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Multiagent Reinforcement Learning-Based Taxi Predispatching Model to Balance Taxi Supply and Demand
2020
Journal of Advanced Transportation
With the improvement of people's living standards, people's demand of traveling by taxi is increasing, but the taxi service system is not perfect yet; taxi drivers usually rely on their operational experience or cruise randomly to find passengers. Without macroguidance, the role of the taxi system cannot be fully utilized. Many scholars have studied taxi behaviors to find better operational strategies for drivers, but their researches rely on local optimization methods to improve the profit of
doi:10.1155/2020/8674512
fatcat:q5wo2ir4b5hoha66ei7wge3nym