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Jul 2, 2019
Transit Operation Optimization in the Context of Connected and Automated Vehicles: A Case Study of Beijing
Authors: Xuanliang Shen, Xiaolei Ma [email protected], Zhao Zhang, Yuelong Su, and Zhenning DongAuthor Affiliations
Publication: CICTP 2019
Abstract
Connected and automated vehicles (CAV) initiatives are revolutionizing the entire transportation society. Not limited in the area of passenger cars, public transit agencies also seek for the possibility of replacing tremendous manpower with the state-of-the-art “self-driving” technologies. In this study, we developed an optimization model to quantify how the CAV benefits the route-level transit operations if all current non-automated buses are converted into autonomous buses. A bi-objective mixed integer programming model is established to minimize passenger waiting times and maximize passenger flows considering all buses are running on a bus dedicated lane. By taking one actual bus route in Beijing as a case study, we computed the operational performance indicators of non-automated bus based on smart card and GPS data, and compared with the optimized bus routes with CAV technologies. The findings reveal that autonomous buses can significantly reduce vehicle usages, reduce bus bunching, increase passenger loads, and lower average passenger waiting time.
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© 2019 American Society of Civil Engineers.
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Published online: Jul 2, 2019
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Xuanliang Shen
Beijing Key Laboratory for Cooperative Vehicle Infrastructure System and Safety Control, School of Transportation Science and Engineering, Beihang Univ., Xue Yuan Rd. No. 37, HaiDian District, Beijing 100191, China.
Beijing Key Laboratory for Cooperative Vehicle Infrastructure System and Safety Control, School of Transportation Science and Engineering, Beihang Univ., Xue Yuan Rd. No. 37, HaiDian District, Beijing 100191, China; Beijing Advanced Innovation Center for Big Data and Brain Computing, Beihang Univ., Xue Yuan Rd. No. 37, HaiDian District, Beijing 100191, China. E-mail: [email protected]
Zhao Zhang
Beijing Key Laboratory for Cooperative Vehicle Infrastructure System and Safety Control, School of Transportation Science and Engineering, Beihang Univ., Xue Yuan Rd. No. 37, HaiDian District, Beijing 100191, China.
Yuelong Su
Traffic Management Solution Division, AutoNavi Software Co., Beijing 100102, China.
Zhenning Dong
Vice President, AutoNavi Software Co., Beijing 100102, China.
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