Reinforcement Learning for Ridesharing: An Extended Survey [article]

Zhiwei Qin, Hongtu Zhu, Jieping Ye
2022 arXiv   pre-print
In this paper, we present a comprehensive, in-depth survey of the literature on reinforcement learning approaches to decision optimization problems in a typical ridesharing system. Papers on the topics of rideshare matching, vehicle repositioning, ride-pooling, routing, and dynamic pricing are covered. Most of the literature has appeared in the last few years, and several core challenges are to continue to be tackled: model complexity, agent coordination, and joint optimization of multiple
more » ... s. Hence, we also introduce popular data sets and open simulation environments to facilitate further research and development. Subsequently, we discuss a number of challenges and opportunities for reinforcement learning research on this important domain.
arXiv:2105.01099v6 fatcat:remvu6ozxna37n6zwoqda6dijm