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Ridership</title> <meta name="description" content="Search results for: Ridership"> <meta name="keywords" content="Ridership"> <meta name="viewport" content="width=device-width, initial-scale=1, minimum-scale=1, maximum-scale=1, user-scalable=no"> <meta charset="utf-8"> <link href="https://cdn.waset.org/favicon.ico" type="image/x-icon" rel="shortcut icon"> <link href="https://cdn.waset.org/static/plugins/bootstrap-4.2.1/css/bootstrap.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/plugins/fontawesome/css/all.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/css/site.css?v=150220211555" rel="stylesheet"> </head> <body> <header> <div class="container"> <nav class="navbar navbar-expand-lg navbar-light"> <a class="navbar-brand" href="https://waset.org"> <img src="https://cdn.waset.org/static/images/wasetc.png" alt="Open Science Research Excellence" title="Open Science Research Excellence" /> </a> <button class="d-block d-lg-none navbar-toggler ml-auto" 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id="custom-search-input"> <div class="input-group"> <i class="fas fa-search"></i> <input type="text" class="search-query" name="q" placeholder="Author, Title, Abstract, Keywords" value="Ridership"> <input type="submit" class="btn_search" value="Search"> </div> </div> </form> </div> </div> <div class="row mt-3"> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Commenced</strong> in January 2007</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Frequency:</strong> Monthly</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Edition:</strong> International</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Paper Count:</strong> 19</div> </div> </div> </div> <h1 class="mt-3 mb-3 text-center" style="font-size:1.6rem;">Search results for: Ridership</h1> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">19</span> Integrated Mass Rapid Transit (MRT) and Bus System in Singapore: MRT Ridership and the Provision of Feeder Bus Services</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Devansh%20Jain">Devansh Jain</a>, <a href="https://publications.waset.org/abstracts/search?q=Shu%20Ting%20Goh"> Shu Ting Goh</a> </p> <p class="card-text"><strong>Abstract:</strong></p> With the aim of improving the quality of life of people of Singapore with provision of better transport services, Land and Transport Authority Singapore recently published its Master Plan 2013. The major objectives mentioned in the plan were to make a comprehensive public transport network with better quality Mass Rapid Transit, bus services along with cycling and walking. MRT is the backbone of the transport system in Singapore, and to promote and increase the MRT ridership, good accessibility to access the MRT stations is a necessity. The aim of this paper is to investigate the relationship between MRT ridership and the provision of feeder bus services in Singapore planning areas and also to understand the hub and spoke model adopted by Singapore for provision of transport services. The findings of the study will lead to conclusions made from the Regression model developed by the various factors affecting MRT ridership, and hence will benefit to enhance the services provided by the system. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=quality%20of%20life" title="quality of life">quality of life</a>, <a href="https://publications.waset.org/abstracts/search?q=public%20transport" title=" public transport"> public transport</a>, <a href="https://publications.waset.org/abstracts/search?q=mass%20rapid%20transit" title=" mass rapid transit"> mass rapid transit</a>, <a href="https://publications.waset.org/abstracts/search?q=ridership" title=" ridership"> ridership</a> </p> <a href="https://publications.waset.org/abstracts/55438/integrated-mass-rapid-transit-mrt-and-bus-system-in-singapore-mrt-ridership-and-the-provision-of-feeder-bus-services" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/55438.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">247</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">18</span> Predicting Seoul Bus Ridership Using Artificial Neural Network Algorithm with Smartcard Data</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Hosuk%20Shin">Hosuk Shin</a>, <a href="https://publications.waset.org/abstracts/search?q=Young-Hyun%20Seo"> Young-Hyun Seo</a>, <a href="https://publications.waset.org/abstracts/search?q=Eunhak%20Lee"> Eunhak Lee</a>, <a href="https://publications.waset.org/abstracts/search?q=Seung-Young%20Kho"> Seung-Young Kho</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Currently, in Seoul, users have the privilege to avoid riding crowded buses with the installation of Bus Information System (BIS). BIS has three levels of on-board bus ridership level information (spacious, normal, and crowded). However, there are flaws in the system due to it being real time which could provide incomplete information to the user. For example, a bus comes to the station, and on the BIS it shows that the bus is crowded, but on the stop that the user is waiting many people get off, which would mean that this station the information should show as normal or spacious. To fix this problem, this study predicts the bus ridership level using smart card data to provide more accurate information about the passenger ridership level on the bus. An Artificial Neural Network (ANN) is an interconnected group of nodes, that was created based on the human brain. Forecasting has been one of the major applications of ANN due to the data-driven self-adaptive methods of the algorithm itself. According to the results, the ANN algorithm was stable and robust with somewhat small error ratio, so the results were rational and reasonable. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=smartcard%20data" title="smartcard data">smartcard data</a>, <a href="https://publications.waset.org/abstracts/search?q=ANN" title=" ANN"> ANN</a>, <a href="https://publications.waset.org/abstracts/search?q=bus" title=" bus"> bus</a>, <a href="https://publications.waset.org/abstracts/search?q=ridership" title=" ridership"> ridership</a> </p> <a href="https://publications.waset.org/abstracts/85135/predicting-seoul-bus-ridership-using-artificial-neural-network-algorithm-with-smartcard-data" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/85135.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">167</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">17</span> Subway Ridership Estimation at a Station-Level: Focus on the Impact of Bus Demand, Commercial Business Characteristics and Network Topology</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Jungyeol%20Hong">Jungyeol Hong</a>, <a href="https://publications.waset.org/abstracts/search?q=Dongjoo%20Park"> Dongjoo Park</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The primary purpose of this study is to develop a methodological framework to predict daily subway ridership at a station-level and to examine the association between subway ridership and bus demand incorporating commercial business facility in the vicinity of each subway station. The socio-economic characteristics, land-use, and built environment as factors may have an impact on subway ridership. However, it should be considered not only the endogenous relationship between bus and subway demand but also the characteristics of commercial business within a subway station’s sphere of influence, and integrated transit network topology. Regarding a statistical approach to estimate subway ridership at a station level, therefore it should be considered endogeneity and heteroscedastic issues which might have in the subway ridership prediction model. This study focused on both discovering the impacts of bus demand, commercial business characteristics, and network topology on subway ridership and developing more precise subway ridership estimation accounting for its statistical bias. The spatial scope of the study covers entire Seoul city in South Korea and includes 243 stations with the temporal scope set at twenty-four hours with one-hour interval time panels each. The data for subway and bus ridership was collected Seoul Smart Card data from 2015 and 2016. Three-Stage Least Square(3SLS) approach was applied to develop daily subway ridership model as capturing the endogeneity and heteroscedasticity between bus and subway demand. Independent variables incorporating in the modeling process were commercial business characteristics, social-economic characteristics, safety index, transit facility attributes, and dummies for seasons and time zone. As a result, it was found that bus ridership and subway ridership were endogenous each other and they had a significantly positive sign of coefficients which means one transit mode could increase another transportation mode’s ridership. In other words, two transit modes of subway and bus have a mutual relationship instead of the competitive relationship. The commercial business characteristics are the most critical dimension among the independent variables. The variables of commercial business facility rate in the paper containing six types; medical, educational, recreational, financial, food service, and shopping. From the model result, a higher rate in medical, financial buildings, shopping, and food service facility lead to increment of subway ridership at a station, while recreational and educational facility shows lower subway ridership. The complex network theory was applied for estimating integrated network topology measures that cover the entire Seoul transit network system, and a framework for seeking an impact on subway ridership. The centrality measures were found to be significant and showed a positive sign indicating higher centrality led to more subway ridership at a station level. The results of model accuracy tests by out of samples provided that 3SLS model has less mean square error rather than OLS and showed the methodological approach for the 3SLS model was plausible to estimate more accurate subway ridership. Acknowledgement: This research was supported by Basic Science Research Program through the National Research Foundation of Korea(NRF) funded by the Ministry of Science and ICT (2017R1C1B2010175). <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=subway%20ridership" title="subway ridership">subway ridership</a>, <a href="https://publications.waset.org/abstracts/search?q=bus%20ridership" title=" bus ridership"> bus ridership</a>, <a href="https://publications.waset.org/abstracts/search?q=commercial%20business%20characteristic" title=" commercial business characteristic"> commercial business characteristic</a>, <a href="https://publications.waset.org/abstracts/search?q=endogeneity" title=" endogeneity"> endogeneity</a>, <a href="https://publications.waset.org/abstracts/search?q=network%20topology" title=" network topology"> network topology</a> </p> <a href="https://publications.waset.org/abstracts/95629/subway-ridership-estimation-at-a-station-level-focus-on-the-impact-of-bus-demand-commercial-business-characteristics-and-network-topology" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/95629.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">144</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">16</span> Three-Stage Least Squared Models of a Station-Level Subway Ridership: Incorporating an Analysis on Integrated Transit Network Topology Measures</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Jungyeol%20Hong">Jungyeol Hong</a>, <a href="https://publications.waset.org/abstracts/search?q=Dongjoo%20Park"> Dongjoo Park</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The urban transit system is a critical part of a solution to the economic, energy, and environmental challenges. Furthermore, it ultimately contributes the improvement of people’s quality of lives. For taking these kinds of advantages, the city of Seoul has tried to construct an integrated transit system including both subway and buses. The effort led to the fact that approximately 6.9 million citizens use the integrated transit system every day for their trips. Diagnosing the current transit network is a significant task to provide more convenient and pleasant transit environment. Therefore, the critical objective of this study is to establish a methodological framework for the analysis of an integrated bus-subway network and to examine the relationship between subway ridership and parameters such as network topology measures, bus demand, and a variety of commercial business facilities. Regarding a statistical approach to estimate subway ridership at a station level, many previous studies relied on Ordinary Least Square regression, but there was lack of studies considering the endogeneity issues which might show in the subway ridership prediction model. This study focused on both discovering the impacts of integrated transit network topology measures and endogenous effect of bus demand on subway ridership. It could ultimately contribute to developing more accurate subway ridership estimation accounting for its statistical bias. The spatial scope of the study covers Seoul city in South Korea, and it includes 243 subway stations and 10,120 bus stops with the temporal scope set during twenty-four hours with one-hour interval time panels each. The subway and bus ridership information in detail was collected from the Seoul Smart Card data in 2015 and 2016. First, integrated subway-bus network topology measures which have characteristics regarding connectivity, centrality, transitivity, and reciprocity were estimated based on the complex network theory. The results of integrated transit network topology analysis were compared to subway-only network topology. Also, the non-recursive approach which is Three-Stage Least Square was applied to develop the daily subway ridership model as capturing the endogeneity between bus and subway demands. Independent variables included roadway geometry, commercial business characteristics, social-economic characteristics, safety index, transit facility attributes, and dummies for seasons and time zone. Consequently, it was found that network topology measures were significant size effect. Especially, centrality measures showed that the elasticity was a change of 4.88% for closeness centrality, 24.48% for betweenness centrality while the elasticity of bus ridership was 8.85%. Moreover, it was proved that bus demand and subway ridership were endogenous in a non-recursive manner as showing that predicted bus ridership and predicted subway ridership is statistically significant in OLS regression models. Therefore, it shows that three-stage least square model appears to be a plausible model for efficient subway ridership estimation. It is expected that the proposed approach provides a reliable guideline that can be used as part of the spectrum of tools for evaluating a city-wide integrated transit network. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=integrated%20transit%20system" title="integrated transit system">integrated transit system</a>, <a href="https://publications.waset.org/abstracts/search?q=network%20topology%20measures" title=" network topology measures"> network topology measures</a>, <a href="https://publications.waset.org/abstracts/search?q=three-stage%20least%20squared" title=" three-stage least squared"> three-stage least squared</a>, <a href="https://publications.waset.org/abstracts/search?q=endogeneity" title=" endogeneity"> endogeneity</a>, <a href="https://publications.waset.org/abstracts/search?q=subway%20ridership" title=" subway ridership"> subway ridership</a> </p> <a href="https://publications.waset.org/abstracts/83097/three-stage-least-squared-models-of-a-station-level-subway-ridership-incorporating-an-analysis-on-integrated-transit-network-topology-measures" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/83097.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">177</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">15</span> Fine-Scale Modeling the Influencing Factors of Multi-Time Dimensions of Transit Ridership at Station Level: The Study of Guangzhou City</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Dijiang%20Lyu">Dijiang Lyu</a>, <a href="https://publications.waset.org/abstracts/search?q=Shaoying%20Li"> Shaoying Li</a>, <a href="https://publications.waset.org/abstracts/search?q=Zhangzhi%20Tan"> Zhangzhi Tan</a>, <a href="https://publications.waset.org/abstracts/search?q=Zhifeng%20Wu"> Zhifeng Wu</a>, <a href="https://publications.waset.org/abstracts/search?q=Feng%20Gao"> Feng Gao</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Nowadays, China is experiencing rapidly urban rail transit expansions in the world. The purpose of this study is to finely model factors influencing transit ridership at multi-time dimensions within transit stations’ pedestrian catchment area (PCA) in Guangzhou, China. This study was based on multi-sources spatial data, including smart card data, high spatial resolution images, points of interest (POIs), real-estate online data and building height data. Eight multiple linear regression models using backward stepwise method and Geographic Information System (GIS) were created at station-level. According to Chinese code for classification of urban land use and planning standards of development land, residential land-use were divided into three categories: first-level (e.g. villa), second-level (e.g. community) and third-level (e.g. urban villages). Finally, it concluded that: (1) four factors (CBD dummy, number of feeder bus route, number of entrance or exit and the years of station operation) were proved to be positively correlated with transit ridership, but the area of green land-use and water land-use negative correlated instead. (2) The area of education land-use, the second-level and third-level residential land-use were found to be highly connected to the average value of morning peak boarding and evening peak alighting ridership. But the area of commercial land-use and the average height of buildings, were significantly positive associated with the average value of morning peak alighting and evening peak boarding ridership. (3) The area of the second-level residential land-use was rarely correlated with ridership in other regression models. Because private car ownership is still large in Guangzhou now, and some residents living in the community around the stations go to work by transit at peak time, but others are much more willing to drive their own car at non-peak time. The area of the third-level residential land-use, like urban villages, was highly positive correlated with ridership in all models, indicating that residents who live in the third-level residential land-use are the main passenger source of the Guangzhou Metro. (4) The diversity of land-use was found to have a significant impact on the passenger flow on the weekend, but was non-related to weekday. The findings can be useful for station planning, management and policymaking. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=fine-scale%20modeling" title="fine-scale modeling">fine-scale modeling</a>, <a href="https://publications.waset.org/abstracts/search?q=Guangzhou%20city" title=" Guangzhou city"> Guangzhou city</a>, <a href="https://publications.waset.org/abstracts/search?q=multi-time%20dimensions" title=" multi-time dimensions"> multi-time dimensions</a>, <a href="https://publications.waset.org/abstracts/search?q=multi-sources%20spatial%20data" title=" multi-sources spatial data"> multi-sources spatial data</a>, <a href="https://publications.waset.org/abstracts/search?q=transit%20ridership" title=" transit ridership"> transit ridership</a> </p> <a href="https://publications.waset.org/abstracts/95728/fine-scale-modeling-the-influencing-factors-of-multi-time-dimensions-of-transit-ridership-at-station-level-the-study-of-guangzhou-city" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/95728.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">142</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">14</span> Quantifying the Impact of Intermittent Signal Priority given to BRT on Ridership and Climate-A Case Study of Ahmadabad</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Smita%20Chaudhary">Smita Chaudhary</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Traffic in India are observed uncontrolled, and are characterized by chaotic (not follows the lane discipline) traffic situation. Bus Rapid Transit (BRT) has emerged as a viable option to enhance transportation capacity and provide increased levels of mobility and accessibility. At present in Ahmadabad there are as many intersections which face the congestion and delay at signalized intersection due to transit (BRT) lanes. Most of the intersection in spite of being signalized is operated manually due to the conflict between BRT buses and heterogeneous traffic. Though BRTS in Ahmadabad has an exclusive lane of its own but with this comes certain limitations which Ahmadabad is facing right now. At many intersections in Ahmadabad due to these conflicts, interference, and congestion both heterogeneous traffic as well as transit buses suffer traffic delays of remarkable 3-4 minutes at each intersection which has a become an issue of great concern. There is no provision of BRT bus priority due to which existing signals have their least role to play in managing the traffic that ultimately call for manual operation. There is an immense decrement in the daily ridership of BRTS because people are finding this transit mode no more time saving in their routine, there is an immense fall in ridership ultimately leading to increased number of private vehicles, idling of vehicles at intersection cause air and noise pollution. In order to bring back these commuters’ transit facilities need to be improvised. Classified volume count survey, travel time delay survey was conducted and revised signal design was done for whole study stretch having three intersections and one roundabout, later one intersection was simulated in order to see the effect of giving priority to BRT on side street queue length and travel time for heterogeneous traffic. This paper aims at suggesting the recommendations in signal cycle, introduction of intermittent priority for transit buses, simulation of intersection in study stretch with proposed signal cycle using VISSIM in order to make this transit amenity feasible and attracting for commuters in Ahmadabad. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=BRT" title="BRT">BRT</a>, <a href="https://publications.waset.org/abstracts/search?q=priority" title=" priority"> priority</a>, <a href="https://publications.waset.org/abstracts/search?q=Ridership" title=" Ridership"> Ridership</a>, <a href="https://publications.waset.org/abstracts/search?q=Signal" title=" Signal"> Signal</a>, <a href="https://publications.waset.org/abstracts/search?q=VISSIM" title=" VISSIM"> VISSIM</a> </p> <a href="https://publications.waset.org/abstracts/35378/quantifying-the-impact-of-intermittent-signal-priority-given-to-brt-on-ridership-and-climate-a-case-study-of-ahmadabad" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/35378.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">441</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">13</span> Ridership Study for the Proposed Installation of Automatic Guide-way Transit (AGT) System along Sapphire Street in Balanga City, Bataan</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Nelson%20Andres">Nelson Andres</a>, <a href="https://publications.waset.org/abstracts/search?q=Meeko%20C.%20Masangcap"> Meeko C. Masangcap</a>, <a href="https://publications.waset.org/abstracts/search?q=John%20Denver%20D.%20Catapang"> John Denver D. Catapang</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Balanga City as, the heart of Bataan, is a growing City and is now at its fast pace of development. The growth of commerce in the city results to an increase in commuters who travel back and forth through the city, leading to congestions. Consequently, queuing of vehicles along national roads and even in the highways of the city have become a regular occurrence. This common scenario of commuters flocking the city, private and public vehicles going bumper to bumper, especially during the rush hours, greatly affect the flow of traffic vehicles and is now a burden not only to the commuters but also to the government who is trying to address this dilemma. Seeing these terrible events, the implementation of an elevated Automated Guide-way transit is seen as a possible solution to help in the decongestion of the affected parts of Balanga City.In response to the problem, the researchers identify if it is feasible to have an elevated guide-way transit in the vicinity of Sapphire Street in Balanga City, Bataan. Specifically, the study aims to determine who will be the riders based on the demographic profile, where the trip can be generated and distributed, the time when volume of people usually peaks and the estimated volume of passengers. Statistical analysis is applied to the data gathered to find out if there is an important relationship between the demographic profile of the respondents and their preference of having an elevated railway transit in the City of Balanga. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=ridership" title="ridership">ridership</a>, <a href="https://publications.waset.org/abstracts/search?q=AGT" title=" AGT"> AGT</a>, <a href="https://publications.waset.org/abstracts/search?q=railway" title=" railway"> railway</a>, <a href="https://publications.waset.org/abstracts/search?q=elevated%20track" title=" elevated track"> elevated track</a> </p> <a href="https://publications.waset.org/abstracts/168275/ridership-study-for-the-proposed-installation-of-automatic-guide-way-transit-agt-system-along-sapphire-street-in-balanga-city-bataan" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/168275.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">82</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">12</span> Predictive Analytics of Bike Sharing Rider Parameters</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Bongs%20Lainjo">Bongs Lainjo</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The evolution and escalation of bike-sharing programs (BSP) continue unabated. Since the sixties, many countries have introduced different models and strategies of BSP. These include variations ranging from dockless models to electronic real-time monitoring systems. Reasons for using this BSP include recreation, errands, work, etc. And there is all indication that complex, and more innovative rider-friendly systems are yet to be introduced. The objective of this paper is to analyze current variables established by different operators and streamline them identifying the most compelling ones using analytics. Given the contents of available databases, there is a lack of uniformity and common standard on what is required and what is not. Two factors appear to be common: user type (registered and unregistered, and duration of each trip). This article uses historical data provided by one operator based in the greater Washington, District of Columbia, USA area. Several variables including categorical and continuous data types were screened. Eight out of 18 were considered acceptable and significantly contribute to determining a useful and reliable predictive model. Bike-sharing systems have become popular in recent years all around the world. Although this trend has resulted in many studies on public cycling systems, there have been few previous studies on the factors influencing public bicycle travel behavior. A bike-sharing system is a computer-controlled system in which individuals can borrow bikes for a fee or free for a limited period. This study has identified unprecedented useful, and pragmatic parameters required in improving BSP ridership dynamics. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=sharing%20program" title="sharing program">sharing program</a>, <a href="https://publications.waset.org/abstracts/search?q=historical%20data" title=" historical data"> historical data</a>, <a href="https://publications.waset.org/abstracts/search?q=parameters" title=" parameters"> parameters</a>, <a href="https://publications.waset.org/abstracts/search?q=ridership%20dynamics" title=" ridership dynamics"> ridership dynamics</a>, <a href="https://publications.waset.org/abstracts/search?q=trip%20duration" title=" trip duration"> trip duration</a> </p> <a href="https://publications.waset.org/abstracts/143186/predictive-analytics-of-bike-sharing-rider-parameters" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/143186.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">138</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">11</span> University Students’ Perception on Public Transit in Dhaka City</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mosabbir%20Pasha">Mosabbir Pasha</a>, <a href="https://publications.waset.org/abstracts/search?q=Ijaj%20Mahmud%20Chowdhury"> Ijaj Mahmud Chowdhury</a>, <a href="https://publications.waset.org/abstracts/search?q=M.%20A.%20Afrahim%20Bhuiyann"> M. A. Afrahim Bhuiyann</a> </p> <p class="card-text"><strong>Abstract:</strong></p> With the increasing population and intensive land use, huge traffic demand is generating worldwide both in developing and developed countries. As a developing country, Bangladesh is also facing the same problem in recent years by producing huge numbers of daily trips. As a matter of fact, extensive traffic demand is increasing day by day. Also, transport system in Dhaka is heterogeneous, reflecting the heterogeneity in the socio-economic and land use patterns. As a matter of fact, trips produced here are for different purposes such as work, business, educational etc. Due to the significant concentration of educational institutions a large share of the trips are generated by educational purpose. And one of the major percentages of educational trips is produced by university going students and most of them are travelled by car, bus, train, taxi, rickshaw etc. The aim of the study was to find out the university students’ perception on public transit ridership. A survey was conducted among 330 students from eight different universities. It was found out that 26% of the trips produced by university going students are travelled by public bus service and only 5% are by train. Percentage of car share is 16% and 12% of the trips are travelled by private taxi. From the study, it has been found that more than 42 percent student’s family resides outside of Dhaka, eventually they prefer bus instead of other options. Again those who chose to walk most of the time, of them, over 40 percent students’ family reside outside of Dhaka and of them over 85 percent students have a tendency to live in a mess. They generally choose a neighboring location to their respective university so that they can reach their destination by walk. On the other hand, those who travel by car 80 percent of their family reside inside Dhaka. The study also revealed that the most important reason that restricts students not to use public transit is poor service. Negative attitudes such as discomfort, uneasiness in using public transit also reduces the usage of public transit. The poor waiting area is another major cause of not using public transit. Insufficient security also plays a significant role in not using public transit. On the contrary, the fare is not a problem for students those who use public transit as a mode of transportation. Students also think stations are not far away from their home or institution and they do not need to wait long for the buses or trains. It was also found accessibility to public transit is moderate. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=traffic%20demand" title="traffic demand">traffic demand</a>, <a href="https://publications.waset.org/abstracts/search?q=fare" title=" fare"> fare</a>, <a href="https://publications.waset.org/abstracts/search?q=poor%20service" title=" poor service"> poor service</a>, <a href="https://publications.waset.org/abstracts/search?q=public%20transit%20ridership" title=" public transit ridership"> public transit ridership</a> </p> <a href="https://publications.waset.org/abstracts/37042/university-students-perception-on-public-transit-in-dhaka-city" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/37042.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">268</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">10</span> Integrated Best Worst PROMETHEE to Evaluate Public Transport Service Quality</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Laila%20Oubahman">Laila Oubahman</a>, <a href="https://publications.waset.org/abstracts/search?q=Duleba%20Szabolcs"> Duleba Szabolcs</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Public transport stakeholders aim to increase the ridership ratio by encouraging citizens to use common transportation modes. For this sight, improving service quality is a crucial option to reach the quality desired by users and reduce the gap between desired and perceived quality. Multi-criteria decision aid has been applied in literature in recent decades because it provides efficient models to assess the most impacting criteria on the overall assessment. In this paper, the PROMETHEE method is combined with the best-worst approach to construct a consensual model that avoids rank reversal to support stakeholders in ameliorating service quality. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=best-worst%20method" title="best-worst method">best-worst method</a>, <a href="https://publications.waset.org/abstracts/search?q=MCDA" title=" MCDA"> MCDA</a>, <a href="https://publications.waset.org/abstracts/search?q=PROMETHEE" title=" PROMETHEE"> PROMETHEE</a>, <a href="https://publications.waset.org/abstracts/search?q=public%20transport" title=" public transport"> public transport</a> </p> <a href="https://publications.waset.org/abstracts/134455/integrated-best-worst-promethee-to-evaluate-public-transport-service-quality" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/134455.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">208</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">9</span> A Study of Cloud Computing Solution for Transportation Big Data Processing</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ilgin%20G%C3%B6ka%C5%9Far">Ilgin Gökaşar</a>, <a href="https://publications.waset.org/abstracts/search?q=Saman%20Ghaffarian"> Saman Ghaffarian</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The need for fast processed big data of transportation ridership (eg., smartcard data) and traffic operation (e.g., traffic detectors data) which requires a lot of computational power is incontrovertible in Intelligent Transportation Systems. Nowadays cloud computing is one of the important subjects and popular information technology solution for data processing. It enables users to process enormous measure of data without having their own particular computing power. Thus, it can also be a good selection for transportation big data processing as well. This paper intends to examine how the cloud computing can enhance transportation big data process with contrasting its advantages and disadvantages, and discussing cloud computing features. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=big%20data" title="big data">big data</a>, <a href="https://publications.waset.org/abstracts/search?q=cloud%20computing" title=" cloud computing"> cloud computing</a>, <a href="https://publications.waset.org/abstracts/search?q=Intelligent%20Transportation%20Systems" title=" Intelligent Transportation Systems"> Intelligent Transportation Systems</a>, <a href="https://publications.waset.org/abstracts/search?q=ITS" title=" ITS"> ITS</a>, <a href="https://publications.waset.org/abstracts/search?q=traffic%20data%20processing" title=" traffic data processing"> traffic data processing</a> </p> <a href="https://publications.waset.org/abstracts/32308/a-study-of-cloud-computing-solution-for-transportation-big-data-processing" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/32308.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">468</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">8</span> Factors Affecting Bus Use as a Sustainable Mode of Transportation: Insights from Kerman, Iran</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Fatemeh%20Rahmani">Fatemeh Rahmani</a>, <a href="https://publications.waset.org/abstracts/search?q=Navid%20Nadimi"> Navid Nadimi</a>, <a href="https://publications.waset.org/abstracts/search?q=Vahid%20Khalifeh"> Vahid Khalifeh</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In the near future, cities with medium populations will face traffic congestion, air pollution, high fuel consumption, and noise pollution. It is possible to improve the sustainability of cities by utilizing public transportation. A study of the factors that influence citizens' bus usage in medium-sized cities is presented in this paper. For this purpose, Kerman's citizens were surveyed online. The model was based on a binary logistic regression. A descriptive analysis revealed that simple measures like renewing the fleet, upgrading the stations, establishing a schedule program, and cleaning the buses could improve passenger satisfaction. In addition, the modeling results showed that future traffic congestion can be prevented by implementing road and parking lot pricing plans. Further, as the number and length of trips increase, the probability of citizens taking the bus increases. In conclusion, Kerman's bus system is both secure and fast, but these two characteristics can be improved to increase bus ridership. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=sustainability" title="sustainability">sustainability</a>, <a href="https://publications.waset.org/abstracts/search?q=transportation" title=" transportation"> transportation</a>, <a href="https://publications.waset.org/abstracts/search?q=bus" title=" bus"> bus</a>, <a href="https://publications.waset.org/abstracts/search?q=congestion" title=" congestion"> congestion</a>, <a href="https://publications.waset.org/abstracts/search?q=satisfaction" title=" satisfaction"> satisfaction</a> </p> <a href="https://publications.waset.org/abstracts/193855/factors-affecting-bus-use-as-a-sustainable-mode-of-transportation-insights-from-kerman-iran" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/193855.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">10</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">7</span> A Look Back at America’s Transit History and the Impacts of Household Income on Walkability</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Jackson%20Becker">Jackson Becker</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Transportation produces the largest amount of carbon dioxide emissions in the United States of America. Today, cars are the predominant mode of transportation across the country, and our cities have been reshaped due to them. This was not always the case. Streetcars were seen in almost every American city of the early 1900s. These streetcar systems were viewed as obsolete with the rise of the automobile. With fewer streetcars came lower public transport ridership. Austin, Texas is one of the fastest growing cities in the country, and it used to have an extensive streetcar line. Today, it plans to build a light rail line with less rail mileage than 100 years ago. This research looks at the areas of Austin that are not included in the city’s new transit plan. Transit connectivity is one factor that goes into walkability rates for cities. This study also looks at the correlation between walkability ratings with median household income levels from the 2019 Census. The results showed a correlation between higher income neighborhoods having higher walkability rates, which was influenced by the lack of public transportation options. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=transportation" title="transportation">transportation</a>, <a href="https://publications.waset.org/abstracts/search?q=walkability" title=" walkability"> walkability</a>, <a href="https://publications.waset.org/abstracts/search?q=income" title=" income"> income</a>, <a href="https://publications.waset.org/abstracts/search?q=austin" title=" austin"> austin</a> </p> <a href="https://publications.waset.org/abstracts/191382/a-look-back-at-americas-transit-history-and-the-impacts-of-household-income-on-walkability" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/191382.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">13</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">6</span> Elasticity Model for Easing Peak Hour Demand for Metrorail Transport System</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=P.%20K.%20Sarkar">P. K. Sarkar</a>, <a href="https://publications.waset.org/abstracts/search?q=Amit%20Kumar%20Jain"> Amit Kumar Jain</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The demand for Urban transportation is characterised by a large scale temporal and spatial variations which causes heavy congestion inside metro trains in peak hours near Centre Business District (CBD) of the city. The conventional approach to address peak hour congestion, metro trains has been to increase the supply by way of introduction of more trains, increasing the length of the trains, optimising the time table to increase the capacity of the system. However, there is a limitation of supply side measures determined by the design capacity of the systems beyond which any addition in the capacity requires huge capital investments. The demand side interventions are essentially required to actually spread the demand across the time and space. In this study, an attempt has been made to identify the potential Transport Demand Management tools applicable to Urban Rail Transportation systems with a special focus on differential pricing. A conceptual price elasticity model has been developed to analyse the effect of various combinations of peak and nonpeak hoursfares on demands. The elasticity values for peak hour, nonpeak hour and cross elasticity have been assumed from the relevant literature available in the field. The conceptual price elasticity model so developed is based on assumptions which need to be validated with actual values of elasticities for different segments of passengers. Once validated, the model can be used to determine the peak and nonpeak hour fares with an objective to increase overall ridership, revenue, demand levelling and optimal utilisation of assets<em>.</em> <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=urban%20transport" title="urban transport">urban transport</a>, <a href="https://publications.waset.org/abstracts/search?q=differential%20fares" title=" differential fares"> differential fares</a>, <a href="https://publications.waset.org/abstracts/search?q=congestion" title=" congestion"> congestion</a>, <a href="https://publications.waset.org/abstracts/search?q=transport%20demand%20management" title=" transport demand management"> transport demand management</a>, <a href="https://publications.waset.org/abstracts/search?q=elasticity" title=" elasticity"> elasticity</a> </p> <a href="https://publications.waset.org/abstracts/51312/elasticity-model-for-easing-peak-hour-demand-for-metrorail-transport-system" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/51312.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">309</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">5</span> Cycling Usage and Determinants on University Campus in Ghana: The Case of Kwame Nkrumah University of Science and Technology</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Nicholas%20Anarfi%20Bofah">Nicholas Anarfi Bofah</a>, <a href="https://publications.waset.org/abstracts/search?q=James%20Damsere-%20Derry"> James Damsere- Derry</a> </p> <p class="card-text"><strong>Abstract:</strong></p> There is increasing interest among institutions, governments, and international organisations to combat congestion, reduce contribution to green gases and provide sustainable urban transportation. College campuses are a preeminent setting for promoting active commuting to ameliorate a community's healthy lifestyle. Cycling is an important physical activity and has a long-term effect on health, and it is considered one of the top five interventions to reduce the prevalence of non-communicable diseases. The main objectives of the research were: (i) to identify students’ attitudes and behavior toward cycling usage, (ii) to identify barriers and opportunities for cycling on a university campus, and (iii) to construct tangible policy recommendations for promoting cycling in the vicinity of the university. The data used in this study were obtained from a survey conducted among students at the Kwame Nkrumah University of Science and Technology (KNUST) in Kumasi between May 2022 and September 2022. A convenient sampling method was used to recruit and interview 398 participants. Two survey assistants who are former students of the university were engaged to administer the questionnaires randomly to students at the selected locations. Descriptive statistics were employed in the analysis of the data. Out of the 398 questionnaires, bicycle ridership and ownership among university students were 57% and 39%, respectively. Generally, the desire to use a bicycle as a mode of transport on campus was 36%. The desire to use a bicycle on campus was more prevalent among males 41% compared to females 30%. There is a high potential for increasing bicycle use among students. Recommendations include the provision of bicycle lanes, public education on the use of bicycles, and a campus bicycle-sharing program. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=sustainable%20development" title="sustainable development">sustainable development</a>, <a href="https://publications.waset.org/abstracts/search?q=cycling" title=" cycling"> cycling</a>, <a href="https://publications.waset.org/abstracts/search?q=university%20campus" title=" university campus"> university campus</a>, <a href="https://publications.waset.org/abstracts/search?q=bicycle" title=" bicycle"> bicycle</a> </p> <a href="https://publications.waset.org/abstracts/169809/cycling-usage-and-determinants-on-university-campus-in-ghana-the-case-of-kwame-nkrumah-university-of-science-and-technology" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/169809.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">88</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">4</span> The Proposal of a Shared Mobility City Index to Support Investment Decision Making for Carsharing</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=S.%20Murr">S. Murr</a>, <a href="https://publications.waset.org/abstracts/search?q=S.%20Phillips"> S. Phillips</a> </p> <p class="card-text"><strong>Abstract:</strong></p> One of the biggest challenges entering a market with a carsharing or any other shared mobility (SM) service is sound investment decision-making. To support this process, the authors think that a city index evaluating different criteria is necessary. The goal of such an index is to benchmark cities along a set of external measures to answer the main two challenges: financially viability and the understanding of its specific requirements. The authors have consulted several shared mobility projects and industry experts to create such a Shared Mobility City Index (SMCI). The current proposal of the SMCI consists of 11 individual index measures: general data (demographics, geography, climate and city culture), shared mobility landscape (current SM providers, public transit options, commuting patterns and driving culture) and political vision and goals (vision of the Mayor, sustainability plan, bylaws/tenders supporting SM). To evaluate the suitability of the index, 16 cities on the East Coast of North America were selected and secondary research was conducted. The main sources of this study were census data, organisational records, independent press releases and informational websites. Only non-academic sources where used because the relevant data for the chosen cities is not published in academia. Applying the index measures to the selected cities resulted in three major findings. Firstly, density (city area divided by number of inhabitants) is not an indicator for the number of SM services offered: the city with the lowest density has five bike and carsharing options. Secondly, there is a direct correlation between commuting patterns and how many shared mobility services are offered. New York, Toronto and Washington DC have the highest public transit ridership and the most shared mobility providers. Lastly, except one, all surveyed cities support shared mobility with their sustainability plan. The current version of the shared mobility index is proving a practical tool to evaluate cities, and to understand functional, political, social and environmental considerations. More cities will have to be evaluated to refine the criteria further. However, the current version of the index can be used to assess cities on their suitability for shared mobility services and will assist investors deciding which city is a financially viable market. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=carsharing" title="carsharing">carsharing</a>, <a href="https://publications.waset.org/abstracts/search?q=transportation" title=" transportation"> transportation</a>, <a href="https://publications.waset.org/abstracts/search?q=urban%20planning" title=" urban planning"> urban planning</a>, <a href="https://publications.waset.org/abstracts/search?q=shared%20mobility%20city%20index" title=" shared mobility city index"> shared mobility city index</a> </p> <a href="https://publications.waset.org/abstracts/41142/the-proposal-of-a-shared-mobility-city-index-to-support-investment-decision-making-for-carsharing" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/41142.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">303</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3</span> Ambient Factors in the Perception of Crowding in Public Transport </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=John%20Zacharias">John Zacharias</a>, <a href="https://publications.waset.org/abstracts/search?q=Bin%20Wang"> Bin Wang</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Travel comfort is increasingly seen as crucial to effecting the switch from private motorized modes to public transit. Surveys suggest that travel comfort is closely related to perceived crowding, that may involve lack of available seating, difficulty entering and exiting, jostling and other physical contacts with strangers. As found in studies on environmental stress, other factors may moderate perceptions of crowding–in this case, we hypothesize that the ambient environment may play a significant role. Travel comfort was measured by applying a structured survey to randomly selected passengers (n=369) on 3 lines of the Beijing metro on workdays. Respondents were standing with all seats occupied and with car occupancy at 14 levels. A second research assistant filmed the metro car while passengers were interviewed, to obtain the total number of passengers. Metro lines 4, 6 and 10 were selected that travel through the central city north-south, east-west and circumferentially. Respondents evaluated the following factors: crowding, noise, smell, air quality, temperature, illumination, vibration and perceived safety as they experienced them at the time of interview, and then were asked to rank these 8 factors according to their importance for their travel comfort. Evaluations were semantic differentials on a 7-point scale from highly unsatisfactory (-3) to highly satisfactory (+3). The control variables included age, sex, annual income and trip purpose. Crowding was assessed most negatively, with 41% of the scores between -3 and -2. Noise and air quality were also assessed negatively, with two-thirds of the evaluations below 0. Illumination was assessed most positively, followed by crime, vibration and temperature, all scoring at indifference (0) or slightly positive. Perception of crowding was linearly and positively related to the number of passengers in the car. Linear regression tested the impact of ambient environmental factors on perception of crowding. Noise intensity accounted for more than the actual number of individuals in the car in the perception of crowding, with smell also contributing. Other variables do not interact with the crowding variable although the evaluations are distinct. In all, only one-third of the perception of crowding (R2=.154) is explained by the number of people, with the other ambient environmental variables accounting for two-thirds of the variance (R2=.316). However, when ranking the factors by their importance to travel comfort, perceived crowding made up 69% of the first rank, followed by noise at 11%. At rank 2, smell dominates (25%), followed by noise and air quality (17%). Commuting to work induces significantly lower evaluations of travel comfort with shopping the most positive. Clearly, travel comfort is particularly important to commuters. Moreover, their perception of crowding while travelling on metro is highly conditioned by the ambient environment in the metro car. Focussing attention on the ambient environmental conditions of the metro is an effective way to address the primary concerns of travellers with overcrowding. In general, the strongly held opinions on travel comfort require more attention in the effort to induce ridership in public transit. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=ambient%20environment" title="ambient environment">ambient environment</a>, <a href="https://publications.waset.org/abstracts/search?q=mass%20rail%20transit" title=" mass rail transit"> mass rail transit</a>, <a href="https://publications.waset.org/abstracts/search?q=public%20transit" title=" public transit"> public transit</a>, <a href="https://publications.waset.org/abstracts/search?q=travel%20comfort" title=" travel comfort"> travel comfort</a> </p> <a href="https://publications.waset.org/abstracts/69586/ambient-factors-in-the-perception-of-crowding-in-public-transport" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/69586.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">262</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2</span> Tall Building Transit-Oriented Development (TB-TOD) and Energy Efficiency in Suburbia: Case Studies, Sydney, Toronto, and Washington D.C. </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Narjes%20Abbasabadi">Narjes Abbasabadi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> As the world continues to urbanize and suburbanize, where suburbanization associated with mass sprawl has been the dominant form of this expansion, sustainable development challenges will be more concerned. Sprawling, characterized by low density and automobile dependency, presents significant environmental issues regarding energy consumption and Co2 emissions. This paper examines the vertical expansion of suburbs integrated into mass transit nodes as a planning strategy for boosting density, intensification of land use, conversion of single family homes to multifamily dwellings or mixed use buildings and development of viable alternative transportation choices. It analyzes the spatial patterns of tall building transit-oriented development (TB-TOD) of suburban regions in Sydney (Australia), Toronto (Canada), and Washington D.C. (United States). The main objectives of this research seek to understand the effect of the new morphology of suburban tall, the physical dimensions of individual buildings and their arrangement at a larger scale with energy efficiency. This study aims to answer these questions: 1) why and how can the potential phenomenon of vertical expansion or high-rise development be integrated into suburb settings? 2) How can this phenomenon contribute to an overall denser development of suburbs? 3) Which spatial pattern or typologies/ sub-typologies of the TB-TOD model do have the greatest energy efficiency? It addresses these questions by focusing on 1) energy, heat energy demand (excluding cooling and lighting) related to design issues at two levels: macro, urban scale and micro, individual buildings—physical dimension, height, morphology, spatial pattern of tall buildings and their relationship with each other and transport infrastructure; 2) Examining TB-TOD to provide more evidence of how the model works regarding ridership. The findings of the research show that the TB-TOD model can be identified as the most appropriate spatial patterns of tall buildings in suburban settings. And among the TB-TOD typologies/ sub-typologies, compact tall building blocks can be the most energy efficient one. This model is associated with much lower energy demands in buildings at the neighborhood level as well as lower transport needs in an urban scale while detached suburban high rise or low rise suburban housing will have the lowest energy efficiency. The research methodology is based on quantitative study through applying the available literature and static data as well as mapping and visual documentations of urban regions such as Google Earth, Microsoft Bing Bird View and Streetview. It will examine each suburb within each city through the satellite imagery and explore the typologies/ sub-typologies which are morphologically distinct. The study quantifies heat energy efficiency of different spatial patterns through simulation via GIS software. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=energy%20efficiency" title="energy efficiency">energy efficiency</a>, <a href="https://publications.waset.org/abstracts/search?q=spatial%20pattern" title=" spatial pattern"> spatial pattern</a>, <a href="https://publications.waset.org/abstracts/search?q=suburb" title=" suburb"> suburb</a>, <a href="https://publications.waset.org/abstracts/search?q=tall%20building%20transit-oriented%20development%20%28TB-TOD%29" title=" tall building transit-oriented development (TB-TOD)"> tall building transit-oriented development (TB-TOD)</a> </p> <a href="https://publications.waset.org/abstracts/65894/tall-building-transit-oriented-development-tb-tod-and-energy-efficiency-in-suburbia-case-studies-sydney-toronto-and-washington-dc" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/65894.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">260</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1</span> Unpacking the Spatial Outcomes of Public Transportation in a Developing Country Context: The Case of Johannesburg</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Adedayo%20B.%20Adegbaju">Adedayo B. Adegbaju</a>, <a href="https://publications.waset.org/abstracts/search?q=Carel%20B.%20Schoeman"> Carel B. Schoeman</a>, <a href="https://publications.waset.org/abstracts/search?q=Ilse%20M.%20Schoeman"> Ilse M. Schoeman</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The unique urban contexts that emanated from the apartheid history of South Africa informed the transport landscape of the City of Johannesburg. Apartheid‘s divisive spatial planning and land use management policies promoted sprawling and separated workers from job opportunities. This was further exacerbated by poor funding of public transport and road designs that encouraged the use of private cars. However, the democratization of the country in 1994 and the hosting of the 2010 FIFA World Cup provided a new impetus to the city’s public transport-oriented urban planning inputs. At the same time, the state’s new approach to policy formulations that entails the provision of public transport as one of the tools to end years of marginalization and inequalities soon began to largely reflect in planning decisions of other spheres of government. The Rea Vaya BRT and the Gautrain were respectively implemented by the municipal and provincial governments to demonstrate strong political will and commitment to the new policy direction. While the Gautrain was implemented to facilitate elite movement within Gauteng and to crowd investments and economic growths around station nodes, the BRT was provided for previously marginalized public transport users to provide a sustainable alternative to the dominant minibus taxi. The aim of this research is to evaluate the spatial impacts of the Gautrain and Rea Vaya BRT on the City of Johannesburg and to inform future outcomes by determining the existing potentials. By using the case study approach with a focus on the BRT and fast rail in a metropolitan context, the triangulation research method, which combines various data collection methods, was used to determine the research outcomes. The use of interviews, questionnaires, field observation, and databases such as REX, Quantec, StatsSA, GCRO observatory, national and provincial household travel surveys, and the quality of life surveys provided the basis for data collection. The research concludes that the Gautrain has demonstrated that viable alternatives to the private car can be provided, with its satisfactory feedbacks from users; while some of its station nodes (Sandton, Rosebank) have shown promises of transit-oriented development, one of the project‘s key objectives. The other stations have been unable to stimulate growth due to reasons like non-implementation of their urban design frameworks and lack of public sector investment required to attract private investors. The Rea Vaya BRT continues to be expanded in spite of both its inability to induce modal change and its low ridership figures. The research identifies factors like the low peak to base ratio, pricing, and the city‘s disjointed urban fabric as some of the reasons for its below-average performance. By drawing from the highlights and limitations, the study recommends that public transport provision should be institutionally integrated across and within spheres of government. Similarly, harmonization of the funding structure, better understanding of users’ needs, and travel patterns, underlined with continuity of policy direction and objectives, will equally promote optimal outcomes. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=bus%20rapid%20transit" title="bus rapid transit">bus rapid transit</a>, <a href="https://publications.waset.org/abstracts/search?q=Gautrain" title=" Gautrain"> Gautrain</a>, <a href="https://publications.waset.org/abstracts/search?q=Rea%20Vaya" title=" Rea Vaya"> Rea Vaya</a>, <a href="https://publications.waset.org/abstracts/search?q=sustainable%20transport" title=" sustainable transport"> sustainable transport</a>, <a href="https://publications.waset.org/abstracts/search?q=spatial%20and%20transport%20planning" title=" spatial and transport planning"> spatial and transport planning</a>, <a href="https://publications.waset.org/abstracts/search?q=transit%20oriented%20development" title=" transit oriented development"> transit oriented development</a> </p> <a href="https://publications.waset.org/abstracts/120489/unpacking-the-spatial-outcomes-of-public-transportation-in-a-developing-country-context-the-case-of-johannesburg" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/120489.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">114</span> </span> </div> </div> </div> </main> <footer> <div id="infolinks" class="pt-3 pb-2"> <div class="container"> <div style="background-color:#f5f5f5;" class="p-3"> <div class="row"> <div class="col-md-2"> <ul class="list-unstyled"> About <li><a href="https://waset.org/page/support">About Us</a></li> <li><a href="https://waset.org/page/support#legal-information">Legal</a></li> <li><a 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