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Path controlling of automated vehicles for system optimum on transportation networks with heterogeneous traffic stream

机译:异构交通运输网络上用于系统优化的自动车辆路径控制

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In the future, when traffic streams comprise a mix of conventional and automated vehicles (AVs), AVs may be employed as mobile actuators to regulate or manage traffic flow across an urban road network to enhance its performance. This paper develops a path-control scheme to achieve the system optimum (SO) of the network by controlling a portion of cooperative AVs (CAVs) as per the SO routing principle. A linear program is formulated to delineate the scheme and determine the minimum control ratio (MCR) of CAVs to achieve SO. The properties of the MCR are mathematically and numerically investigated. Numerical examples based on real-world networks reveal that the SO of most of the tested networks can be achieved with an MCR below 23%. Considering the low market penetration of AVs at early stages of their deployment, we further investigate a joint path-based control and pricing scheme to replicate SO. Numerical examples demonstrate the remarkable synergy of these combined instruments on reducing the MCR with little collected tolling revenue.
机译:将来,当交通流包括传统车辆和自动驾驶车辆(AV)的混合时,AV可用作移动执行器,以调节或管理跨城市道路网络的交通流量,以增强其性能。本文提出了一种路径控制方案,通过按照SO路由原理控制部分协作式AV(CAV)来实现网络的系统最佳(SO)。制定了一个线性程序来描述该方案并确定CAV的最小控制比(MCR)以实现SO。对MCR的特性进行了数学和数值研究。基于实际网络的数值示例表明,MCR低于23%可以实现大多数测试网络的SO。考虑到AV在其部署的早期阶段市场渗透率较低,我们进一步研究了基于路径的联合控制和定价方案来复制SO。数值算例表明,这些组合工具在减少通行费收入的同时减少了MCR,具有显着的协同作用。

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