论文标题
混合交通流量中的领先巡航控制：系统建模，可控性和字符串稳定性
Leading Cruise Control in Mixed Traffic Flow: System Modeling, Controllability, and String Stability
论文作者
论文摘要
连接和自动驾驶汽车（CAVS）具有改善道路运输系统的巨大潜力。骑士的纵向控制的大多数现有策略都集中在下游的交通状况上，但忽略了骑士行为对上游交通流的影响。在本文中，我们介绍了领先的巡航控制（LCC）的概念，其中骑士维护着适应其先前车辆状态的汽车跟随操作，并旨在领导其以下车辆的运动。具体而言，通过控制CAV，LCC旨在减弱下游的交通扰动，并积极地平稳上游交通流量。我们首先介绍LCC的动态建模，重点关注三种基本场景：跟随汽车，自由驾驶和连接的巡航控制。然后，对可控性，可观察性和从头到尾的字符串稳定性的分析揭示了LCC在改善混合流动流量性能方面的可行性和潜力。广泛的数值研究表明，当将车辆的信息纳入骑士的控制中时，骑士在消散交通扰动方面的能力将进一步加强。
Connected and autonomous vehicles (CAVs) have great potential to improve road transportation systems. Most existing strategies for CAVs' longitudinal control focus on downstream traffic conditions, but neglect the impact of CAVs' behaviors on upstream traffic flow. In this paper, we introduce a notion of Leading Cruise Control (LCC), in which the CAV maintains car-following operations adapting to the states of its preceding vehicles, and also aims to lead the motion of its following vehicles. Specifically, by controlling the CAV, LCC aims to attenuate downstream traffic perturbations and smooth upstream traffic flow actively. We first present the dynamical modeling of LCC, with a focus on three fundamental scenarios: car-following, free-driving, and Connected Cruise Control. Then, the analysis of controllability, observability, and head-to-tail string stability reveals the feasibility and potential of LCC in improving mixed traffic flow performance. Extensive numerical studies validate that the capability of CAVs in dissipating traffic perturbations is further strengthened when incorporating the information of the vehicles behind into the CAV's control.
