【作者】 何旭东； 孙棣华； 赵敏； 王荣斌； 唐毅； 代振；

【Author】 Xudong He;Dihua Sun;Min Zhao;Rongbin Wang;Yi Tang;Zhen Dai;School of Automation, Chongqing University;Chongqing Expressway Group Co., Ltd;

【机构】 重庆大学自动化学院； 重庆高速公路集团有限公司；

【摘要】 受交通信号的影响,道路交通连续车群呈现出周期性驶停和车辆能耗增加。在混合交通条件下,充分利用网联自动驾驶汽车(CAV)的联通性和可控性,在近信号区根据信号周期和相位对车群进行分群协同控制,有助于改善上述问题。为此,论文基于信息物理系统(CPS)视角,提出一种混行车辆的分群协同控制策略。利用CAV获取交通信号状态信息,并依据其在车群中的位置,结合绿灯周期最大通行能力,进行车群内CAV头车的速度规划。仿真结果表明,该策略可以显著减少车辆的频繁启停行为,随着CAV渗透率的增加,可进一步降低车群整体能耗。更多还原

【Abstract】 Due to traffic signals, the continuous traffic flow shows periodic stop and go, leading to increased energy consumption. In mixed traffic, it will help to solve the above problems if we can make full use of the connectivity and controllability of the network connected autonomous vehicle(CAVs) by coordinating the vehicle groups with signal cycles and phase in the vicinity of traffic signals.Therefore, this paper proposes a grouping strategy for mixed traffic from the perspective of Cyber-Physical Systems(CPS), utilizing CAVs to obtain information about traffic signals and considering their position in the vehicle group and the maximum capacity during the light cycle, the speed planning for the leading CAV in the group is conducted. The simulation results show that this strategy can significantly reduce the frequent start stop behavior of vehicles, and as the penetration rate of CAV increases, it can further reduce the overall energy consumption of the vehicle group.更多还原