基于强化学习的危化品运输路径选择博弈分析

危化品运输企业常常为追求自身利益最大化而忽略运输安全问题,导致危化品运输安全事故频发.为提高危化品运输安全性,除了行政监管,政府还通过路径税收政策影响危化品运输路径,从而避免安全事故发生.本文根据危化品运输企业具有自主学习的特性,引入强化学习相关理论方法,建立了路径税收政策下基于强化学习的危化品运输路径选择的演化博弈模型;同时通过理论分析及仿真算例,对路径税收政策下危化品运输路径选择问题进行研究.仿真结果显示,路径税收政策可促使危化品运输企业选择收税路段,进而降低危化品运输风险,对于提高国家危化品安全运输管理具有实际意义.

Game analysis of hazardous chemicals transport route selection based on reinforcement learning-model

Many hazardous chemicals transportation accidents occur in China in recent years. One of the reasons is that the transport company often ignores the transportation safety when transporting the hazardous chemicals. In order to improve the transportation safety, one of the effective policies for the government is to set the tax policy for the different routes. In this paper, the model of hazardous chemicals transport route selection with tax policy is established. Reinforcement learning is introduced into this paper to model the behavior of transport company. The simulation example illustrated that the transport company is willing to choose the road with tax policy, which reduces the risk of hazardous chemicals transport.