Path controlling of automated vehicles for system optimum on transportation networks with heterogeneous traffic stream
Path controlling of automated vehicles for system optimum on transportation networks with heterogeneous traffic stream
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DOI：
10.1016/j.trc.2019.11.017
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发表时间：
2020
影响因子：
8.3
通讯作者：
Zhibin Chen;Xi Lin;Yafeng Yin;Meng Li
中科院分区：
文献类型：
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作者：
Zhibin Chen;Xi Lin;Yafeng Yin;Meng Li
在未来，当交通流包括传统和自动车辆（AV）的混合时，AV可以用作移动的致动器来调节或管理城市道路网络上的交通流以增强其性能。本文提出了一种路径控制方案，通过控制一部分协同无人机（CAV），按照SO路由原则，实现网络的系统最优（SO）。用线性规划的方法来描述控制方案，并确定CAV的最小控制比（MCR）以实现SO。的MCR的性能进行了数学和数值研究。基于真实网络的数值算例表明，大多数测试网络的SO可以在MCR低于23%的情况下实现。考虑到无人驾驶汽车在部署初期的市场渗透率较低，我们进一步研究了一种基于路径的联合控制和定价方案来复制SO。数值例子表明，显着的协同作用，这些组合的工具，以减少MCR收取很少的通行费收入。
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.