Chapter
Aug 12, 2020
A Grouping Approach to Ridesplitting Optimization
Authors: Jiangtao Zhu [email protected], Dong Mo [email protected], and Xiqun (Michael) Chen, Ph.D. [email protected]Author Affiliations
Publication: CICTP 2020
ABSTRACT
Ridesplitting optimization is one of the hot issues in the studies of on-demand ride services. An efficient ridesplitting optimization model can provide an insightful basis for the platform’s decision-making and management. In reality, on-demand ride service orders include pre-trip reservation orders and real-time orders. This paper proposes a grouping approach to ridesplitting optimization for pre-trip reservation orders in a large-scale urban road network. To improve the ridesplitting rate, we combine reservation orders into travel groups which can be dispatched to vehicles and model this process as an integer linear programming problem. Both CPLEX and a greedy algorithm are used to solve the problem and get the travel groups. Besides, we adopt the CPLEX to solve the dispatching problem between vehicles and travel groups by minimizing the total waiting time of passengers. Finally, the proposed approach is applied to a numerical experiment in a large-scale network based on real-world trip order data of DiDi Chuxing. The results show that our model can effectively improve the ridesplitting rate.
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© 2020 American Society of Civil Engineers.
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Published online: Aug 12, 2020
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1College of Civil Engineering and Architecture, Zhejiang Univ., 866 Yuhangtang Rd., Hangzhou 310058, China. Email: [email protected]
2College of Civil Engineering and Architecture, Zhejiang Univ., 866 Yuhangtang Rd., Hangzhou 310058, China. Email: [email protected]
3College of Civil Engineering and Architecture, Zhejiang Univ., 866 Yuhangtang Rd., Hangzhou 310058, China. Email: [email protected]
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Terms of Use: ASCE Library Cards are for individual, personal use only. Reselling, republishing, or forwarding the materials to libraries or reading rooms is prohibited.