异质交通流下高速公路CAV合流次序优化与轨迹规划方法  

Merging order optimization and trajectory planning methods for highway CAVs in heterogeneous traffic flow

作　　者：程国柱 陈永胜 王文志 徐亮[2] CHENG Guozhu;CHEN Yongsheng;WANG Wenzhi;XU Liang(School of Civil Engineering and Transportation,Northeast Forestry University,Harbin 150040,China;School of Civil Engineering,Changchun Institute of Technology,Changchun 130012,China)

机构地区：[1]东北林业大学土木与交通学院,哈尔滨150040 [2]长春工程学院土木工程学院,长春130012

出　　处：《北京交通大学学报》2025年第1期100-109,共10页JOURNAL OF BEIJING JIAOTONG UNIVERSITY

基　　金：国家自然科学基金(52378433);中央高校基本科研业务费专项资金(2572023CT21)。

摘　　要：为提升高速公路合流区交通运行效率及驾乘人员舒适性,在保障安全的前提下,面向人工驾驶车辆(Human Driven Vehicles,HDV)和智能网联车辆(Connected and Autonomous Vehicles,CAV)混行的异质交通流环境,提出高速公路CAV合流次序优化与轨迹规划方法.首先,以车辆通行时间和延误作为合流区交通运行效率表征指标,建立合流次序优化函数,采用并调整蒙特卡洛树搜索(Monte Carlo Tree Search,MCTS)算法,获得最优合流次序;其次,依据合流次序,建立最小化加速度和急动度的CAV合流轨迹规划(Minimize Acceleration and Jerk Trajectory Planning,MAJTP)函数,运用最优控制理论,求解车辆纵向最优轨迹解析解,进而形成高速公路合流区CAV协同控制方法;最后,联合运用SUMO软件和PYTHON库,对本文所提方法进行交通仿真验证.仿真结果表明:在CAV渗透率分别为0.2、0.4、0.6和0.8时,相较于先进先出(First In First Out,FIFO)算法,基于MCTS算法的合流次序优化方法累积延误分别降低5.75%、8.84%、12.24%和11.06%;相较于最小化加速度的车辆轨迹规划(Minimize Acceleration Trajectory Planning,MATP)方法,MAJTP方法平均急动度更趋近于零,驾乘人员舒适性有所提升,验证了方法的有效性.研究成果可为高速公路合流区交通运行管控研究提供理论支持.To enhance traffic operation efficiency and improve driver and passenger comfort in highway merging areas while ensuring safety,this study proposes an optimization method for highway merging order and trajectory planning for Connected and Autonomous Vehicles(CAVs)in a heterogeneous traffic flow environment where Human Driven Vehicles(HDVs)and CAVs coexist.First,vehicle travel time and delay are used as performance indicators to characterize traffic operation efficiency in the merging area,and a merging order optimization function is established.The Monte Carlo Tree Search(MCTS)algorithm is used and adjusted to determine the optimal merging order.Then,based on the optimized merging order,a CAV merging trajectory planning function,referred to as Minimize Acceleration and Jerk Trajectory Planning(MAJTP),is established.By applying optimal control theory,the analytical solution for the longitudinal optimal trajectory of CAVs is derived,forming a cooperative control strategy for highway merging.Finally,traffic simulations are conducted using the SUMO software and PYTHON libraries to validate the proposed method.Simulation results demonstrate that,at CAV penetration rates of 0.2,0.4,0.6 and 0.8,the MCTS-based merging order optimization method reduces cumulative delay by 5.75%,8.84%,12.24%,and 11.06%,respectively,compared to the First In First Out(FIFO)algorithm.Additionally,compared to the Minimize Acceleration Trajectory Planning(MATP)method,the MAJTP approach results in an average jerk value closer to zero,thereby enhancing ride comfort and verifying the effectiveness of the method.These findings provide theoretical support for traffic management and control strategies in highway merging areas.

关 键 词：交通工程 合流区 合流次序 轨迹规划 蒙特卡洛树搜索 最优控制 

分 类 号：U491[交通运输工程—交通运输规划与管理]