Aggregated Modeling for Multimodal Traffic Flow and Dispatching Control in Urban Road Networks with Ride-Sharing Services
Publication: Journal of Transportation Engineering, Part A: Systems
Volume 149, Issue 12
Abstract
As ride-sharing emerges as a new mobility choice, modeling and control of large-scale multimodal systems in automated and shared environment recently has received significant attention. This paper developed a modeling approach for capturing the demand–supply relationship and the traffic flow dynamics in such ride-sharing systems at an aggregated network level. Private cars, taxis, and single- and multioccupancy ride-sharing vehicles are considered. A macroscopic fundamental diagram–based traffic flow model was constructed to describe the spatiotemporal physics of traffic. Multimodal meeting functions are utilized for passenger–vehicle matching in the shared transportation system. The proposed model enabled us to formulate an optimization model for region-level dispatching control strategies and relocating taxis and ride-sharing vehicles for different objectives. The results of experimental study reveal that (1) the proposed model can reproduce traffic dynamics and multimodal interactions under various traffic conditions, travel demands, and service intensities; and (2) the developed control theory–based dispatching strategies can improve the efficiency of all modes in the shared transportation system, and reduce the travel cost for riders and promote the level of service for passengers.
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Data Availability Statement
Some or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request.
Acknowledgments
This research is jointly supported by the Beijing Advanced Innovation Centre of Big Data and Brain Computing (BDBC) of Beihang University and the Monash-JITRI Industrial Research and Development Fund. Jingyang Liao completed part of her work at China Academy of Urban Planning & Design. The authors retain sole responsibility for any errors or omissions. The authors thank Dr. Mohsen Ramezani from the University of Sydney for generously sharing his knowledge of the base model and providing advice for this work. This work is partially supported by the Youth Talent Support Program of Beihang University (YWF-22-L-1239), the National Natural Science Foundation of China (72201017), the China Postdoctoral Science Foundation (2022M720354), and the Academic Excellence Foundation of BUAA for Ph.D. Students.
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Published In
Journal of Transportation Engineering, Part A: Systems
Volume 149 • Issue 12 • December 2023
Copyright
© 2023 American Society of Civil Engineers.
History
Received: Dec 6, 2022
Accepted: Jun 22, 2023
Published online: Sep 22, 2023
Published in print: Dec 1, 2023
Discussion open until: Feb 22, 2024
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