Optimal passenger-seeking policies on E-hailing platforms using Markov decision process and imitation learning-Reference-Cited by-同舟云学术

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Optimal passenger-seeking policies on E-hailing platforms using Markov decision process and imitation learning

Published:2020-02 Issue: Volume:111 Page:91-113
ISSN:0968-090X
Container-title:Transportation Research Part C: Emerging Technologies
language:en
Short-container-title:Transportation Research Part C: Emerging Technologies

Author:

Shou Zhenyu,Di Xuan,Ye Jieping,Zhu Hongtu,Zhang Hua,Hampshire Robert

Funder

Didichuxing

Publisher

Elsevier BV

Subject

Computer Science Applications,Transportation,Automotive Engineering,Civil and Structural Engineering

Reference55 articles.

1. What drives the use of ridehailing in California? Ordered probit models of the usage frequency of Uber and Lyft;Alemi;Transp. Res. Part C: Emerg. Technol.,2019

2. Predicting real-time surge pricing of ride-sourcing companies;Battifarano;Transp. Res. Part C: Emerg. Technol.,2019

3. Dynamic Programming and Optimal Control;Bertsekas,2000

4. A unified equilibrium framework of new shared mobility systems;Di;Transp. Res. Part B: Methodol.,2019

5. Hybrid extended kalman filtering approach for traffic density estimation along signalized arterials: Use of global positioning system data;Di;Transp. Res. Rec.,2010

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