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class="upload-header"><h2 class="ds2-5-heading-sans-serif-xs">Uploads</h2></div><div class="documents-container backbone-social-profile-documents" style="width: 100%;"><div class="u-taCenter"></div><div class="profile--tab_content_container js-tab-pane tab-pane active" id="all"><div class="profile--tab_heading_container js-section-heading" data-section="Papers" id="Papers"><h3 class="profile--tab_heading_container">Papers by Liping Fu</h3></div><div class="js-work-strip profile--work_container" data-work-id="82889811"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/82889811/Vehicular_Person_and_Pedestrian_Delays_at_Signalised_Intersections"><img alt="Research paper thumbnail of Vehicular, Person and Pedestrian Delays at Signalised Intersections" class="work-thumbnail" src="https://attachments.academia-assets.com/88441159/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/82889811/Vehicular_Person_and_Pedestrian_Delays_at_Signalised_Intersections">Vehicular, Person and Pedestrian Delays at Signalised Intersections</a></div><div class="wp-workCard_item"><span>IFAC Proceedings Volumes</span><span>, 1997</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="6be68d9b487b96380520be7dc637fbdc" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":88441159,"asset_id":82889811,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/88441159/download_file?st=MTczMjc4NzMwOCw4LjIyMi4yMDguMTQ2&s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="82889809"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/82889809/Location_Optimization_of_Road_Weather_Information_System_RWIS_Network_Considering_the_Needs_of_Winter_Road_Maintenance_and_the_Traveling_Public"><img alt="Research paper thumbnail of Location Optimization of Road Weather Information System (RWIS) Network Considering the Needs of Winter Road Maintenance and the Traveling Public" class="work-thumbnail" src="https://attachments.academia-assets.com/88441158/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/82889809/Location_Optimization_of_Road_Weather_Information_System_RWIS_Network_Considering_the_Needs_of_Winter_Road_Maintenance_and_the_Traveling_Public">Location Optimization of Road Weather Information System (RWIS) Network Considering the Needs of Winter Road Maintenance and the Traveling Public</a></div><div class="wp-workCard_item"><span>Computer-Aided Civil and Infrastructure Engineering</span><span>, 2016</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="f98b5d6a0cf9270538b6d56d204b0fe6" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":88441158,"asset_id":82889809,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/88441158/download_file?st=MTczMjc4NzMwOCw4LjIyMi4yMDguMTQ2&s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="82889809"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="82889809"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 82889809; 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The problem is formulated to minimize the spatially averaged kriging variance of hazardous road surface conditions while maximizing the coverage of accident-prone areas. This optimization framework takes explicit account of the value of information from an RWIS network, providing the potential to enhance the overall efficacy of winter maintenance operations and the safety of the travelers. Spatial simulated annealing is used to solve the resulting optimization problem and its performance is demonstrated using a real-world case study from Minnesota, United States. The case study illustrates the distinct features of the proposed model, assesses the effectiveness of the current location setting, and recommends additional stations locations. 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="82889807"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/82889807/Developing_Safety_Performance_Functions_for_Railway_Grade_Crossings_A_Case_Study_of_Canada"><img alt="Research paper thumbnail of Developing Safety Performance Functions for Railway Grade Crossings: A Case Study of Canada" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/82889807/Developing_Safety_Performance_Functions_for_Railway_Grade_Crossings_A_Case_Study_of_Canada">Developing Safety Performance Functions for Railway Grade Crossings: A Case Study of Canada</a></div><div class="wp-workCard_item"><span>2015 Joint Rail Conference</span><span>, 2015</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Although accident frequencies at railway grade crossings have shown a decreasing trend over the l...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Although accident frequencies at railway grade crossings have shown a decreasing trend over the last two decades (partly due to implemented safety improvements and technological advances), safety at grade crossings is still a major concern since crossing accidents are usually associated with devastating consequences. This paper investigates the effect of various site attributes on railway crossing safety outcomes using recent Canada wide data from a 6-year period (2008–2013). The new data sets allow adjusting previous accident models according to latest circumstances (e.g., vehicles’ improved safety features) affecting safety dynamics at crossings. Employing Bayesian hierarchical models including the non-conventional Poisson-Weibull model, different safety performance functions were separately developed for crossings with the following major warning systems: (1) flashing light and bell (FLB), (2) flashing light, bell, and gate (FLBG), (3) standard reflectorized crossing sign (SRCS), and (4) standard reflectorized crossing sign and stop sign (SRCS &amp; STOP). Among other findings, the results indicated that traffic exposure (product of train and vehicle), number of lanes, whistle prohibition, train speed, and road speed were the most important factors affecting accident frequencies at Canadian railway crossings. It should be also noted that safety performance functions vary, in terms of independent variables and their associated coefficients, between the aforementioned warning devices.Copyright © 2015 by ASME</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="82889807"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="82889807"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 82889807; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=82889807]").text(description); $(".js-view-count[data-work-id=82889807]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 82889807; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='82889807']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 82889807, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=82889807]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":82889807,"title":"Developing Safety Performance Functions for Railway Grade Crossings: A Case Study of Canada","translated_title":"","metadata":{"abstract":"Although accident frequencies at railway grade crossings have shown a decreasing trend over the last two decades (partly due to implemented safety improvements and technological advances), safety at grade crossings is still a major concern since crossing accidents are usually associated with devastating consequences. 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Among other findings, the results indicated that traffic exposure (product of train and vehicle), number of lanes, whistle prohibition, train speed, and road speed were the most important factors affecting accident frequencies at Canadian railway crossings. It should be also noted that safety performance functions vary, in terms of independent variables and their associated coefficients, between the aforementioned warning devices.Copyright © 2015 by ASME","publication_date":{"day":null,"month":null,"year":2015,"errors":{}},"publication_name":"2015 Joint Rail Conference"},"translated_abstract":"Although accident frequencies at railway grade crossings have shown a decreasing trend over the last two decades (partly due to implemented safety improvements and technological advances), safety at grade crossings is still a major concern since crossing accidents are usually associated with devastating consequences. This paper investigates the effect of various site attributes on railway crossing safety outcomes using recent Canada wide data from a 6-year period (2008–2013). The new data sets allow adjusting previous accident models according to latest circumstances (e.g., vehicles’ improved safety features) affecting safety dynamics at crossings. Employing Bayesian hierarchical models including the non-conventional Poisson-Weibull model, different safety performance functions were separately developed for crossings with the following major warning systems: (1) flashing light and bell (FLB), (2) flashing light, bell, and gate (FLBG), (3) standard reflectorized crossing sign (SRCS), and (4) standard reflectorized crossing sign and stop sign (SRCS \u0026amp; STOP). Among other findings, the results indicated that traffic exposure (product of train and vehicle), number of lanes, whistle prohibition, train speed, and road speed were the most important factors affecting accident frequencies at Canadian railway crossings. It should be also noted that safety performance functions vary, in terms of independent variables and their associated coefficients, between the aforementioned warning devices.Copyright © 2015 by ASME","internal_url":"https://www.academia.edu/82889807/Developing_Safety_Performance_Functions_for_Railway_Grade_Crossings_A_Case_Study_of_Canada","translated_internal_url":"","created_at":"2022-07-10T13:00:22.502-07:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":168547610,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[],"slug":"Developing_Safety_Performance_Functions_for_Railway_Grade_Crossings_A_Case_Study_of_Canada","translated_slug":"","page_count":null,"language":"en","content_type":"Work","owner":{"id":168547610,"first_name":"Liping","middle_initials":null,"last_name":"Fu","page_name":"FuLiping","domain_name":"independent","created_at":"2020-09-01T07:37:24.003-07:00","display_name":"Liping Fu","url":"https://independent.academia.edu/FuLiping"},"attachments":[],"research_interests":[],"urls":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="82889805"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/82889805/Paper_Submitted_to_2003_Annual_Conference_of_the_Transportation_Association_of_Canada_A_METHOD_FOR_QUANTITATIVELY_PRIORITISING_TRANSPORTATION_PROJECTS_ON_THE_BASIS_OF_SUSTAINABILITY"><img alt="Research paper thumbnail of Paper Submitted to 2003 Annual Conference of the Transportation Association of Canada A METHOD FOR QUANTITATIVELY PRIORITISING TRANSPORTATION PROJECTS ON THE BASIS OF SUSTAINABILITY" class="work-thumbnail" src="https://attachments.academia-assets.com/88441154/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/82889805/Paper_Submitted_to_2003_Annual_Conference_of_the_Transportation_Association_of_Canada_A_METHOD_FOR_QUANTITATIVELY_PRIORITISING_TRANSPORTATION_PROJECTS_ON_THE_BASIS_OF_SUSTAINABILITY">Paper Submitted to 2003 Annual Conference of the Transportation Association of Canada A METHOD FOR QUANTITATIVELY PRIORITISING TRANSPORTATION PROJECTS ON THE BASIS OF SUSTAINABILITY</a></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="3a722c317628e5bf406ff30093d8df05" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":88441154,"asset_id":82889805,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/88441154/download_file?st=MTczMjc4NzMwOCw4LjIyMi4yMDguMTQ2&s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="82889805"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="82889805"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 82889805; 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="82889797"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/82889797/Design_and_Implementation_of_Bus_Holding_Control_Strategies_with_Real_Time_Information"><img alt="Research paper thumbnail of Design and Implementation of Bus–Holding Control Strategies with Real-Time Information" class="work-thumbnail" src="https://attachments.academia-assets.com/88441151/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/82889797/Design_and_Implementation_of_Bus_Holding_Control_Strategies_with_Real_Time_Information">Design and Implementation of Bus–Holding Control Strategies with Real-Time Information</a></div><div class="wp-workCard_item"><span>Transportation Research Record: Journal of the Transportation Research Board</span><span>, 2002</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">A systematic study is described to address various design and implementation issues associated wi...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">A systematic study is described to address various design and implementation issues associated with the problem of real-time bus holding control. Two holding control models have been investigated. The first model follows the conventional threshold-based control logic that determines holding times on the basis of headway to the preceding bus. The second model makes use of both preceding and following headways in identifying optimal control decisions with the assumption that real-time bus location information is available for estimating future bus arrivals at the control stop. An extensive simulation analysis is performed using a real-fife bus route operated by the Grand River Transit of the region of Waterloo, Ontario. 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The simulation results have substantiated several conclusions and yielded new findings on various issues such as where to set the control point, how many control points should be used, what is the optimal control strength, and what is the value of real-time location in...","publisher":"SAGE Publications","publication_date":{"day":null,"month":null,"year":2002,"errors":{}},"publication_name":"Transportation Research Record: Journal of the Transportation Research Board"},"translated_abstract":"A systematic study is described to address various design and implementation issues associated with the problem of real-time bus holding control. Two holding control models have been investigated. The first model follows the conventional threshold-based control logic that determines holding times on the basis of headway to the preceding bus. 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The simulation results have substantiated several conclusions and yielded new findings on various issues such as where to set the control point, how many control points should be used, what is the optimal control strength, and what is the value of real-time location in...","internal_url":"https://www.academia.edu/82889797/Design_and_Implementation_of_Bus_Holding_Control_Strategies_with_Real_Time_Information","translated_internal_url":"","created_at":"2022-07-10T13:00:19.742-07:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":168547610,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[{"id":88441151,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/88441151/thumbnails/1.jpg","file_name":"ab80894d95a96535b5c875c9f84d6d83b0bc.pdf","download_url":"https://www.academia.edu/attachments/88441151/download_file?st=MTczMjc4NzMwOCw4LjIyMi4yMDguMTQ2&","bulk_download_file_name":"Design_and_Implementation_of_Bus_Holding.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/88441151/ab80894d95a96535b5c875c9f84d6d83b0bc-libre.pdf?1657508690=\u0026response-content-disposition=attachment%3B+filename%3DDesign_and_Implementation_of_Bus_Holding.pdf\u0026Expires=1732781801\u0026Signature=L5kWukdwCP4xFSD8EZ65QbXkEFA9wMHFhDdYKB4NLXdpYZBvPXfzkEcriJJ5oOFSd0EhAqT7SzDQMmXErBafrQeHhgQUta2qJVIUN3r8RzGePnvQBH5Q4phe3O4nnkno2ie27OKnnCM6wtEViHKDEL7GXIzBFYW2WEl6yxaj~5kdgoQgqavyxXXcauSSyZRsqZYAGrw3RA9T0X707ioSgpysoG5oOu2zKi24SYVoPme7hxY0NN4k3QQjgwzwWPNtwp9ndqqE2Z~D0x4eBkVUPK-o78MNb40DEV0sauJGufNXfkp5NmqFFOGk9fH~J6UzC1BTbknI9GKkaR8R5ubukA__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}],"slug":"Design_and_Implementation_of_Bus_Holding_Control_Strategies_with_Real_Time_Information","translated_slug":"","page_count":7,"language":"en","content_type":"Work","owner":{"id":168547610,"first_name":"Liping","middle_initials":null,"last_name":"Fu","page_name":"FuLiping","domain_name":"independent","created_at":"2020-09-01T07:37:24.003-07:00","display_name":"Liping Fu","url":"https://independent.academia.edu/FuLiping"},"attachments":[{"id":88441151,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/88441151/thumbnails/1.jpg","file_name":"ab80894d95a96535b5c875c9f84d6d83b0bc.pdf","download_url":"https://www.academia.edu/attachments/88441151/download_file?st=MTczMjc4NzMwOCw4LjIyMi4yMDguMTQ2&","bulk_download_file_name":"Design_and_Implementation_of_Bus_Holding.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/88441151/ab80894d95a96535b5c875c9f84d6d83b0bc-libre.pdf?1657508690=\u0026response-content-disposition=attachment%3B+filename%3DDesign_and_Implementation_of_Bus_Holding.pdf\u0026Expires=1732781801\u0026Signature=L5kWukdwCP4xFSD8EZ65QbXkEFA9wMHFhDdYKB4NLXdpYZBvPXfzkEcriJJ5oOFSd0EhAqT7SzDQMmXErBafrQeHhgQUta2qJVIUN3r8RzGePnvQBH5Q4phe3O4nnkno2ie27OKnnCM6wtEViHKDEL7GXIzBFYW2WEl6yxaj~5kdgoQgqavyxXXcauSSyZRsqZYAGrw3RA9T0X707ioSgpysoG5oOu2zKi24SYVoPme7hxY0NN4k3QQjgwzwWPNtwp9ndqqE2Z~D0x4eBkVUPK-o78MNb40DEV0sauJGufNXfkp5NmqFFOGk9fH~J6UzC1BTbknI9GKkaR8R5ubukA__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}],"research_interests":[{"id":48,"name":"Engineering","url":"https://www.academia.edu/Documents/in/Engineering"},{"id":73,"name":"Civil Engineering","url":"https://www.academia.edu/Documents/in/Civil_Engineering"},{"id":2200,"name":"Optimal Control","url":"https://www.academia.edu/Documents/in/Optimal_Control"},{"id":20436,"name":"Urban And Regional Planning","url":"https://www.academia.edu/Documents/in/Urban_And_Regional_Planning"},{"id":34756,"name":"System Design","url":"https://www.academia.edu/Documents/in/System_Design"},{"id":46271,"name":"Strategy","url":"https://www.academia.edu/Documents/in/Strategy"},{"id":48636,"name":"Simulation","url":"https://www.academia.edu/Documents/in/Simulation"},{"id":69542,"name":"Computer Simulation","url":"https://www.academia.edu/Documents/in/Computer_Simulation"},{"id":97610,"name":"Bus","url":"https://www.academia.edu/Documents/in/Bus"},{"id":129253,"name":"Real Time Control","url":"https://www.academia.edu/Documents/in/Real_Time_Control"},{"id":161318,"name":"Mathematical Models","url":"https://www.academia.edu/Documents/in/Mathematical_Models"},{"id":229390,"name":"Real Time","url":"https://www.academia.edu/Documents/in/Real_Time"},{"id":238655,"name":"Implementation","url":"https://www.academia.edu/Documents/in/Implementation"},{"id":291387,"name":"Mathematical Model","url":"https://www.academia.edu/Documents/in/Mathematical_Model"},{"id":889662,"name":"Holding Time","url":"https://www.academia.edu/Documents/in/Holding_Time"},{"id":1208732,"name":"Simulation Model","url":"https://www.academia.edu/Documents/in/Simulation_Model"}],"urls":[{"id":22053100,"url":"http://journals.sagepub.com/doi/pdf/10.3141/1791-02"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="82889788"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/82889788/Empirical_evidence_from_the_Greater_Toronto_Area_on_the_acceptability_and_impacts_of_HOT_lanes"><img alt="Research paper thumbnail of Empirical evidence from the Greater Toronto Area on the acceptability and impacts of HOT lanes" class="work-thumbnail" src="https://attachments.academia-assets.com/88441145/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/82889788/Empirical_evidence_from_the_Greater_Toronto_Area_on_the_acceptability_and_impacts_of_HOT_lanes">Empirical evidence from the Greater Toronto Area on the acceptability and impacts of HOT lanes</a></div><div class="wp-workCard_item"><span>Transport Policy</span><span>, 2011</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="5e4b37e5f1ac1509800bad9344c3be6b" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":88441145,"asset_id":82889788,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/88441145/download_file?st=MTczMjc4NzMwOCw4LjIyMi4yMDguMTQ2&s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="82889788"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="82889788"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 82889788; 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From a stated preference survey of more than 250 drivers, we estimate mean willingness to pay values under various trip conditions and for various traveler characteristics. The study provides statistically significant evidence on the relationships between willingness to pay and the improvement in travel speeds in HOT lanes, the length of the trip, and the urgency of on-time arrival. Furthermore, our study confirms several literature findings from previous studies on the relationship between travelers' willingness to pay and income as well as prior experience with HOT lanes. Some of the findings are qualitatively validated on the basis of the observed travel behavior in choosing tolled facilities over untolled facilities during periods of heightened congestion and urgency.","publication_date":{"day":null,"month":null,"year":2011,"errors":{}},"publication_name":"Transport Policy","grobid_abstract_attachment_id":88441145},"translated_abstract":null,"internal_url":"https://www.academia.edu/82889788/Empirical_evidence_from_the_Greater_Toronto_Area_on_the_acceptability_and_impacts_of_HOT_lanes","translated_internal_url":"","created_at":"2022-07-10T13:00:08.587-07:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":168547610,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[{"id":88441145,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/88441145/thumbnails/1.jpg","file_name":"papers_5C2011-1_20Empirical_20evidence_20of_20acceptability_20of_20HOT.pdf","download_url":"https://www.academia.edu/attachments/88441145/download_file?st=MTczMjc4NzMwOCw4LjIyMi4yMDguMTQ2&","bulk_download_file_name":"Empirical_evidence_from_the_Greater_Toro.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/88441145/papers_5C2011-1_20Empirical_20evidence_20of_20acceptability_20of_20HOT-libre.pdf?1657508711=\u0026response-content-disposition=attachment%3B+filename%3DEmpirical_evidence_from_the_Greater_Toro.pdf\u0026Expires=1732749004\u0026Signature=QK~kRDaS9GOgmbWt3Om0x~MCzb2W5aR1MVqDp3VBtvMdqux79AqFxlPFb932rbd-xc6dupdl1xq952WQIkRcslRCNgkqxZ0CzZL4E21C04xA7yiwgLf4v9VEkZcmuGRHKjmJ~WrpXuxBV2p~IjyJisqcPzRJf551OkraJSdQroqj6aLZFnvcqsLB6I6Gesq~G6SiPreciLaF3Fz0v8kDpJlnXLBiPAh616b2mjM3nmof6yswU5Kiq-nxEZZRh0Q80PO6fKqIxe7C0EUFjkGXdIO4t6kY1BLDd06gb57kJqs55AbJgW4uEafmtB9XiYx4HlOb7pv-jSjnlZ62PGcrkw__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}],"slug":"Empirical_evidence_from_the_Greater_Toronto_Area_on_the_acceptability_and_impacts_of_HOT_lanes","translated_slug":"","page_count":11,"language":"en","content_type":"Work","owner":{"id":168547610,"first_name":"Liping","middle_initials":null,"last_name":"Fu","page_name":"FuLiping","domain_name":"independent","created_at":"2020-09-01T07:37:24.003-07:00","display_name":"Liping Fu","url":"https://independent.academia.edu/FuLiping"},"attachments":[{"id":88441145,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/88441145/thumbnails/1.jpg","file_name":"papers_5C2011-1_20Empirical_20evidence_20of_20acceptability_20of_20HOT.pdf","download_url":"https://www.academia.edu/attachments/88441145/download_file?st=MTczMjc4NzMwOCw4LjIyMi4yMDguMTQ2&","bulk_download_file_name":"Empirical_evidence_from_the_Greater_Toro.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/88441145/papers_5C2011-1_20Empirical_20evidence_20of_20acceptability_20of_20HOT-libre.pdf?1657508711=\u0026response-content-disposition=attachment%3B+filename%3DEmpirical_evidence_from_the_Greater_Toro.pdf\u0026Expires=1732749004\u0026Signature=QK~kRDaS9GOgmbWt3Om0x~MCzb2W5aR1MVqDp3VBtvMdqux79AqFxlPFb932rbd-xc6dupdl1xq952WQIkRcslRCNgkqxZ0CzZL4E21C04xA7yiwgLf4v9VEkZcmuGRHKjmJ~WrpXuxBV2p~IjyJisqcPzRJf551OkraJSdQroqj6aLZFnvcqsLB6I6Gesq~G6SiPreciLaF3Fz0v8kDpJlnXLBiPAh616b2mjM3nmof6yswU5Kiq-nxEZZRh0Q80PO6fKqIxe7C0EUFjkGXdIO4t6kY1BLDd06gb57kJqs55AbJgW4uEafmtB9XiYx4HlOb7pv-jSjnlZ62PGcrkw__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}],"research_interests":[{"id":724,"name":"Economics","url":"https://www.academia.edu/Documents/in/Economics"},{"id":20436,"name":"Urban And Regional Planning","url":"https://www.academia.edu/Documents/in/Urban_And_Regional_Planning"},{"id":62828,"name":"Transport policy","url":"https://www.academia.edu/Documents/in/Transport_policy"},{"id":125564,"name":"Statistical Significance","url":"https://www.academia.edu/Documents/in/Statistical_Significance"},{"id":234951,"name":"Travel Time","url":"https://www.academia.edu/Documents/in/Travel_Time"},{"id":393134,"name":"Empirical evidence","url":"https://www.academia.edu/Documents/in/Empirical_evidence"},{"id":414736,"name":"Stated Preference","url":"https://www.academia.edu/Documents/in/Stated_Preference"},{"id":435206,"name":"Willingness to Pay","url":"https://www.academia.edu/Documents/in/Willingness_to_Pay"},{"id":453803,"name":"Travel Behavior","url":"https://www.academia.edu/Documents/in/Travel_Behavior"},{"id":501613,"name":"Hot","url":"https://www.academia.edu/Documents/in/Hot"},{"id":2108071,"name":"Data Gathering","url":"https://www.academia.edu/Documents/in/Data_Gathering"},{"id":4081772,"name":"High Occupancy Toll Lanes","url":"https://www.academia.edu/Documents/in/High_Occupancy_Toll_Lanes"}],"urls":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="82889759"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/82889759/An_Efficient_Optimization_Approach_to_Real_Time_Coordinated_and_Integrated_Freeway_Traffic_Control"><img alt="Research paper thumbnail of An Efficient Optimization Approach to Real-Time Coordinated and Integrated Freeway Traffic Control" class="work-thumbnail" src="https://attachments.academia-assets.com/88441144/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/82889759/An_Efficient_Optimization_Approach_to_Real_Time_Coordinated_and_Integrated_Freeway_Traffic_Control">An Efficient Optimization Approach to Real-Time Coordinated and Integrated Freeway Traffic Control</a></div><div class="wp-workCard_item"><span>IEEE Transactions on Intelligent Transportation Systems</span><span>, 2010</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="c36b3f932617f19584f46be3f79d716e" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":88441144,"asset_id":82889759,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/88441144/download_file?st=MTczMjc4NzMwOCw4LjIyMi4yMDguMTQ2&s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="82889759"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="82889759"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 82889759; 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One promising ap-6 proach to this problem is casting the underlying dynamic control 7 problem in a model predictive framework. The challenge is that 8 the resulting optimization problem is computationally intractable 9 for online applications in a network with a large number of 10 controllers. In this paper, a game-theoretic approach with distrib-11 uted controllers is proposed to address the foregoing issue. The 12 efficiency of the proposed method is tested for a coordinated ramp 13 metering and variable-speed limit control applied to a stretch of 14 freeway network. The parallel nature of the optimization algo-15 rithm makes it suitable for solving large-scale problems with high 16 accuracy. The speed and accuracy of the proposed solution ap-17 proach are examined and compared with that of the conventional 18 optimization method in a case study to demonstrate its superior 19 performance. 20 Index Terms-Distributed controllers, game theory, model pre-21 dictive control (MPC), parallel optimization, ramp metering, 22 speed limit control. 23 I. INTRODUCTION 24 S EVERAL methods have been developed to improve the 25 performance of freeway networks. Among them, control 26 strategies such as ramp metering, speed limits, and route rec-27 ommendation are recognized as the most effective ways to 28 relieve the freeway traffic congestion. Furthermore, the latest 29 advances in computers and communication technologies have 30 made it feasible to implement network-wide multiple traffic 31 control systems, as opposed to single local control schemes.","publication_date":{"day":null,"month":null,"year":2010,"errors":{}},"publication_name":"IEEE Transactions on Intelligent Transportation 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class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/82889719/Reducing_the_threat_of_in_transit_derailments_involving_dangerous_goods_through_effective_placement_along_the_train_consist">Reducing the threat of in-transit derailments involving dangerous goods through effective placement along the train consist</a></div><div class="wp-workCard_item"><span>Accident Analysis &amp; Prevention</span><span>, 2011</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="cf79678d97f7cf5fd84c2dce8ab649a3" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":88441103,"asset_id":82889719,"asset_type":"Work","button_location":"profile"}" 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})(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "cf79678d97f7cf5fd84c2dce8ab649a3" } } $('.js-work-strip[data-work-id=82889719]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":82889719,"title":"Reducing the threat of in-transit derailments involving dangerous goods through effective placement along the train consist","translated_title":"","metadata":{"publisher":"Elsevier BV","grobid_abstract":"Train derailments are important safety concerns, and they become increasingly so when dangerous goods (DG) are involved. One way to reduce the risk of DG derailments is through effective DG railway car placement along the train consist. This paper investigates the relationship between DG railway car placement and derailment for different route attributes and DG shipments. A model is presented for estimating the probability of derailment by position, based on the estimated point of derailment (POD) and the number of cars derailing. A DG placement model that considers in-transit derailment risk is shown to provide a sound scientific basis for effective DG marshalling in conventional rail hump yard operations.","publication_date":{"day":null,"month":null,"year":2011,"errors":{}},"publication_name":"Accident Analysis \u0026amp; 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data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/82889673/Development_of_a_global_road_safety_performance_function_using_deep_neural_networks"><img alt="Research paper thumbnail of Development of a global road safety performance function using deep neural networks" class="work-thumbnail" src="https://attachments.academia-assets.com/88441063/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/82889673/Development_of_a_global_road_safety_performance_function_using_deep_neural_networks">Development of a global road safety performance function using deep neural networks</a></div><div class="wp-workCard_item"><span>International Journal of Transportation Science and Technology</span><span>, 2017</span></div><div class="wp-workCard_item 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deep neural networks","translated_title":"","metadata":{"publisher":"Elsevier BV","ai_title_tag":"Global Road Safety Prediction via Deep Neural Networks","grobid_abstract":"This paper explores the idea of applying a machine learning approach to develop a global road safety performance function (SFP) that can be used to predict the expected crash frequencies of different highways from different regions. A deep belief network (DBN)-one of the most popular deep learning models is introduced as an alternative to the traditional regression models for crash modelling. An extensive empirical study is conducted using three real world crash data sets covering six classes of highways as defined by location (urban vs. rural), number of lanes, access control, and region. The study involves a number of experiments aiming at addressing several critical questions pertaining to the relative performance of the DBN in terms of network structure, training method, data size, and generalization ability, as compared to the traditional regression models. 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="75065096"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/75065096/Simulation_Model_for_Evaluating_Intelligent_Paratransit_Systems"><img alt="Research paper thumbnail of Simulation Model for Evaluating Intelligent Paratransit Systems" class="work-thumbnail" src="https://attachments.academia-assets.com/82984880/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/75065096/Simulation_Model_for_Evaluating_Intelligent_Paratransit_Systems">Simulation Model for Evaluating Intelligent Paratransit Systems</a></div><div class="wp-workCard_item"><span>Transportation Research Record: Journal of the Transportation Research Board</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="1a9002c14eebc142e58946230c6874b3" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":82984880,"asset_id":75065096,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/82984880/download_file?st=MTczMjc4NzMwOCw4LjIyMi4yMDguMTQ2&s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="75065096"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="75065096"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 75065096; 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class="work-thumbnail" src="https://attachments.academia-assets.com/82984946/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/75065094/Potential_Effects_of_Automatic_Vehicle_Location_and_Computer_Aided_Dispatch_Technology_on_Paratransit_Performance_A_Simulation_Study">Potential Effects of Automatic Vehicle Location and Computer-Aided Dispatch Technology on Paratransit Performance: A Simulation Study</a></div><div class="wp-workCard_item"><span>Transportation Research Record: Journal of the Transportation Research Board</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Automatic vehicle location (AVL) and computer-aided dispatch (CAD) systems have afforded a unique...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Automatic vehicle location (AVL) and computer-aided dispatch (CAD) systems have afforded a unique opportunity for public transit agencies to integrate these technologies in their paratransit systems for improved productivity and reliability. This opportunity has also prompted widespread interest in quantifying the benefits that can be attained from such technological enhancement. This research assesses the potential effects of AVL and CAD on the productivity and service reliability of a paratransit system. A simulation model that can realistically model AVL and CAD functionality is used in the investigation. Many cases representing variations in operating environment, such as service area, demand intensity, and proportion of real-time demand trips, are simulated for a sensitivity analysis under three assumed operational improvements—en route diversion, dwell time reduction, and periodic reoptimization. The results indicate that although AVL and CAD effectiveness varies from case to ...</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="2934aeab934141d49083c5701c3dae2a" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":82984946,"asset_id":75065094,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/82984946/download_file?st=MTczMjc4NzMwOCw4LjIyMi4yMDguMTQ2&s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="75065094"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="75065094"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 75065094; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=75065094]").text(description); $(".js-view-count[data-work-id=75065094]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 75065094; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='75065094']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 75065094, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "2934aeab934141d49083c5701c3dae2a" } } $('.js-work-strip[data-work-id=75065094]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":75065094,"title":"Potential Effects of Automatic Vehicle Location and Computer-Aided Dispatch Technology on Paratransit Performance: A Simulation Study","translated_title":"","metadata":{"abstract":"Automatic vehicle location (AVL) and computer-aided dispatch (CAD) systems have afforded a unique opportunity for public transit agencies to integrate these technologies in their paratransit systems for improved productivity and reliability. 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src="https://attachments.academia-assets.com/82984945/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/75065092/Planning_and_Design_of_Flex_Route_Transit_Services">Planning and Design of Flex-Route Transit Services</a></div><div class="wp-workCard_item"><span>Transportation Research Record: Journal of the Transportation Research Board</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">A theoretical investigation is presented of various issues involved in the planning and design of...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">A theoretical investigation is presented of various issues involved in the planning and design of flex-route transit services. An analytical model is proposed for an idealized operating environment with the objective of determining the optimal slack time that should be allocated to a flexroute segment. The optimization objective is defined to minimize total operator and user cost, which enables a systematic examination of complex interactions among the system parameters. An equation is derived for the relationship between the number of feasible deviations and various system parameters such as slack time, zone size, and dwell time. Subsequent analysis shows that the analytical model is elaborate enough to provide substantial insights into various issues that may arise in designing a flex-route service. A simulation analysis is conducted to validate some of the conclusions drawn from the analytical model and to further analyze the implications of stochastic variation in passenger demand.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="bee915ec09e1159eef2e02cc37981c7b" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":82984945,"asset_id":75065092,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/82984945/download_file?st=MTczMjc4NzMwOCw4LjIyMi4yMDguMTQ2&s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="75065092"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="75065092"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 75065092; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=75065092]").text(description); $(".js-view-count[data-work-id=75065092]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 75065092; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='75065092']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 75065092, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "bee915ec09e1159eef2e02cc37981c7b" } } $('.js-work-strip[data-work-id=75065092]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":75065092,"title":"Planning and Design of Flex-Route Transit Services","translated_title":"","metadata":{"abstract":"A theoretical investigation is presented of various issues involved in the planning and design of flex-route transit services. 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Subsequent analysis shows that the analytical model is elaborate enough to provide substantial insights into various issues that may arise in designing a flex-route service. 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="75065091"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/75065091/Road_weather_information_system_stations_where_and_how_many_to_install_a_cost_benefit_analysis_approach"><img alt="Research paper thumbnail of Road weather information system stations — where and how many to install: a cost benefit analysis approach" class="work-thumbnail" src="https://attachments.academia-assets.com/83485098/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/75065091/Road_weather_information_system_stations_where_and_how_many_to_install_a_cost_benefit_analysis_approach">Road weather information system stations — where and how many to install: a cost benefit analysis approach</a></div><div class="wp-workCard_item"><span>Canadian Journal of Civil Engineering</span><span>, 2015</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">This paper presents a cost–benefit based approach to the problem of finding the optimal location ...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">This paper presents a cost–benefit based approach to the problem of finding the optimal location and density of road weather information system (RWIS) stations over a regional road network. The novelty of the proposed method lies in the models that can be used to estimate the benefits of RWIS information, including reduced maintenance costs and collisions, thus determining the optimal number and location of a RWIS network. A case study based on the existing RWIS network in Northern Minnesota in the US is used to show the application of the proposed approach. Linear regression models are developed for the annual maintenance costs and the expected number of collisions that could occur on two types of highways delineated by the existence of a RWIS station nearby. The calibrated models are then applied to individual highway segments defined on the basis of a uniform grid system to determine the expected benefit of having a RWIS station installed. These benefits along with RWIS installat...</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="2f311a37e0a9378d0cc23c1d273ceb44" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":83485098,"asset_id":75065091,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/83485098/download_file?st=MTczMjc4NzMwOCw4LjIyMi4yMDguMTQ2&s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="75065091"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="75065091"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 75065091; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=75065091]").text(description); $(".js-view-count[data-work-id=75065091]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 75065091; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='75065091']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 75065091, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "2f311a37e0a9378d0cc23c1d273ceb44" } } $('.js-work-strip[data-work-id=75065091]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":75065091,"title":"Road weather information system stations — where and how many to install: a cost benefit analysis approach","translated_title":"","metadata":{"abstract":"This paper presents a cost–benefit based approach to the problem of finding the optimal location and density of road weather information system (RWIS) stations over a regional road network. The novelty of the proposed method lies in the models that can be used to estimate the benefits of RWIS information, including reduced maintenance costs and collisions, thus determining the optimal number and location of a RWIS network. A case study based on the existing RWIS network in Northern Minnesota in the US is used to show the application of the proposed approach. Linear regression models are developed for the annual maintenance costs and the expected number of collisions that could occur on two types of highways delineated by the existence of a RWIS station nearby. The calibrated models are then applied to individual highway segments defined on the basis of a uniform grid system to determine the expected benefit of having a RWIS station installed. These benefits along with RWIS installat...","publisher":"Canadian Science Publishing","publication_date":{"day":null,"month":null,"year":2015,"errors":{}},"publication_name":"Canadian Journal of Civil Engineering"},"translated_abstract":"This paper presents a cost–benefit based approach to the problem of finding the optimal location and density of road weather information system (RWIS) stations over a regional road network. The novelty of the proposed method lies in the models that can be used to estimate the benefits of RWIS information, including reduced maintenance costs and collisions, thus determining the optimal number and location of a RWIS network. A case study based on the existing RWIS network in Northern Minnesota in the US is used to show the application of the proposed approach. Linear regression models are developed for the annual maintenance costs and the expected number of collisions that could occur on two types of highways delineated by the existence of a RWIS station nearby. The calibrated models are then applied to individual highway segments defined on the basis of a uniform grid system to determine the expected benefit of having a RWIS station installed. 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="75065090"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/75065090/Analyzing_injury_severity_factors_at_highway_railway_grade_crossing_accidents_involving_vulnerable_road_users_A_comparative_study"><img alt="Research paper thumbnail of Analyzing injury severity factors at highway railway grade crossing accidents involving vulnerable road users: A comparative study" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" rel="nofollow" href="https://www.academia.edu/75065090/Analyzing_injury_severity_factors_at_highway_railway_grade_crossing_accidents_involving_vulnerable_road_users_A_comparative_study">Analyzing injury severity factors at highway railway grade crossing accidents involving vulnerable road users: A comparative study</a></div><div class="wp-workCard_item"><span>Traffic Injury Prevention</span><span>, 2016</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">The main objective of this study is to identify the main factors associated with injury severity ...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">The main objective of this study is to identify the main factors associated with injury severity of the vulnerable road user (VRU) involved in the accidents at highway railroad grade crossings (HRGC) using data mining techniques. This paper applies Ordered Probit model, Association Rules and Classification-Regression Tree (CART) algorithms to the U.S. Federal Railroad Administration (FRA) HRGC accident database for the period of 2007-2013, to identify VRU injury severity factors at HRGCs. The results show that train speed is the key factor influencing the injury severity. Further analysis illustrated that the presence of an illumination does not reduce the severity of accidents for high speed train. Also there is a greater propensity towards fatal accidents for elderly road users compared to the younger individuals. Interestingly, during the night, injury accident involving a female road user is more sever in comparison to a male. The Ordered Probit Model was the primary technique, and CART and Association Rules act as the supporter and identifier of interactions between variables. All of the three algorithms results, consistently show that the most influential accident factors such as the train speed, VRU age and gender. The findings of this research could be applied for identifying high-risk hotspots and developing cost-effective countermeasures targeting VRUs at HRGC.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="75065090"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="75065090"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 75065090; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=75065090]").text(description); $(".js-view-count[data-work-id=75065090]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 75065090; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='75065090']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 75065090, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=75065090]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":75065090,"title":"Analyzing injury severity factors at highway railway grade crossing accidents involving vulnerable road users: A comparative study","translated_title":"","metadata":{"abstract":"The main objective of this study is to identify the main factors associated with injury severity of the vulnerable road user (VRU) involved in the accidents at highway railroad grade crossings (HRGC) using data mining techniques. This paper applies Ordered Probit model, Association Rules and Classification-Regression Tree (CART) algorithms to the U.S. Federal Railroad Administration (FRA) HRGC accident database for the period of 2007-2013, to identify VRU injury severity factors at HRGCs. The results show that train speed is the key factor influencing the injury severity. Further analysis illustrated that the presence of an illumination does not reduce the severity of accidents for high speed train. Also there is a greater propensity towards fatal accidents for elderly road users compared to the younger individuals. Interestingly, during the night, injury accident involving a female road user is more sever in comparison to a male. The Ordered Probit Model was the primary technique, and CART and Association Rules act as the supporter and identifier of interactions between variables. All of the three algorithms results, consistently show that the most influential accident factors such as the train speed, VRU age and gender. The findings of this research could be applied for identifying high-risk hotspots and developing cost-effective countermeasures targeting VRUs at HRGC.","publisher":"Informa UK Limited","publication_date":{"day":null,"month":null,"year":2016,"errors":{}},"publication_name":"Traffic Injury Prevention"},"translated_abstract":"The main objective of this study is to identify the main factors associated with injury severity of the vulnerable road user (VRU) involved in the accidents at highway railroad grade crossings (HRGC) using data mining techniques. This paper applies Ordered Probit model, Association Rules and Classification-Regression Tree (CART) algorithms to the U.S. Federal Railroad Administration (FRA) HRGC accident database for the period of 2007-2013, to identify VRU injury severity factors at HRGCs. The results show that train speed is the key factor influencing the injury severity. Further analysis illustrated that the presence of an illumination does not reduce the severity of accidents for high speed train. Also there is a greater propensity towards fatal accidents for elderly road users compared to the younger individuals. Interestingly, during the night, injury accident involving a female road user is more sever in comparison to a male. The Ordered Probit Model was the primary technique, and CART and Association Rules act as the supporter and identifier of interactions between variables. All of the three algorithms results, consistently show that the most influential accident factors such as the train speed, VRU age and gender. The findings of this research could be applied for identifying high-risk hotspots and developing cost-effective countermeasures targeting VRUs at HRGC.","internal_url":"https://www.academia.edu/75065090/Analyzing_injury_severity_factors_at_highway_railway_grade_crossing_accidents_involving_vulnerable_road_users_A_comparative_study","translated_internal_url":"","created_at":"2022-03-31T05:30:34.219-07:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":168547610,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[],"slug":"Analyzing_injury_severity_factors_at_highway_railway_grade_crossing_accidents_involving_vulnerable_road_users_A_comparative_study","translated_slug":"","page_count":null,"language":"en","content_type":"Work","owner":{"id":168547610,"first_name":"Liping","middle_initials":null,"last_name":"Fu","page_name":"FuLiping","domain_name":"independent","created_at":"2020-09-01T07:37:24.003-07:00","display_name":"Liping Fu","url":"https://independent.academia.edu/FuLiping"},"attachments":[],"research_interests":[{"id":48,"name":"Engineering","url":"https://www.academia.edu/Documents/in/Engineering"},{"id":221,"name":"Psychology","url":"https://www.academia.edu/Documents/in/Psychology"},{"id":2009,"name":"Data Mining","url":"https://www.academia.edu/Documents/in/Data_Mining"},{"id":26327,"name":"Medicine","url":"https://www.academia.edu/Documents/in/Medicine"},{"id":47297,"name":"Automotive Engineering","url":"https://www.academia.edu/Documents/in/Automotive_Engineering"},{"id":98134,"name":"United States","url":"https://www.academia.edu/Documents/in/United_States"},{"id":192721,"name":"Risk factors","url":"https://www.academia.edu/Documents/in/Risk_factors"},{"id":226488,"name":"Vulnerable Populations","url":"https://www.academia.edu/Documents/in/Vulnerable_Populations"},{"id":289271,"name":"Aged","url":"https://www.academia.edu/Documents/in/Aged"},{"id":434017,"name":"Railroads","url":"https://www.academia.edu/Documents/in/Railroads"},{"id":620049,"name":"Risk Factors","url":"https://www.academia.edu/Documents/in/Risk_Factors-1"},{"id":1031658,"name":"Wounds and Injuries","url":"https://www.academia.edu/Documents/in/Wounds_and_Injuries"},{"id":2467531,"name":"Trauma Severity Indices","url":"https://www.academia.edu/Documents/in/Trauma_Severity_Indices"},{"id":4002452,"name":"Accidents Traffic","url":"https://www.academia.edu/Documents/in/Accidents_Traffic"}],"urls":[{"id":18979419,"url":"https://www.tandfonline.com/doi/pdf/10.1080/15389588.2016.1151011"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="75065089"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/75065089/Road_surface_condition_classification_method_and_system"><img alt="Research paper thumbnail of Road surface condition classification method and system" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" rel="nofollow" href="https://www.academia.edu/75065089/Road_surface_condition_classification_method_and_system">Road surface condition classification method and system</a></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="75065089"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="75065089"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 75065089; 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="75065088"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/75065088/A_multi_class_transit_assignment_model_for_estimating_transit_passenger_flows_a_case_study_of_Beijing_subway_network"><img alt="Research paper thumbnail of A multi-class transit assignment model for estimating transit passenger flows-a case study of Beijing subway network" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/75065088/A_multi_class_transit_assignment_model_for_estimating_transit_passenger_flows_a_case_study_of_Beijing_subway_network">A multi-class transit assignment model for estimating transit passenger flows-a case study of Beijing subway network</a></div><div class="wp-workCard_item"><span>Journal of Advanced Transportation</span><span>, 2015</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">ABSTRACT This paper describes a case study comparing a multi-class transit assignment model with ...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">ABSTRACT This paper describes a case study comparing a multi-class transit assignment model with its single class counterpart for estimating the passenger flows of the Beijing subway network—one of the largest railway transit networks in the world. Multi-class traffic assignment has been widely considered as a theoretically sound approach to capture the inherent variation in users&amp;#39; route choice behavior. However, few empirical studies have been devoted to showing the effectiveness of this approach in improving the accuracy of the underlying passenger flow estimation process. In this research, a passenger classification scheme is proposed on the basis of a dataset from a large stated preference survey conducted in the City of Beijing, China. Separate generalized cost functions are calibrated for different classes of subway users in Beijing and applied in a multi-class transit assignment model for estimating passenger flows over a subway network. The case study has shown that the proposed multi-class approach resulted in significantly improved estimation results with an average estimation error of less than 15% on the transfer flows as compared with 30% for the single class model. Copyright © 2015 John Wiley &amp;amp; Sons, Ltd.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="75065088"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="75065088"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 75065088; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=75065088]").text(description); $(".js-view-count[data-work-id=75065088]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 75065088; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='75065088']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 75065088, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=75065088]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":75065088,"title":"A multi-class transit assignment model for estimating transit passenger flows-a case study of Beijing subway network","translated_title":"","metadata":{"abstract":"ABSTRACT This paper describes a case study comparing a multi-class transit assignment model with its single class counterpart for estimating the passenger flows of the Beijing subway network—one of the largest railway transit networks in the world. Multi-class traffic assignment has been widely considered as a theoretically sound approach to capture the inherent variation in users\u0026amp;#39; route choice behavior. However, few empirical studies have been devoted to showing the effectiveness of this approach in improving the accuracy of the underlying passenger flow estimation process. In this research, a passenger classification scheme is proposed on the basis of a dataset from a large stated preference survey conducted in the City of Beijing, China. Separate generalized cost functions are calibrated for different classes of subway users in Beijing and applied in a multi-class transit assignment model for estimating passenger flows over a subway network. The case study has shown that the proposed multi-class approach resulted in significantly improved estimation results with an average estimation error of less than 15% on the transfer flows as compared with 30% for the single class model. Copyright © 2015 John Wiley \u0026amp;amp; Sons, Ltd.","publisher":"Wiley-Blackwell","publication_date":{"day":null,"month":null,"year":2015,"errors":{}},"publication_name":"Journal of Advanced Transportation"},"translated_abstract":"ABSTRACT This paper describes a case study comparing a multi-class transit assignment model with its single class counterpart for estimating the passenger flows of the Beijing subway network—one of the largest railway transit networks in the world. Multi-class traffic assignment has been widely considered as a theoretically sound approach to capture the inherent variation in users\u0026amp;#39; route choice behavior. However, few empirical studies have been devoted to showing the effectiveness of this approach in improving the accuracy of the underlying passenger flow estimation process. In this research, a passenger classification scheme is proposed on the basis of a dataset from a large stated preference survey conducted in the City of Beijing, China. Separate generalized cost functions are calibrated for different classes of subway users in Beijing and applied in a multi-class transit assignment model for estimating passenger flows over a subway network. The case study has shown that the proposed multi-class approach resulted in significantly improved estimation results with an average estimation error of less than 15% on the transfer flows as compared with 30% for the single class model. Copyright © 2015 John Wiley \u0026amp;amp; Sons, Ltd.","internal_url":"https://www.academia.edu/75065088/A_multi_class_transit_assignment_model_for_estimating_transit_passenger_flows_a_case_study_of_Beijing_subway_network","translated_internal_url":"","created_at":"2022-03-31T05:30:33.987-07:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":168547610,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[],"slug":"A_multi_class_transit_assignment_model_for_estimating_transit_passenger_flows_a_case_study_of_Beijing_subway_network","translated_slug":"","page_count":null,"language":"en","content_type":"Work","owner":{"id":168547610,"first_name":"Liping","middle_initials":null,"last_name":"Fu","page_name":"FuLiping","domain_name":"independent","created_at":"2020-09-01T07:37:24.003-07:00","display_name":"Liping Fu","url":"https://independent.academia.edu/FuLiping"},"attachments":[],"research_interests":[{"id":73,"name":"Civil Engineering","url":"https://www.academia.edu/Documents/in/Civil_Engineering"},{"id":422,"name":"Computer Science","url":"https://www.academia.edu/Documents/in/Computer_Science"},{"id":199372,"name":"Metro","url":"https://www.academia.edu/Documents/in/Metro"}],"urls":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="75065087"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/75065087/Evaluation_of_alternative_criteria_for_determining_the_optimal_location_of_RWIS_stations"><img alt="Research paper thumbnail of Evaluation of alternative criteria for determining the optimal location of RWIS stations" class="work-thumbnail" src="https://attachments.academia-assets.com/83485136/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/75065087/Evaluation_of_alternative_criteria_for_determining_the_optimal_location_of_RWIS_stations">Evaluation of alternative criteria for determining the optimal location of RWIS stations</a></div><div class="wp-workCard_item"><span>Journal of Modern Transportation</span><span>, 2013</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="0c94c78366e276eb0016198aad8bb6a7" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":83485136,"asset_id":75065087,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/83485136/download_file?st=MTczMjc4NzMwOCw4LjIyMi4yMDguMTQ2&s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="75065087"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="75065087"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 75065087; 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In the proposed methodology, the region is divided into a grid of equal-sized zones which are considered as the minimum spatial unit for allocating a candidate set of RWIS stations. These zones are ranked according to a set of pre-specified criteria that reflect the needs for, and potential benefits from, real-time road weather information, including road surface temperature variability, precipitation, network traffic, and collision patterns. A case study based on the existing RWIS network in the province of Ontario was conducted to illustrate the major features of the proposed method and evaluate the implications of alternative location selection criteria. The findings of the study suggest that it is feasible to develop a systematic process for locating RWIS stations using an integrated location criterion to capture multiple factors being considered in practice. 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="75065086"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/75065086/Deicing_Performance_of_Road_Salt"><img alt="Research paper thumbnail of Deicing Performance of Road Salt" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/75065086/Deicing_Performance_of_Road_Salt">Deicing Performance of Road Salt</a></div><div class="wp-workCard_item"><span>Transportation Research Record: Journal of the Transportation Research Board</span><span>, 2014</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">This paper describes the results of a field study designed to quantify the effects of various fac...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">This paper describes the results of a field study designed to quantify the effects of various factors on the snow-melting performance of salt. Many tests were conducted in a realistic environment over two winter seasons, covering more than 70 snow events, with temperatures ranging from −14°C to 3°C and snowfalls ranging from ∼0.2 to 21.0 cm. For each snow event, salts were applied to a set of test sections with specific application rates, and time series performance; condition data such as snow coverage or bare pavement status, friction, pavement and air temperature, sky view, and humidity were collected. An exploratory data analysis was performed to identify the key factors influencing the snow-melting performance of salt, such as application rate, temperature, and snow amount. A multiple linear regression model was calibrated for the relationship between the key snow-melting performance indicators: bare pavement regain time and various influencing factors. The calibrated model was...</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="75065086"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="75065086"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 75065086; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=75065086]").text(description); $(".js-view-count[data-work-id=75065086]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 75065086; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='75065086']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 75065086, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=75065086]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":75065086,"title":"Deicing Performance of Road Salt","translated_title":"","metadata":{"abstract":"This paper describes the results of a field study designed to quantify the effects of various factors on the snow-melting performance of salt. 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The calibrated model was...","publisher":"SAGE Publications","publication_date":{"day":null,"month":null,"year":2014,"errors":{}},"publication_name":"Transportation Research Record: Journal of the Transportation Research Board"},"translated_abstract":"This paper describes the results of a field study designed to quantify the effects of various factors on the snow-melting performance of salt. Many tests were conducted in a realistic environment over two winter seasons, covering more than 70 snow events, with temperatures ranging from −14°C to 3°C and snowfalls ranging from ∼0.2 to 21.0 cm. For each snow event, salts were applied to a set of test sections with specific application rates, and time series performance; condition data such as snow coverage or bare pavement status, friction, pavement and air temperature, sky view, and humidity were collected. 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> </div><div class="profile--tab_content_container js-tab-pane tab-pane" data-section-id="11616704" id="papers"><div class="js-work-strip profile--work_container" data-work-id="82889811"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/82889811/Vehicular_Person_and_Pedestrian_Delays_at_Signalised_Intersections"><img alt="Research paper thumbnail of Vehicular, Person and Pedestrian Delays at Signalised Intersections" class="work-thumbnail" src="https://attachments.academia-assets.com/88441159/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/82889811/Vehicular_Person_and_Pedestrian_Delays_at_Signalised_Intersections">Vehicular, Person and Pedestrian Delays at Signalised Intersections</a></div><div class="wp-workCard_item"><span>IFAC Proceedings Volumes</span><span>, 1997</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="6be68d9b487b96380520be7dc637fbdc" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":88441159,"asset_id":82889811,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/88441159/download_file?st=MTczMjc4NzMwOCw4LjIyMi4yMDguMTQ2&s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="82889811"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="82889811"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 82889811; 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="82889809"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/82889809/Location_Optimization_of_Road_Weather_Information_System_RWIS_Network_Considering_the_Needs_of_Winter_Road_Maintenance_and_the_Traveling_Public"><img alt="Research paper thumbnail of Location Optimization of Road Weather Information System (RWIS) Network Considering the Needs of Winter Road Maintenance and the Traveling Public" class="work-thumbnail" src="https://attachments.academia-assets.com/88441158/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/82889809/Location_Optimization_of_Road_Weather_Information_System_RWIS_Network_Considering_the_Needs_of_Winter_Road_Maintenance_and_the_Traveling_Public">Location Optimization of Road Weather Information System (RWIS) Network Considering the Needs of Winter Road Maintenance and the Traveling Public</a></div><div class="wp-workCard_item"><span>Computer-Aided Civil and Infrastructure Engineering</span><span>, 2016</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="f98b5d6a0cf9270538b6d56d204b0fe6" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":88441158,"asset_id":82889809,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/88441158/download_file?st=MTczMjc4NzMwOCw4LjIyMi4yMDguMTQ2&s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="82889809"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="82889809"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 82889809; 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="82889807"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/82889807/Developing_Safety_Performance_Functions_for_Railway_Grade_Crossings_A_Case_Study_of_Canada"><img alt="Research paper thumbnail of Developing Safety Performance Functions for Railway Grade Crossings: A Case Study of Canada" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/82889807/Developing_Safety_Performance_Functions_for_Railway_Grade_Crossings_A_Case_Study_of_Canada">Developing Safety Performance Functions for Railway Grade Crossings: A Case Study of Canada</a></div><div class="wp-workCard_item"><span>2015 Joint Rail Conference</span><span>, 2015</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Although accident frequencies at railway grade crossings have shown a decreasing trend over the l...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Although accident frequencies at railway grade crossings have shown a decreasing trend over the last two decades (partly due to implemented safety improvements and technological advances), safety at grade crossings is still a major concern since crossing accidents are usually associated with devastating consequences. This paper investigates the effect of various site attributes on railway crossing safety outcomes using recent Canada wide data from a 6-year period (2008–2013). The new data sets allow adjusting previous accident models according to latest circumstances (e.g., vehicles’ improved safety features) affecting safety dynamics at crossings. Employing Bayesian hierarchical models including the non-conventional Poisson-Weibull model, different safety performance functions were separately developed for crossings with the following major warning systems: (1) flashing light and bell (FLB), (2) flashing light, bell, and gate (FLBG), (3) standard reflectorized crossing sign (SRCS), and (4) standard reflectorized crossing sign and stop sign (SRCS &amp; STOP). Among other findings, the results indicated that traffic exposure (product of train and vehicle), number of lanes, whistle prohibition, train speed, and road speed were the most important factors affecting accident frequencies at Canadian railway crossings. It should be also noted that safety performance functions vary, in terms of independent variables and their associated coefficients, between the aforementioned warning devices.Copyright © 2015 by ASME</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="82889807"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="82889807"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 82889807; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=82889807]").text(description); $(".js-view-count[data-work-id=82889807]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 82889807; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='82889807']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 82889807, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=82889807]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":82889807,"title":"Developing Safety Performance Functions for Railway Grade Crossings: A Case Study of Canada","translated_title":"","metadata":{"abstract":"Although accident frequencies at railway grade crossings have shown a decreasing trend over the last two decades (partly due to implemented safety improvements and technological advances), safety at grade crossings is still a major concern since crossing accidents are usually associated with devastating consequences. 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Among other findings, the results indicated that traffic exposure (product of train and vehicle), number of lanes, whistle prohibition, train speed, and road speed were the most important factors affecting accident frequencies at Canadian railway crossings. It should be also noted that safety performance functions vary, in terms of independent variables and their associated coefficients, between the aforementioned warning devices.Copyright © 2015 by ASME","publication_date":{"day":null,"month":null,"year":2015,"errors":{}},"publication_name":"2015 Joint Rail Conference"},"translated_abstract":"Although accident frequencies at railway grade crossings have shown a decreasing trend over the last two decades (partly due to implemented safety improvements and technological advances), safety at grade crossings is still a major concern since crossing accidents are usually associated with devastating consequences. 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Among other findings, the results indicated that traffic exposure (product of train and vehicle), number of lanes, whistle prohibition, train speed, and road speed were the most important factors affecting accident frequencies at Canadian railway crossings. 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Specifically, this paper presents several sustainability measures of performance and presents a framework within which these indicators can be used to evaluate potential transportation projects. 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="82889803"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/82889803/Geographic_Information_System_Based_Integrated_Model_for_Analysis_and_Prediction_of_Road_Accidents"><img alt="Research paper thumbnail of Geographic Information System—Based Integrated Model for Analysis and Prediction of Road Accidents" class="work-thumbnail" src="https://attachments.academia-assets.com/88441153/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/82889803/Geographic_Information_System_Based_Integrated_Model_for_Analysis_and_Prediction_of_Road_Accidents">Geographic Information System—Based Integrated Model for Analysis and Prediction of Road Accidents</a></div><div class="wp-workCard_item"><span>Transportation Research Record</span><span>, 2001</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="5e58c04968e3185ff1d63f20cb6b3dff" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":88441153,"asset_id":82889803,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/88441153/download_file?st=MTczMjc4NzMwOCw4LjIyMi4yMDguMTQ2&s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="82889803"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="82889803"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 82889803; 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="82889797"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/82889797/Design_and_Implementation_of_Bus_Holding_Control_Strategies_with_Real_Time_Information"><img alt="Research paper thumbnail of Design and Implementation of Bus–Holding Control Strategies with Real-Time Information" class="work-thumbnail" src="https://attachments.academia-assets.com/88441151/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/82889797/Design_and_Implementation_of_Bus_Holding_Control_Strategies_with_Real_Time_Information">Design and Implementation of Bus–Holding Control Strategies with Real-Time Information</a></div><div class="wp-workCard_item"><span>Transportation Research Record: Journal of the Transportation Research Board</span><span>, 2002</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">A systematic study is described to address various design and implementation issues associated wi...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">A systematic study is described to address various design and implementation issues associated with the problem of real-time bus holding control. Two holding control models have been investigated. The first model follows the conventional threshold-based control logic that determines holding times on the basis of headway to the preceding bus. The second model makes use of both preceding and following headways in identifying optimal control decisions with the assumption that real-time bus location information is available for estimating future bus arrivals at the control stop. An extensive simulation analysis is performed using a real-fife bus route operated by the Grand River Transit of the region of Waterloo, Ontario. The simulation results have substantiated several conclusions and yielded new findings on various issues such as where to set the control point, how many control points should be used, what is the optimal control strength, and what is the value of real-time location in...</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="81cb928c7af864e065bc3790aaccbf84" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":88441151,"asset_id":82889797,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/88441151/download_file?st=MTczMjc4NzMwOCw4LjIyMi4yMDguMTQ2&s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="82889797"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="82889797"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 82889797; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=82889797]").text(description); $(".js-view-count[data-work-id=82889797]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 82889797; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='82889797']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 82889797, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "81cb928c7af864e065bc3790aaccbf84" } } $('.js-work-strip[data-work-id=82889797]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":82889797,"title":"Design and Implementation of Bus–Holding Control Strategies with Real-Time Information","translated_title":"","metadata":{"abstract":"A systematic study is described to address various design and implementation issues associated with the problem of real-time bus holding control. 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="82889759"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/82889759/An_Efficient_Optimization_Approach_to_Real_Time_Coordinated_and_Integrated_Freeway_Traffic_Control"><img alt="Research paper thumbnail of An Efficient Optimization Approach to Real-Time Coordinated and Integrated Freeway Traffic Control" class="work-thumbnail" src="https://attachments.academia-assets.com/88441144/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/82889759/An_Efficient_Optimization_Approach_to_Real_Time_Coordinated_and_Integrated_Freeway_Traffic_Control">An Efficient Optimization Approach to Real-Time Coordinated and Integrated Freeway Traffic Control</a></div><div class="wp-workCard_item"><span>IEEE Transactions on Intelligent Transportation Systems</span><span>, 2010</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="c36b3f932617f19584f46be3f79d716e" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":88441144,"asset_id":82889759,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/88441144/download_file?st=MTczMjc4NzMwOCw4LjIyMi4yMDguMTQ2&s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="82889759"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="82889759"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 82889759; 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One promising ap-6 proach to this problem is casting the underlying dynamic control 7 problem in a model predictive framework. The challenge is that 8 the resulting optimization problem is computationally intractable 9 for online applications in a network with a large number of 10 controllers. In this paper, a game-theoretic approach with distrib-11 uted controllers is proposed to address the foregoing issue. The 12 efficiency of the proposed method is tested for a coordinated ramp 13 metering and variable-speed limit control applied to a stretch of 14 freeway network. The parallel nature of the optimization algo-15 rithm makes it suitable for solving large-scale problems with high 16 accuracy. The speed and accuracy of the proposed solution ap-17 proach are examined and compared with that of the conventional 18 optimization method in a case study to demonstrate its superior 19 performance. 20 Index Terms-Distributed controllers, game theory, model pre-21 dictive control (MPC), parallel optimization, ramp metering, 22 speed limit control. 23 I. INTRODUCTION 24 S EVERAL methods have been developed to improve the 25 performance of freeway networks. Among them, control 26 strategies such as ramp metering, speed limits, and route rec-27 ommendation are recognized as the most effective ways to 28 relieve the freeway traffic congestion. Furthermore, the latest 29 advances in computers and communication technologies have 30 made it feasible to implement network-wide multiple traffic 31 control systems, as opposed to single local control schemes.","publication_date":{"day":null,"month":null,"year":2010,"errors":{}},"publication_name":"IEEE Transactions on Intelligent Transportation 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class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/82889719/Reducing_the_threat_of_in_transit_derailments_involving_dangerous_goods_through_effective_placement_along_the_train_consist">Reducing the threat of in-transit derailments involving dangerous goods through effective placement along the train consist</a></div><div class="wp-workCard_item"><span>Accident Analysis &amp; Prevention</span><span>, 2011</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="cf79678d97f7cf5fd84c2dce8ab649a3" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":88441103,"asset_id":82889719,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/88441103/download_file?st=MTczMjc4NzMwOCw4LjIyMi4yMDguMTQ2&s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="82889719"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="82889719"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 82889719; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=82889719]").text(description); $(".js-view-count[data-work-id=82889719]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 82889719; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='82889719']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 82889719, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "cf79678d97f7cf5fd84c2dce8ab649a3" } } $('.js-work-strip[data-work-id=82889719]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":82889719,"title":"Reducing the threat of in-transit derailments involving dangerous goods through effective placement along the train consist","translated_title":"","metadata":{"publisher":"Elsevier BV","grobid_abstract":"Train derailments are important safety concerns, and they become increasingly so when dangerous goods (DG) are involved. One way to reduce the risk of DG derailments is through effective DG railway car placement along the train consist. This paper investigates the relationship between DG railway car placement and derailment for different route attributes and DG shipments. A model is presented for estimating the probability of derailment by position, based on the estimated point of derailment (POD) and the number of cars derailing. A DG placement model that considers in-transit derailment risk is shown to provide a sound scientific basis for effective DG marshalling in conventional rail hump yard operations.","publication_date":{"day":null,"month":null,"year":2011,"errors":{}},"publication_name":"Accident Analysis \u0026amp; 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data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/82889673/Development_of_a_global_road_safety_performance_function_using_deep_neural_networks"><img alt="Research paper thumbnail of Development of a global road safety performance function using deep neural networks" class="work-thumbnail" src="https://attachments.academia-assets.com/88441063/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/82889673/Development_of_a_global_road_safety_performance_function_using_deep_neural_networks">Development of a global road safety performance function using deep neural networks</a></div><div class="wp-workCard_item"><span>International Journal of Transportation Science and Technology</span><span>, 2017</span></div><div class="wp-workCard_item 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class="work-thumbnail" src="https://attachments.academia-assets.com/82984946/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/75065094/Potential_Effects_of_Automatic_Vehicle_Location_and_Computer_Aided_Dispatch_Technology_on_Paratransit_Performance_A_Simulation_Study">Potential Effects of Automatic Vehicle Location and Computer-Aided Dispatch Technology on Paratransit Performance: A Simulation Study</a></div><div class="wp-workCard_item"><span>Transportation Research Record: Journal of the Transportation Research Board</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Automatic vehicle location (AVL) and computer-aided dispatch (CAD) systems have afforded a unique...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Automatic vehicle location (AVL) and computer-aided dispatch (CAD) systems have afforded a unique opportunity for public transit agencies to integrate these technologies in their paratransit systems for improved productivity and reliability. This opportunity has also prompted widespread interest in quantifying the benefits that can be attained from such technological enhancement. This research assesses the potential effects of AVL and CAD on the productivity and service reliability of a paratransit system. A simulation model that can realistically model AVL and CAD functionality is used in the investigation. Many cases representing variations in operating environment, such as service area, demand intensity, and proportion of real-time demand trips, are simulated for a sensitivity analysis under three assumed operational improvements—en route diversion, dwell time reduction, and periodic reoptimization. The results indicate that although AVL and CAD effectiveness varies from case to ...</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="2934aeab934141d49083c5701c3dae2a" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":82984946,"asset_id":75065094,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/82984946/download_file?st=MTczMjc4NzMwOCw4LjIyMi4yMDguMTQ2&s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="75065094"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="75065094"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 75065094; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=75065094]").text(description); $(".js-view-count[data-work-id=75065094]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 75065094; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='75065094']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 75065094, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "2934aeab934141d49083c5701c3dae2a" } } $('.js-work-strip[data-work-id=75065094]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":75065094,"title":"Potential Effects of Automatic Vehicle Location and Computer-Aided Dispatch Technology on Paratransit Performance: A Simulation Study","translated_title":"","metadata":{"abstract":"Automatic vehicle location (AVL) and computer-aided dispatch (CAD) systems have afforded a unique opportunity for public transit agencies to integrate these technologies in their paratransit systems for improved productivity and reliability. 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src="https://attachments.academia-assets.com/82984945/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/75065092/Planning_and_Design_of_Flex_Route_Transit_Services">Planning and Design of Flex-Route Transit Services</a></div><div class="wp-workCard_item"><span>Transportation Research Record: Journal of the Transportation Research Board</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">A theoretical investigation is presented of various issues involved in the planning and design of...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">A theoretical investigation is presented of various issues involved in the planning and design of flex-route transit services. An analytical model is proposed for an idealized operating environment with the objective of determining the optimal slack time that should be allocated to a flexroute segment. The optimization objective is defined to minimize total operator and user cost, which enables a systematic examination of complex interactions among the system parameters. An equation is derived for the relationship between the number of feasible deviations and various system parameters such as slack time, zone size, and dwell time. Subsequent analysis shows that the analytical model is elaborate enough to provide substantial insights into various issues that may arise in designing a flex-route service. A simulation analysis is conducted to validate some of the conclusions drawn from the analytical model and to further analyze the implications of stochastic variation in passenger demand.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="bee915ec09e1159eef2e02cc37981c7b" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":82984945,"asset_id":75065092,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/82984945/download_file?st=MTczMjc4NzMwOCw4LjIyMi4yMDguMTQ2&s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="75065092"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="75065092"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 75065092; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=75065092]").text(description); $(".js-view-count[data-work-id=75065092]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 75065092; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='75065092']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 75065092, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "bee915ec09e1159eef2e02cc37981c7b" } } $('.js-work-strip[data-work-id=75065092]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":75065092,"title":"Planning and Design of Flex-Route Transit Services","translated_title":"","metadata":{"abstract":"A theoretical investigation is presented of various issues involved in the planning and design of flex-route transit services. 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="75065091"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/75065091/Road_weather_information_system_stations_where_and_how_many_to_install_a_cost_benefit_analysis_approach"><img alt="Research paper thumbnail of Road weather information system stations — where and how many to install: a cost benefit analysis approach" class="work-thumbnail" src="https://attachments.academia-assets.com/83485098/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/75065091/Road_weather_information_system_stations_where_and_how_many_to_install_a_cost_benefit_analysis_approach">Road weather information system stations — where and how many to install: a cost benefit analysis approach</a></div><div class="wp-workCard_item"><span>Canadian Journal of Civil Engineering</span><span>, 2015</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">This paper presents a cost–benefit based approach to the problem of finding the optimal location ...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">This paper presents a cost–benefit based approach to the problem of finding the optimal location and density of road weather information system (RWIS) stations over a regional road network. The novelty of the proposed method lies in the models that can be used to estimate the benefits of RWIS information, including reduced maintenance costs and collisions, thus determining the optimal number and location of a RWIS network. A case study based on the existing RWIS network in Northern Minnesota in the US is used to show the application of the proposed approach. Linear regression models are developed for the annual maintenance costs and the expected number of collisions that could occur on two types of highways delineated by the existence of a RWIS station nearby. The calibrated models are then applied to individual highway segments defined on the basis of a uniform grid system to determine the expected benefit of having a RWIS station installed. These benefits along with RWIS installat...</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="2f311a37e0a9378d0cc23c1d273ceb44" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":83485098,"asset_id":75065091,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/83485098/download_file?st=MTczMjc4NzMwOCw4LjIyMi4yMDguMTQ2&s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="75065091"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="75065091"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 75065091; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=75065091]").text(description); $(".js-view-count[data-work-id=75065091]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 75065091; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='75065091']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 75065091, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "2f311a37e0a9378d0cc23c1d273ceb44" } } $('.js-work-strip[data-work-id=75065091]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":75065091,"title":"Road weather information system stations — where and how many to install: a cost benefit analysis approach","translated_title":"","metadata":{"abstract":"This paper presents a cost–benefit based approach to the problem of finding the optimal location and density of road weather information system (RWIS) stations over a regional road network. 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These benefits along with RWIS installat...","publisher":"Canadian Science Publishing","publication_date":{"day":null,"month":null,"year":2015,"errors":{}},"publication_name":"Canadian Journal of Civil Engineering"},"translated_abstract":"This paper presents a cost–benefit based approach to the problem of finding the optimal location and density of road weather information system (RWIS) stations over a regional road network. The novelty of the proposed method lies in the models that can be used to estimate the benefits of RWIS information, including reduced maintenance costs and collisions, thus determining the optimal number and location of a RWIS network. A case study based on the existing RWIS network in Northern Minnesota in the US is used to show the application of the proposed approach. Linear regression models are developed for the annual maintenance costs and the expected number of collisions that could occur on two types of highways delineated by the existence of a RWIS station nearby. The calibrated models are then applied to individual highway segments defined on the basis of a uniform grid system to determine the expected benefit of having a RWIS station installed. 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="75065090"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/75065090/Analyzing_injury_severity_factors_at_highway_railway_grade_crossing_accidents_involving_vulnerable_road_users_A_comparative_study"><img alt="Research paper thumbnail of Analyzing injury severity factors at highway railway grade crossing accidents involving vulnerable road users: A comparative study" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" rel="nofollow" href="https://www.academia.edu/75065090/Analyzing_injury_severity_factors_at_highway_railway_grade_crossing_accidents_involving_vulnerable_road_users_A_comparative_study">Analyzing injury severity factors at highway railway grade crossing accidents involving vulnerable road users: A comparative study</a></div><div class="wp-workCard_item"><span>Traffic Injury Prevention</span><span>, 2016</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">The main objective of this study is to identify the main factors associated with injury severity ...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">The main objective of this study is to identify the main factors associated with injury severity of the vulnerable road user (VRU) involved in the accidents at highway railroad grade crossings (HRGC) using data mining techniques. This paper applies Ordered Probit model, Association Rules and Classification-Regression Tree (CART) algorithms to the U.S. Federal Railroad Administration (FRA) HRGC accident database for the period of 2007-2013, to identify VRU injury severity factors at HRGCs. The results show that train speed is the key factor influencing the injury severity. Further analysis illustrated that the presence of an illumination does not reduce the severity of accidents for high speed train. Also there is a greater propensity towards fatal accidents for elderly road users compared to the younger individuals. Interestingly, during the night, injury accident involving a female road user is more sever in comparison to a male. The Ordered Probit Model was the primary technique, and CART and Association Rules act as the supporter and identifier of interactions between variables. All of the three algorithms results, consistently show that the most influential accident factors such as the train speed, VRU age and gender. The findings of this research could be applied for identifying high-risk hotspots and developing cost-effective countermeasures targeting VRUs at HRGC.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="75065090"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="75065090"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 75065090; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=75065090]").text(description); $(".js-view-count[data-work-id=75065090]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 75065090; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='75065090']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 75065090, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=75065090]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":75065090,"title":"Analyzing injury severity factors at highway railway grade crossing accidents involving vulnerable road users: A comparative study","translated_title":"","metadata":{"abstract":"The main objective of this study is to identify the main factors associated with injury severity of the vulnerable road user (VRU) involved in the accidents at highway railroad grade crossings (HRGC) using data mining techniques. This paper applies Ordered Probit model, Association Rules and Classification-Regression Tree (CART) algorithms to the U.S. Federal Railroad Administration (FRA) HRGC accident database for the period of 2007-2013, to identify VRU injury severity factors at HRGCs. The results show that train speed is the key factor influencing the injury severity. Further analysis illustrated that the presence of an illumination does not reduce the severity of accidents for high speed train. Also there is a greater propensity towards fatal accidents for elderly road users compared to the younger individuals. Interestingly, during the night, injury accident involving a female road user is more sever in comparison to a male. The Ordered Probit Model was the primary technique, and CART and Association Rules act as the supporter and identifier of interactions between variables. All of the three algorithms results, consistently show that the most influential accident factors such as the train speed, VRU age and gender. The findings of this research could be applied for identifying high-risk hotspots and developing cost-effective countermeasures targeting VRUs at HRGC.","publisher":"Informa UK Limited","publication_date":{"day":null,"month":null,"year":2016,"errors":{}},"publication_name":"Traffic Injury Prevention"},"translated_abstract":"The main objective of this study is to identify the main factors associated with injury severity of the vulnerable road user (VRU) involved in the accidents at highway railroad grade crossings (HRGC) using data mining techniques. This paper applies Ordered Probit model, Association Rules and Classification-Regression Tree (CART) algorithms to the U.S. Federal Railroad Administration (FRA) HRGC accident database for the period of 2007-2013, to identify VRU injury severity factors at HRGCs. The results show that train speed is the key factor influencing the injury severity. Further analysis illustrated that the presence of an illumination does not reduce the severity of accidents for high speed train. Also there is a greater propensity towards fatal accidents for elderly road users compared to the younger individuals. Interestingly, during the night, injury accident involving a female road user is more sever in comparison to a male. The Ordered Probit Model was the primary technique, and CART and Association Rules act as the supporter and identifier of interactions between variables. All of the three algorithms results, consistently show that the most influential accident factors such as the train speed, VRU age and gender. The findings of this research could be applied for identifying high-risk hotspots and developing cost-effective countermeasures targeting VRUs at HRGC.","internal_url":"https://www.academia.edu/75065090/Analyzing_injury_severity_factors_at_highway_railway_grade_crossing_accidents_involving_vulnerable_road_users_A_comparative_study","translated_internal_url":"","created_at":"2022-03-31T05:30:34.219-07:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":168547610,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[],"slug":"Analyzing_injury_severity_factors_at_highway_railway_grade_crossing_accidents_involving_vulnerable_road_users_A_comparative_study","translated_slug":"","page_count":null,"language":"en","content_type":"Work","owner":{"id":168547610,"first_name":"Liping","middle_initials":null,"last_name":"Fu","page_name":"FuLiping","domain_name":"independent","created_at":"2020-09-01T07:37:24.003-07:00","display_name":"Liping Fu","url":"https://independent.academia.edu/FuLiping"},"attachments":[],"research_interests":[{"id":48,"name":"Engineering","url":"https://www.academia.edu/Documents/in/Engineering"},{"id":221,"name":"Psychology","url":"https://www.academia.edu/Documents/in/Psychology"},{"id":2009,"name":"Data Mining","url":"https://www.academia.edu/Documents/in/Data_Mining"},{"id":26327,"name":"Medicine","url":"https://www.academia.edu/Documents/in/Medicine"},{"id":47297,"name":"Automotive Engineering","url":"https://www.academia.edu/Documents/in/Automotive_Engineering"},{"id":98134,"name":"United States","url":"https://www.academia.edu/Documents/in/United_States"},{"id":192721,"name":"Risk factors","url":"https://www.academia.edu/Documents/in/Risk_factors"},{"id":226488,"name":"Vulnerable Populations","url":"https://www.academia.edu/Documents/in/Vulnerable_Populations"},{"id":289271,"name":"Aged","url":"https://www.academia.edu/Documents/in/Aged"},{"id":434017,"name":"Railroads","url":"https://www.academia.edu/Documents/in/Railroads"},{"id":620049,"name":"Risk Factors","url":"https://www.academia.edu/Documents/in/Risk_Factors-1"},{"id":1031658,"name":"Wounds and Injuries","url":"https://www.academia.edu/Documents/in/Wounds_and_Injuries"},{"id":2467531,"name":"Trauma Severity Indices","url":"https://www.academia.edu/Documents/in/Trauma_Severity_Indices"},{"id":4002452,"name":"Accidents Traffic","url":"https://www.academia.edu/Documents/in/Accidents_Traffic"}],"urls":[{"id":18979419,"url":"https://www.tandfonline.com/doi/pdf/10.1080/15389588.2016.1151011"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="75065089"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/75065089/Road_surface_condition_classification_method_and_system"><img alt="Research paper thumbnail of Road surface condition classification method and system" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" rel="nofollow" href="https://www.academia.edu/75065089/Road_surface_condition_classification_method_and_system">Road surface condition classification method and system</a></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="75065089"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="75065089"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 75065089; 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="75065088"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/75065088/A_multi_class_transit_assignment_model_for_estimating_transit_passenger_flows_a_case_study_of_Beijing_subway_network"><img alt="Research paper thumbnail of A multi-class transit assignment model for estimating transit passenger flows-a case study of Beijing subway network" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/75065088/A_multi_class_transit_assignment_model_for_estimating_transit_passenger_flows_a_case_study_of_Beijing_subway_network">A multi-class transit assignment model for estimating transit passenger flows-a case study of Beijing subway network</a></div><div class="wp-workCard_item"><span>Journal of Advanced Transportation</span><span>, 2015</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">ABSTRACT This paper describes a case study comparing a multi-class transit assignment model with ...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">ABSTRACT This paper describes a case study comparing a multi-class transit assignment model with its single class counterpart for estimating the passenger flows of the Beijing subway network—one of the largest railway transit networks in the world. Multi-class traffic assignment has been widely considered as a theoretically sound approach to capture the inherent variation in users&amp;#39; route choice behavior. However, few empirical studies have been devoted to showing the effectiveness of this approach in improving the accuracy of the underlying passenger flow estimation process. In this research, a passenger classification scheme is proposed on the basis of a dataset from a large stated preference survey conducted in the City of Beijing, China. Separate generalized cost functions are calibrated for different classes of subway users in Beijing and applied in a multi-class transit assignment model for estimating passenger flows over a subway network. The case study has shown that the proposed multi-class approach resulted in significantly improved estimation results with an average estimation error of less than 15% on the transfer flows as compared with 30% for the single class model. Copyright © 2015 John Wiley &amp;amp; Sons, Ltd.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="75065088"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="75065088"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 75065088; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=75065088]").text(description); $(".js-view-count[data-work-id=75065088]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 75065088; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='75065088']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 75065088, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=75065088]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":75065088,"title":"A multi-class transit assignment model for estimating transit passenger flows-a case study of Beijing subway network","translated_title":"","metadata":{"abstract":"ABSTRACT This paper describes a case study comparing a multi-class transit assignment model with its single class counterpart for estimating the passenger flows of the Beijing subway network—one of the largest railway transit networks in the world. Multi-class traffic assignment has been widely considered as a theoretically sound approach to capture the inherent variation in users\u0026amp;#39; route choice behavior. However, few empirical studies have been devoted to showing the effectiveness of this approach in improving the accuracy of the underlying passenger flow estimation process. In this research, a passenger classification scheme is proposed on the basis of a dataset from a large stated preference survey conducted in the City of Beijing, China. Separate generalized cost functions are calibrated for different classes of subway users in Beijing and applied in a multi-class transit assignment model for estimating passenger flows over a subway network. The case study has shown that the proposed multi-class approach resulted in significantly improved estimation results with an average estimation error of less than 15% on the transfer flows as compared with 30% for the single class model. Copyright © 2015 John Wiley \u0026amp;amp; Sons, Ltd.","publisher":"Wiley-Blackwell","publication_date":{"day":null,"month":null,"year":2015,"errors":{}},"publication_name":"Journal of Advanced Transportation"},"translated_abstract":"ABSTRACT This paper describes a case study comparing a multi-class transit assignment model with its single class counterpart for estimating the passenger flows of the Beijing subway network—one of the largest railway transit networks in the world. Multi-class traffic assignment has been widely considered as a theoretically sound approach to capture the inherent variation in users\u0026amp;#39; route choice behavior. However, few empirical studies have been devoted to showing the effectiveness of this approach in improving the accuracy of the underlying passenger flow estimation process. In this research, a passenger classification scheme is proposed on the basis of a dataset from a large stated preference survey conducted in the City of Beijing, China. Separate generalized cost functions are calibrated for different classes of subway users in Beijing and applied in a multi-class transit assignment model for estimating passenger flows over a subway network. The case study has shown that the proposed multi-class approach resulted in significantly improved estimation results with an average estimation error of less than 15% on the transfer flows as compared with 30% for the single class model. Copyright © 2015 John Wiley \u0026amp;amp; Sons, Ltd.","internal_url":"https://www.academia.edu/75065088/A_multi_class_transit_assignment_model_for_estimating_transit_passenger_flows_a_case_study_of_Beijing_subway_network","translated_internal_url":"","created_at":"2022-03-31T05:30:33.987-07:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":168547610,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[],"slug":"A_multi_class_transit_assignment_model_for_estimating_transit_passenger_flows_a_case_study_of_Beijing_subway_network","translated_slug":"","page_count":null,"language":"en","content_type":"Work","owner":{"id":168547610,"first_name":"Liping","middle_initials":null,"last_name":"Fu","page_name":"FuLiping","domain_name":"independent","created_at":"2020-09-01T07:37:24.003-07:00","display_name":"Liping Fu","url":"https://independent.academia.edu/FuLiping"},"attachments":[],"research_interests":[{"id":73,"name":"Civil Engineering","url":"https://www.academia.edu/Documents/in/Civil_Engineering"},{"id":422,"name":"Computer Science","url":"https://www.academia.edu/Documents/in/Computer_Science"},{"id":199372,"name":"Metro","url":"https://www.academia.edu/Documents/in/Metro"}],"urls":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="75065087"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/75065087/Evaluation_of_alternative_criteria_for_determining_the_optimal_location_of_RWIS_stations"><img alt="Research paper thumbnail of Evaluation of alternative criteria for determining the optimal location of RWIS stations" class="work-thumbnail" src="https://attachments.academia-assets.com/83485136/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/75065087/Evaluation_of_alternative_criteria_for_determining_the_optimal_location_of_RWIS_stations">Evaluation of alternative criteria for determining the optimal location of RWIS stations</a></div><div class="wp-workCard_item"><span>Journal of Modern Transportation</span><span>, 2013</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="0c94c78366e276eb0016198aad8bb6a7" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":83485136,"asset_id":75065087,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/83485136/download_file?st=MTczMjc4NzMwOCw4LjIyMi4yMDguMTQ2&s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="75065087"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="75065087"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 75065087; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=75065087]").text(description); $(".js-view-count[data-work-id=75065087]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 75065087; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='75065087']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 75065087, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); 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In the proposed methodology, the region is divided into a grid of equal-sized zones which are considered as the minimum spatial unit for allocating a candidate set of RWIS stations. These zones are ranked according to a set of pre-specified criteria that reflect the needs for, and potential benefits from, real-time road weather information, including road surface temperature variability, precipitation, network traffic, and collision patterns. A case study based on the existing RWIS network in the province of Ontario was conducted to illustrate the major features of the proposed method and evaluate the implications of alternative location selection criteria. The findings of the study suggest that it is feasible to develop a systematic process for locating RWIS stations using an integrated location criterion to capture multiple factors being considered in practice. The study has also revealed the need to establish quantitative models for estimating the benefit of real-time information from RWIS stations, which is the foundation of a cost-benefit-based RWIS location optimization model.","publication_date":{"day":null,"month":null,"year":2013,"errors":{}},"publication_name":"Journal of Modern Transportation","grobid_abstract_attachment_id":83485136},"translated_abstract":null,"internal_url":"https://www.academia.edu/75065087/Evaluation_of_alternative_criteria_for_determining_the_optimal_location_of_RWIS_stations","translated_internal_url":"","created_at":"2022-03-31T05:30:33.897-07:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":168547610,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[{"id":83485136,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/83485136/thumbnails/1.jpg","file_name":"Evaluation_of_alternative_criteria_for_d20220408-5055-1hu675d.pdf","download_url":"https://www.academia.edu/attachments/83485136/download_file?st=MTczMjc4NzMwOCw4LjIyMi4yMDguMTQ2&","bulk_download_file_name":"Evaluation_of_alternative_criteria_for_d.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/83485136/Evaluation_of_alternative_criteria_for_d20220408-5055-1hu675d.pdf?1649457170=\u0026response-content-disposition=attachment%3B+filename%3DEvaluation_of_alternative_criteria_for_d.pdf\u0026Expires=1732781801\u0026Signature=Ibi16tz0Cu9VhI9I~~1RyJxCe6CSbcVPw-iU0XQ4JUI1EHmcaC7TcyVyp2r8ASKMH~LLIaqIZABJagak~BNbeRtO2EnittVmObAHav3kblC-8g9DBOFsTSRla5j2aPyzfijdl7enAKbTMxhmX-PX8syxD~Yp6munsPc3DhoevTN~IcvJdNo2J5PIiSII7kPMV3GAfm5-lo9KJBXmAc1zQurfBD9sk56EBrNV-S5Cvgo9gzlL8jZcIGUUfYlEVtkbjVJE-QK5GoP-3lxp1EJUl71qCPdfoCoD3uWWdS98T3-eVh5PB8-343sU7rIj26TrkzjFC2L~XktIoanBCYdR0g__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}],"slug":"Evaluation_of_alternative_criteria_for_determining_the_optimal_location_of_RWIS_stations","translated_slug":"","page_count":11,"language":"en","content_type":"Work","owner":{"id":168547610,"first_name":"Liping","middle_initials":null,"last_name":"Fu","page_name":"FuLiping","domain_name":"independent","created_at":"2020-09-01T07:37:24.003-07:00","display_name":"Liping Fu","url":"https://independent.academia.edu/FuLiping"},"attachments":[{"id":83485136,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/83485136/thumbnails/1.jpg","file_name":"Evaluation_of_alternative_criteria_for_d20220408-5055-1hu675d.pdf","download_url":"https://www.academia.edu/attachments/83485136/download_file?st=MTczMjc4NzMwOCw4LjIyMi4yMDguMTQ2&","bulk_download_file_name":"Evaluation_of_alternative_criteria_for_d.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/83485136/Evaluation_of_alternative_criteria_for_d20220408-5055-1hu675d.pdf?1649457170=\u0026response-content-disposition=attachment%3B+filename%3DEvaluation_of_alternative_criteria_for_d.pdf\u0026Expires=1732781801\u0026Signature=Ibi16tz0Cu9VhI9I~~1RyJxCe6CSbcVPw-iU0XQ4JUI1EHmcaC7TcyVyp2r8ASKMH~LLIaqIZABJagak~BNbeRtO2EnittVmObAHav3kblC-8g9DBOFsTSRla5j2aPyzfijdl7enAKbTMxhmX-PX8syxD~Yp6munsPc3DhoevTN~IcvJdNo2J5PIiSII7kPMV3GAfm5-lo9KJBXmAc1zQurfBD9sk56EBrNV-S5Cvgo9gzlL8jZcIGUUfYlEVtkbjVJE-QK5GoP-3lxp1EJUl71qCPdfoCoD3uWWdS98T3-eVh5PB8-343sU7rIj26TrkzjFC2L~XktIoanBCYdR0g__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}],"research_interests":[],"urls":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="75065086"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/75065086/Deicing_Performance_of_Road_Salt"><img alt="Research paper thumbnail of Deicing Performance of Road Salt" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/75065086/Deicing_Performance_of_Road_Salt">Deicing Performance of Road Salt</a></div><div class="wp-workCard_item"><span>Transportation Research Record: Journal of the Transportation Research Board</span><span>, 2014</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">This paper describes the results of a field study designed to quantify the effects of various fac...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">This paper describes the results of a field study designed to quantify the effects of various factors on the snow-melting performance of salt. Many tests were conducted in a realistic environment over two winter seasons, covering more than 70 snow events, with temperatures ranging from −14°C to 3°C and snowfalls ranging from ∼0.2 to 21.0 cm. For each snow event, salts were applied to a set of test sections with specific application rates, and time series performance; condition data such as snow coverage or bare pavement status, friction, pavement and air temperature, sky view, and humidity were collected. An exploratory data analysis was performed to identify the key factors influencing the snow-melting performance of salt, such as application rate, temperature, and snow amount. A multiple linear regression model was calibrated for the relationship between the key snow-melting performance indicators: bare pavement regain time and various influencing factors. The calibrated model was...</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="75065086"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="75065086"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 75065086; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=75065086]").text(description); $(".js-view-count[data-work-id=75065086]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 75065086; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='75065086']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 75065086, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=75065086]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":75065086,"title":"Deicing Performance of Road Salt","translated_title":"","metadata":{"abstract":"This paper describes the results of a field study designed to quantify the effects of various factors on the snow-melting performance of salt. Many tests were conducted in a realistic environment over two winter seasons, covering more than 70 snow events, with temperatures ranging from −14°C to 3°C and snowfalls ranging from ∼0.2 to 21.0 cm. For each snow event, salts were applied to a set of test sections with specific application rates, and time series performance; condition data such as snow coverage or bare pavement status, friction, pavement and air temperature, sky view, and humidity were collected. An exploratory data analysis was performed to identify the key factors influencing the snow-melting performance of salt, such as application rate, temperature, and snow amount. A multiple linear regression model was calibrated for the relationship between the key snow-melting performance indicators: bare pavement regain time and various influencing factors. The calibrated model was...","publisher":"SAGE Publications","publication_date":{"day":null,"month":null,"year":2014,"errors":{}},"publication_name":"Transportation Research Record: Journal of the Transportation Research Board"},"translated_abstract":"This paper describes the results of a field study designed to quantify the effects of various factors on the snow-melting performance of salt. Many tests were conducted in a realistic environment over two winter seasons, covering more than 70 snow events, with temperatures ranging from −14°C to 3°C and snowfalls ranging from ∼0.2 to 21.0 cm. For each snow event, salts were applied to a set of test sections with specific application rates, and time series performance; condition data such as snow coverage or bare pavement status, friction, pavement and air temperature, sky view, and humidity were collected. An exploratory data analysis was performed to identify the key factors influencing the snow-melting performance of salt, such as application rate, temperature, and snow amount. A multiple linear regression model was calibrated for the relationship between the key snow-melting performance indicators: bare pavement regain time and various influencing factors. 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