Cooperative Multi-Lane Shock Wave Detection and Dissipation via Local Communication

Nilesh Suriyarachchi, Christos N. Mavridis, J. Baras
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引用次数: 1

Abstract

Traffic shock waves are well-known naturally occurring phenomena that lead to unnecessary congestion in highway networks. Introducing connected autonomous vehicles (CAVs) to highways of human-driven vehicles (HDVs) allows for the development of traffic control schemes that can mitigate the effects of the shock waves. In this work, we propose a shock wave detection algorithm based on communication between CAVs with local traffic information. The proposed methodology is suitable for multi-lane mixed traffic highways of arbitrary structure, i.e., it is not limited to closed-circuit ring roads. We show that the detection information can be used to design a class of proactive shock wave mitigating CAV controllers. The choice of the controller can depend on design parameters such as the aggressiveness of the driving behavior allowed. We also demonstrate the importance of the positioning of autonomous agents in multi-lane scenarios. The shock wave dissipation efficiency is evaluated on a three lane highway loop using realistic traffic simulations and low CAV penetration levels.
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基于局部通信的协同多车道冲击波检测与耗散
交通冲击波是众所周知的自然现象,它会导致公路网不必要的拥堵。将联网自动驾驶汽车(cav)引入人类驾驶汽车(HDVs)的高速公路,可以开发交通控制方案,减轻冲击波的影响。在这项工作中,我们提出了一种基于自动驾驶汽车与当地交通信息通信的冲击波检测算法。该方法适用于任意结构的多车道混合交通公路,即不局限于环形封闭道路。结果表明,该检测信息可用于设计一类主动减震CAV控制器。控制器的选择可以取决于设计参数,例如允许的驾驶行为的侵略性。我们还证明了自主智能体在多车道场景中定位的重要性。在低CAV侵彻水平下,对三车道环线公路的冲击波耗散效率进行了仿真研究。
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