Congestion-Aware Cooperative Adaptive Cruise Control for Mitigation of Self-Organized Traffic Jams
Congestion-Aware Cooperative Adaptive Cruise Control for Mitigation of Self-Organized Traffic Jams
复制标题
用于缓解自组织交通拥堵的拥堵感知协作自适应巡航控制
DOI：
10.1109/tits.2021.3059237
复制
发表时间：
2022
影响因子：
8.5
通讯作者：
Kshitij Jerath
中科院分区：
文献类型：
--
作者：
Taehooie Kim;Kshitij Jerath
以前的工作表明，自适应巡航控制(ACC)可以通过提高首次出现拥堵的临界车辆密度来改善交通流量。然而，这些工作也表明，配备ACC的车辆具有中到高渗透率的交通更容易由于车辆人口统计的扰动而形成自组织幻影交通拥堵。在这项工作中，我们提出了一种拥塞感知的协作式自适应巡航控制(CACC)算法，以解决在提高临界密度和降低拥堵敏感度之间的权衡，这些目标是在配备ACC的车辆较高的渗透率下观察到的。拥堵感知CACC算法模仿通用汽车的跟车模型，其中驾驶员的敏感度根据连接的车辆下游的普遍拥堵状态(或交通拥堵程度)而改变。使用主方程对自组织交通拥堵的动力学进行了建模。结果表明，拥塞感知CACC算法可以提高有效临界密度，导致较高的交通流量，同时也降低了密度范围内车辆密度扰动对配备ACC车辆的不利影响的敏感性。
Previous work has shown that Adaptive Cruise Control (ACC) can improve traffic flow by raising the critical vehicular density at which congestion first appears. However, these works also indicate that traffic with medium-to-high penetration of ACC-equipped vehicles is more susceptible to the formation of self-organized phantom traffic jams induced by perturbations in vehicular demographics. In this work, we propose a congestion-aware Cooperative Adaptive Cruise Control (CACC) algorithm as an alternative to address the trade-off between competing goals of raising the critical density, and reducing susceptibility to congestion observed at higher penetration rates of ACC-equipped vehicles. The congestion-aware CACC algorithm is modeled after the General Motor’s car-following models, wherein the driver sensitivity is altered based on the prevailing congestion state (or traffic jam size) downstream of the connected vehicle. The dynamics of the self-organized traffic jam are modeled using a master equation. Results indicate that the congestion-aware CACC algorithm can increase the effective critical density leading to higher traffic flows, while also reducing the susceptibility to perturbations in vehicle demographics in the density range that adversely affects ACC-equipped vehicles.