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Journal Article
人工和自动混合驾驶环境下的最优道路拥堵收费模型
2023
Overview
为了得到自动驾驶汽车(CAV)与人工驾驶汽车(HDV)并存条件下最优道路收费方案,针对CAV在道路上的通行能力,特别是对道路容量产生的影响进行量化分析,获得道路容量与HDV流量和CAV流量之间的非线性关系.然后,对传统的美国公路局路阻函数进行改进,并基于改进后的路阻函数,建立系统最优(system optimal,SO)流量分配模型,对不同CAV占比条件下和不同HDV与CAV安全车距比值条件下的交通流进行系统最优分配.采用Frank-Wolfe算法,对SO模型进行求解,并考虑因HDV而产生的额外道路出行成本对不同条件下系统最优分配结果的差异性进行比较.基于最优收费理论,针对不同规模道路网制定相应的收费方案.最后,将模型与算法应用到Nguyen-Dupuis交通网络中.结果表明,在HDV与CAV并存条件下,以系统最优分配结果下的边际成本进行收费是道路交通系统最优拥堵收费方案,可作为HDV与CAV并存条件下道路收费方案设计的依据.
Publisher
北京交通大学综合交通运输理论交通运输行业重点实验室,北京 100044%北京交通大学先进轨道交通 自主运行全国重点实验室,北京 100044
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