traffic control","url":"https://www.academia.edu/Documents/in/Traffic_control?f_ri=22247","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="1127663" href="https://www.academia.edu/Documents/in/Field_Data">Field Data</a>, <script data-card-contents-for-ri="1127663" type="text/json">{"id":1127663,"name":"Field Data","url":"https://www.academia.edu/Documents/in/Field_Data?f_ri=22247","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="1208732" href="https://www.academia.edu/Documents/in/Simulation_Model">Simulation Model</a><script data-card-contents-for-ri="1208732" type="text/json">{"id":1208732,"name":"Simulation Model","url":"https://www.academia.edu/Documents/in/Simulation_Model?f_ri=22247","nofollow":false}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=23529540]'), work: {"id":23529540,"title":"Passing sight distance on two-lane highways: Review and revision","created_at":"2016-03-21T15:11:03.276-07:00","url":"https://www.academia.edu/23529540/Passing_sight_distance_on_two_lane_highways_Review_and_revision?f_ri=22247","dom_id":"work_23529540","summary":null,"downloadable_attachments":[{"id":43964108,"asset_id":23529540,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":45443700,"first_name":"Said","last_name":"Easa","domain_name":"independent","page_name":"SaidEasa","display_name":"Said Easa","profile_url":"https://independent.academia.edu/SaidEasa?f_ri=22247","photo":"/images/s65_no_pic.png"}],"research_interests":[{"id":20436,"name":"Urban And Regional Planning","url":"https://www.academia.edu/Documents/in/Urban_And_Regional_Planning?f_ri=22247","nofollow":false},{"id":22247,"name":"Traffic control","url":"https://www.academia.edu/Documents/in/Traffic_control?f_ri=22247","nofollow":false},{"id":1127663,"name":"Field 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A typical datacenter is made up of thousands of servers connected with a large network and... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_35448278" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">—Datacenters provide cost-effective and flexible access to scalable compute and storage resources necessary for today's cloud computing needs. A typical datacenter is made up of thousands of servers connected with a large network and usually managed by one operator. To provide quality access to the variety of applications and services hosted on datacenters and maximize performance, it deems necessary to use datacenter networks effectively and efficiently. Datacenter traffic is often a mix of several classes with different priorities and requirements. This includes user-generated interactive traffic, traffic with deadlines, and long-running traffic. To this end, custom transport protocols and traffic management techniques have been developed to improve datacenter network performance. In this tutorial paper, we review the general architecture of datacenter networks, various topologies proposed for them, their traffic properties, general traffic control challenges in datacenters and general traffic control objectives. The purpose of this paper is to bring out the important characteristics of traffic control in datacenters and not to survey all existing solutions (as it is virtually impossible due to massive body of existing research). We hope to provide readers with a wide range of options and factors while considering a variety of traffic control mechanisms. We discuss various characteristics of datacenter traffic control including management schemes, transmission control, traffic shaping, prioritization, load balancing, multipathing, and traffic scheduling. Next, we point to several open challenges as well as new and interesting networking paradigms. At the end of this paper, we briefly review inter-datacenter networks that connect geographically dispersed datacenters which have been receiving increasing attention recently and pose interesting and novel research problems. To measure the performance of datacenter networks, different performance metrics have been used such as flow completion times, deadline miss rate, throughput and fairness. Depending on the application and user requirements, some metrics may need more attention. While investigating different traffic control techniques, we point out the trade-offs involved in terms of costs, complexity and performance. We find that a combination of different traffic control techniques may be necessary at particular entities and layers in the network to improve the variety of performance metrics. We also find that despite significant research efforts, there are still open problems that demand further attention from the research community.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/35448278" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="69f6a2bfe0e606546e94a0a87432547c" rel="nofollow" data-download="{"attachment_id":55309756,"asset_id":35448278,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/55309756/download_file?st=MTczMjQyMjgxOSw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="60691401" href="https://usc.academia.edu/noormoha">Mohammad Noormohammadpour</a><script data-card-contents-for-user="60691401" type="text/json">{"id":60691401,"first_name":"Mohammad","last_name":"Noormohammadpour","domain_name":"usc","page_name":"noormoha","display_name":"Mohammad Noormohammadpour","profile_url":"https://usc.academia.edu/noormoha?f_ri=22247","photo":"https://0.academia-photos.com/60691401/15863927/26454595/s65_mohammad.noormohammadpour.jpg"}</script></span></span></li><li class="js-paper-rank-work_35448278 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="35448278"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 35448278, container: ".js-paper-rank-work_35448278", }); 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A typical datacenter is made up of thousands of servers connected with a large network and usually managed by one operator. To provide quality access to the variety of applications and services hosted on datacenters and maximize performance, it deems necessary to use datacenter networks effectively and efficiently. Datacenter traffic is often a mix of several classes with different priorities and requirements. This includes user-generated interactive traffic, traffic with deadlines, and long-running traffic. To this end, custom transport protocols and traffic management techniques have been developed to improve datacenter network performance. In this tutorial paper, we review the general architecture of datacenter networks, various topologies proposed for them, their traffic properties, general traffic control challenges in datacenters and general traffic control objectives. The purpose of this paper is to bring out the important characteristics of traffic control in datacenters and not to survey all existing solutions (as it is virtually impossible due to massive body of existing research). We hope to provide readers with a wide range of options and factors while considering a variety of traffic control mechanisms. We discuss various characteristics of datacenter traffic control including management schemes, transmission control, traffic shaping, prioritization, load balancing, multipathing, and traffic scheduling. Next, we point to several open challenges as well as new and interesting networking paradigms. At the end of this paper, we briefly review inter-datacenter networks that connect geographically dispersed datacenters which have been receiving increasing attention recently and pose interesting and novel research problems. 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various pedestrian facilities: an examination based on observation and survey data","created_at":"2015-10-27T13:47:17.959-07:00","url":"https://www.academia.edu/17363581/Pedestrian_behaviors_at_and_perceptions_towards_various_pedestrian_facilities_an_examination_based_on_observation_and_survey_data?f_ri=22247","dom_id":"work_17363581","summary":null,"downloadable_attachments":[{"id":39468799,"asset_id":17363581,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":34374253,"first_name":"Virginia","last_name":"Sisiopiku","domain_name":"ua-birmingham","page_name":"VirginiaSisiopiku","display_name":"Virginia Sisiopiku","profile_url":"https://ua-birmingham.academia.edu/VirginiaSisiopiku?f_ri=22247","photo":"/images/s65_no_pic.png"}],"research_interests":[{"id":221,"name":"Psychology","url":"https://www.academia.edu/Documents/in/Psychology?f_ri=22247","nofollow":false},{"id":22247,"name":"Traffic control","url":"https://www.academia.edu/Documents/in/Traffic_control?f_ri=22247","nofollow":false},{"id":313195,"name":"Survey data","url":"https://www.academia.edu/Documents/in/Survey_data?f_ri=22247","nofollow":false},{"id":910024,"name":"Observational Study","url":"https://www.academia.edu/Documents/in/Observational_Study?f_ri=22247","nofollow":false}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_13580554" data-work_id="13580554" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/13580554/Review_of_Closed_Circuit_Television_CCTV_Techniques_for_Vehicles_Traffic_Management">Review of Closed Circuit Television (CCTV) Techniques for Vehicles Traffic Management</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">Due to the population increase all over the world current road infrastructures are unable to keep up with the escalating transportation demands. This situation where travel demands exceeds the capacity of the transportation network is... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_13580554" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">Due to the population increase all over the world current road infrastructures are unable to keep up with the escalating transportation demands. This situation where travel demands exceeds the capacity of the transportation network is known as traffic congestion. However, it is impractical to build more roads and infrastructure to accommodate these demands. Governments are increasingly recognizing the importance of traffic control tools, such as Closed Circuit Television (CCTV) systems as a feasible solution to mitigate the traffic congestion problem. CCTV systems are deployed across city centres, motorways, trunk roads, car parks etc., to collect diverse data on large regions where manual observation can be difficult, problematic or unfeasible. By processing this data, which contains video images of traffic parameters, useful information can be extracted, including speed, traffic composition,<br />vehicle shapes, vehicle types, vehicle identification numbers and occurrences of traffic violations or road accidents.<br /><br />This paper reviews different approaches to utilize CCTV systems for traffic management of Vehicles. It highlights existing architectural, deployment models, and various approaches to analyse generated traffic data. The objective is to provide a clear background that can help in any related future research.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/13580554" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="1559a5daf334222f7a083008ea5bb817" rel="nofollow" data-download="{"attachment_id":38079516,"asset_id":13580554,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/38079516/download_file?st=MTczMjQyMjgxOSw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="26099575" href="https://independent.academia.edu/JournalIJCSIT">International Journal of Computer Science & Information Technology (IJCSIT)</a><script data-card-contents-for-user="26099575" type="text/json">{"id":26099575,"first_name":"International Journal of Computer Science \u0026 Information Technology","last_name":"(IJCSIT)","domain_name":"independent","page_name":"JournalIJCSIT","display_name":"International Journal of Computer Science \u0026 Information Technology (IJCSIT)","profile_url":"https://independent.academia.edu/JournalIJCSIT?f_ri=22247","photo":"https://0.academia-photos.com/26099575/8320480/13234227/s65_international_journal_of_computer_science_information_technology._ijcsit_.jpg"}</script></span></span></li><li class="js-paper-rank-work_13580554 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="13580554"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 13580554, container: ".js-paper-rank-work_13580554", }); 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$(".js-view-count[data-work-id=13580554]").text(description); $(".js-view-count-work_13580554").attr('title', description).tooltip(); }); });</script></span><script>$(function() { $(".js-view-count-work_13580554").removeClass('hidden') })</script></div></li><li class="InlineList-item u-positionRelative" style="max-width: 250px"><div class="u-positionAbsolute" data-has-card-for-ri-list="13580554"><i class="fa fa-tag InlineList-item-icon u-positionRelative"></i>  <a class="InlineList-item-text u-positionRelative">8</a>  </div><span class="InlineList-item-text u-textTruncate u-pl9x"><a class="InlineList-item-text" data-has-card-for-ri="5473" href="https://www.academia.edu/Documents/in/Embedded_Systems">Embedded Systems</a>, <script data-card-contents-for-ri="5473" type="text/json">{"id":5473,"name":"Embedded Systems","url":"https://www.academia.edu/Documents/in/Embedded_Systems?f_ri=22247","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="22247" href="https://www.academia.edu/Documents/in/Traffic_control">Traffic control</a>, <script data-card-contents-for-ri="22247" type="text/json">{"id":22247,"name":"Traffic control","url":"https://www.academia.edu/Documents/in/Traffic_control?f_ri=22247","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="159178" href="https://www.academia.edu/Documents/in/Cctv">Cctv</a>, <script data-card-contents-for-ri="159178" type="text/json">{"id":159178,"name":"Cctv","url":"https://www.academia.edu/Documents/in/Cctv?f_ri=22247","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="267901" href="https://www.academia.edu/Documents/in/Computer_science_and_Information_Technology">Computer science & Information Technology</a><script data-card-contents-for-ri="267901" type="text/json">{"id":267901,"name":"Computer science \u0026 Information Technology","url":"https://www.academia.edu/Documents/in/Computer_science_and_Information_Technology?f_ri=22247","nofollow":false}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=13580554]'), work: {"id":13580554,"title":"Review of Closed Circuit Television (CCTV) Techniques for Vehicles Traffic Management","created_at":"2015-07-03T02:43:03.674-07:00","url":"https://www.academia.edu/13580554/Review_of_Closed_Circuit_Television_CCTV_Techniques_for_Vehicles_Traffic_Management?f_ri=22247","dom_id":"work_13580554","summary":"Due to the population increase all over the world current road infrastructures are unable to keep up with the escalating transportation demands. This situation where travel demands exceeds the capacity of the transportation network is known as traffic congestion. However, it is impractical to build more roads and infrastructure to accommodate these demands. Governments are increasingly recognizing the importance of traffic control tools, such as Closed Circuit Television (CCTV) systems as a feasible solution to mitigate the traffic congestion problem. CCTV systems are deployed across city centres, motorways, trunk roads, car parks etc., to collect diverse data on large regions where manual observation can be difficult, problematic or unfeasible. By processing this data, which contains video images of traffic parameters, useful information can be extracted, including speed, traffic composition,\nvehicle shapes, vehicle types, vehicle identification numbers and occurrences of traffic violations or road accidents.\n\nThis paper reviews different approaches to utilize CCTV systems for traffic management of Vehicles. It highlights existing architectural, deployment models, and various approaches to analyse generated traffic data. The objective is to provide a clear background that can help in any related future research.","downloadable_attachments":[{"id":38079516,"asset_id":13580554,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":26099575,"first_name":"International Journal of Computer Science \u0026 Information Technology","last_name":"(IJCSIT)","domain_name":"independent","page_name":"JournalIJCSIT","display_name":"International Journal of Computer Science \u0026 Information Technology (IJCSIT)","profile_url":"https://independent.academia.edu/JournalIJCSIT?f_ri=22247","photo":"https://0.academia-photos.com/26099575/8320480/13234227/s65_international_journal_of_computer_science_information_technology._ijcsit_.jpg"}],"research_interests":[{"id":5473,"name":"Embedded Systems","url":"https://www.academia.edu/Documents/in/Embedded_Systems?f_ri=22247","nofollow":false},{"id":22247,"name":"Traffic control","url":"https://www.academia.edu/Documents/in/Traffic_control?f_ri=22247","nofollow":false},{"id":159178,"name":"Cctv","url":"https://www.academia.edu/Documents/in/Cctv?f_ri=22247","nofollow":false},{"id":267901,"name":"Computer science \u0026 Information Technology","url":"https://www.academia.edu/Documents/in/Computer_science_and_Information_Technology?f_ri=22247","nofollow":false},{"id":319931,"name":"Computer Science and Information Technology","url":"https://www.academia.edu/Documents/in/Computer_Science_and_Information_Technology-1?f_ri=22247"},{"id":1583507,"name":"Sensors Network","url":"https://www.academia.edu/Documents/in/Sensors_Network?f_ri=22247"},{"id":1985824,"name":"Review of Closed Circuit Television","url":"https://www.academia.edu/Documents/in/Review_of_Closed_Circuit_Television?f_ri=22247"},{"id":1985825,"name":"Vehicles Traffic Management","url":"https://www.academia.edu/Documents/in/Vehicles_Traffic_Management?f_ri=22247"}]}, }) } })();</script></ul></li></ul></div></div><div class="u-borderBottom1 u-borderColorGrayLighter"><div class="clearfix u-pv7x u-mb0x js-work-card work_41829422 coauthored" data-work_id="41829422" itemscope="itemscope" itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/41829422/DENSITY_BASED_TRAFFIC_CONTROL_USING_IoT_">DENSITY BASED TRAFFIC CONTROL USING IoT</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">With the rapid development of road infrastructure, the volume of the vehicle on the road network increases which leads to traffic Congestion. The exact situation exists in the Coimbatore cities. Traffic congestions are amongst the top... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_41829422" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">With the rapid development of road infrastructure, the volume of the vehicle on the road network increases which leads to traffic Congestion. The exact situation exists in the Coimbatore cities. Traffic congestions are amongst the top list of the problems faced in Muscat and other cities around Coimbatore. This is mainly caused due to the rapid surprise in the number of vehicles in a short period. To overcome such an impact of traffic congestions, it is required to develop an IoT Based traffic control system. The proposed system would be based on the measurement of the actual traffic density on the road. This would be achieved using real-time video and image processing techniques. Wherein the images captured and are stored in the server, which will be compared with the real-time image captured via camera to identify the density. The theme is to control the traffic by determining the traffic density on each side of the four roads and enabling a controlling option of the traffic signal to the user through a software application.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/41829422" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="27fcb60c04069753eafee5d561070fbc" rel="nofollow" data-download="{"attachment_id":61967073,"asset_id":41829422,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/61967073/download_file?st=MTczMjQyMjgxOSw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="2902340" href="https://ijcsmc.academia.edu/IJCSMCJournal">IJCSMC Journal</a><script data-card-contents-for-user="2902340" type="text/json">{"id":2902340,"first_name":"IJCSMC","last_name":"Journal","domain_name":"ijcsmc","page_name":"IJCSMCJournal","display_name":"IJCSMC Journal","profile_url":"https://ijcsmc.academia.edu/IJCSMCJournal?f_ri=22247","photo":"https://0.academia-photos.com/2902340/955759/1197349/s65_ijcsmc.journal.jpg"}</script></span></span><span class="u-displayInlineBlock InlineList-item-text"> and <span class="u-textDecorationUnderline u-clickable InlineList-item-text js-work-more-authors-41829422">+1</span><div class="hidden js-additional-users-41829422"><div><span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a href="https://independent.academia.edu/SrimathiW">Srimathi W</a></span></div></div></span><script>(function(){ var popoverSettings = { el: $('.js-work-more-authors-41829422'), placement: 'bottom', hide_delay: 200, html: true, content: function(){ return $('.js-additional-users-41829422').html(); 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The exact situation exists in the Coimbatore cities. Traffic congestions are amongst the top list of the problems faced in Muscat and other cities around Coimbatore. This is mainly caused due to the rapid surprise in the number of vehicles in a short period. To overcome such an impact of traffic congestions, it is required to develop an IoT Based traffic control system. The proposed system would be based on the measurement of the actual traffic density on the road. This would be achieved using real-time video and image processing techniques. Wherein the images captured and are stored in the server, which will be compared with the real-time image captured via camera to identify the density. The theme is to control the traffic by determining the traffic density on each side of the four roads and enabling a controlling option of the traffic signal to the user through a software application.","downloadable_attachments":[{"id":61967073,"asset_id":41829422,"asset_type":"Work","always_allow_download":false}],"ordered_authors":[{"id":2902340,"first_name":"IJCSMC","last_name":"Journal","domain_name":"ijcsmc","page_name":"IJCSMCJournal","display_name":"IJCSMC Journal","profile_url":"https://ijcsmc.academia.edu/IJCSMCJournal?f_ri=22247","photo":"https://0.academia-photos.com/2902340/955759/1197349/s65_ijcsmc.journal.jpg"},{"id":145520923,"first_name":"Srimathi","last_name":"W","domain_name":"independent","page_name":"SrimathiW","display_name":"Srimathi 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data-has-card-for-ri="5395" href="https://www.academia.edu/Documents/in/Swarm_Intelligence">Swarm Intelligence</a>, <script data-card-contents-for-ri="5395" type="text/json">{"id":5395,"name":"Swarm Intelligence","url":"https://www.academia.edu/Documents/in/Swarm_Intelligence?f_ri=22247","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="6420" href="https://www.academia.edu/Documents/in/Ant_Colony_Optimization">Ant Colony Optimization</a>, <script data-card-contents-for-ri="6420" type="text/json">{"id":6420,"name":"Ant Colony Optimization","url":"https://www.academia.edu/Documents/in/Ant_Colony_Optimization?f_ri=22247","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="22247" href="https://www.academia.edu/Documents/in/Traffic_control">Traffic control</a>, <script data-card-contents-for-ri="22247" type="text/json">{"id":22247,"name":"Traffic 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itemtype="https://schema.org/ScholarlyArticle"><div class="header"><div class="title u-fontSerif u-fs22 u-lineHeight1_3"><a class="u-tcGrayDarkest js-work-link" href="https://www.academia.edu/5483783/Neural_Network_Based_Models_for_Short_Term_Traffic_Flow_Forecasting_Using_a_Hybrid_Exponential_Smoothing_and_Levenberg_Marquardt_Algorithm">Neural-Network-Based Models for Short-Term Traffic Flow Forecasting Using a Hybrid Exponential Smoothing and Levenberg–Marquardt Algorithm</a></div></div><div class="u-pb4x u-mt3x"><div class="summary u-fs14 u-fw300 u-lineHeight1_5 u-tcGrayDarkest"><div class="summarized">This paper proposes a novel neural network (NN) training method that employs the hybrid exponential smoothing method and the Levenberg-Marquardt (LM) algorithm, which aims to improve the generalization capabilities of previously used... <a class="more_link u-tcGrayDark u-linkUnstyled" data-container=".work_5483783" data-show=".complete" data-hide=".summarized" data-more-link-behavior="true" href="#">more</a></div><div class="complete hidden">This paper proposes a novel neural network (NN) training method that employs the hybrid exponential smoothing method and the Levenberg-Marquardt (LM) algorithm, which aims to improve the generalization capabilities of previously used methods for training NNs for short-term traffic flow forecasting. The approach uses exponential smoothing to preprocess traffic flow data by removing the lumpiness from collected traffic flow data, before employing a variant of the LM algorithm to train the NN weights of an NN model. This approach aids NN training, as the preprocessed traffic flow data are more smooth and continuous than the original unprocessed traffic flow data. The proposed method was evaluated by forecasting short-term traffic flow conditions on the Mitchell freeway in Western Australia. With regard to the generalization capabilities for short-term traffic flow forecasting, the NN models developed using the proposed approach outperform those that are developed based on the alternative tested algorithms, which are particularly designed either for short-term traffic flow forecasting or for enhancing generalization capabilities of NNs.</div></div></div><ul class="InlineList u-ph0x u-fs13"><li class="InlineList-item logged_in_only"><div class="share_on_academia_work_button"><a class="academia_share Button Button--inverseBlue Button--sm js-bookmark-button" data-academia-share="Work/5483783" data-share-source="work_strip" data-spinner="small_white_hide_contents"><i class="fa fa-plus"></i><span class="work-strip-link-text u-ml1x" data-content="button_text">Bookmark</span></a></div></li><li class="InlineList-item"><div class="download"><a id="252a11af94d3fa220d2dd358a5afcfbe" rel="nofollow" data-download="{"attachment_id":49275804,"asset_id":5483783,"asset_type":"Work","always_allow_download":false,"track":null,"button_location":"work_strip","source":null,"hide_modal":null}" class="Button Button--sm Button--inverseGreen js-download-button prompt_button doc_download" href="https://www.academia.edu/attachments/49275804/download_file?st=MTczMjQyMjgxOSw4LjIyMi4yMDguMTQ2&s=work_strip"><i class="fa fa-arrow-circle-o-down fa-lg"></i><span class="u-textUppercase u-ml1x" data-content="button_text">Download</span></a></div></li><li class="InlineList-item"><ul class="InlineList InlineList--bordered u-ph0x"><li class="InlineList-item InlineList-item--bordered"><span class="InlineList-item-text">by <span itemscope="itemscope" itemprop="author" itemtype="https://schema.org/Person"><a class="u-tcGrayDark u-fw700" data-has-card-for-user="7713383" href="https://curtin.academia.edu/kityanchan">kit yan chan</a><script data-card-contents-for-user="7713383" type="text/json">{"id":7713383,"first_name":"kit yan","last_name":"chan","domain_name":"curtin","page_name":"kityanchan","display_name":"kit yan chan","profile_url":"https://curtin.academia.edu/kityanchan?f_ri=22247","photo":"/images/s65_no_pic.png"}</script></span></span></li><li class="js-paper-rank-work_5483783 InlineList-item InlineList-item--bordered hidden"><span class="js-paper-rank-view hidden u-tcGrayDark" data-paper-rank-work-id="5483783"><i class="u-m1x fa fa-bar-chart"></i><strong class="js-paper-rank"></strong></span><script>$(function() { new Works.PaperRankView({ workId: 5483783, container: ".js-paper-rank-work_5483783", }); 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The approach uses exponential smoothing to preprocess traffic flow data by removing the lumpiness from collected traffic flow data, before employing a variant of the LM algorithm to train the NN weights of an NN model. This approach aids NN training, as the preprocessed traffic flow data are more smooth and continuous than the original unprocessed traffic flow data. The proposed method was evaluated by forecasting short-term traffic flow conditions on the Mitchell freeway in Western Australia. 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type="text/json">{"id":440,"name":"Distributed Computing","url":"https://www.academia.edu/Documents/in/Distributed_Computing?f_ri=22247","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="14212" href="https://www.academia.edu/Documents/in/Group_communication">Group communication</a>, <script data-card-contents-for-ri="14212" type="text/json">{"id":14212,"name":"Group communication","url":"https://www.academia.edu/Documents/in/Group_communication?f_ri=22247","nofollow":false}</script><a class="InlineList-item-text" data-has-card-for-ri="22247" href="https://www.academia.edu/Documents/in/Traffic_control">Traffic control</a><script data-card-contents-for-ri="22247" type="text/json">{"id":22247,"name":"Traffic control","url":"https://www.academia.edu/Documents/in/Traffic_control?f_ri=22247","nofollow":false}</script></span></li><script>(function(){ if (true) { new Aedu.ResearchInterestListCard({ el: $('*[data-has-card-for-ri-list=891192]'), work: 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