车路协同下的无信号交叉口车辆通行调度策略  

Vehicle traffic scheduling strategy at unsignalized intersections under vehicle road coordination

作　　者：张方忆 彭景阳[1] 李磊[1] 王文格[1] Zhang Fangyi;Peng Jingyang;Li Lei;Wang Wenge(College of Mechanical&Vehicle Engineering,Hunan University,Changsha 410082,China)

机构地区：[1]湖南大学机械与运载工程学院,长沙410082

出　　处：《计算机应用研究》2024年第7期2087-2092,共6页Application Research of Computers

摘　　要：无信号交叉口车辆通行调度问题是智能交通领域的研究重点,由于车辆通行顺序决策问题的解空间随着车辆数增加而指数级增长,在保证实时性的同时找到较优通行顺序成为无信号交叉口通行调度的一大问题。针对该问题提出一种基于自适应蒙特卡罗树搜索算法的无信号交叉口车辆通行调度方法,采用分层式框架,上层集中式顺序决策,下层分布式轨迹规划。首先,建立基于冲突点的交叉口模型,将网联车加入到待搜索队列中,根据交叉口中的车辆通行特点设计通行顺序的蒙特卡罗树搜索流程,以总通行时间为指标建立评价函数,然后针对不同交通情景设计自适应探索系数及其他超参数,使算法在求解不同车辆数时以及搜索的不同时期保持最佳状态。轨迹规划环节以加速度二范数为目标函数,以速度、加速度以及始终点位置等为约束,建立最优控制命题求解车辆轨迹。最后,进行实验,结果表明该算法相较于其他算法在数值仿真和微缩平台实验中最大优化幅度分别达到33.42%和38.04%,为无信号交叉口车辆通行调度提供了一个有效解决方案。The vehicle traffic scheduling problem at unsignalized intersections is the research focus in the field of intelligent transportation.Because the solution space of vehicle traffic order decision problem increases exponentially with the increase of the number of vehicles,finding the optimal traffic sequence while ensuring the real-time performance has become a major problem for traffic scheduling at unsignalized intersections.To solve this problem,this paper proposed a vehicle traffic scheduling method at unsignalized intersections based on adaptive Monte Carlo tree search algorithm,which used a hierarchical framework,upper level centralized sequential decision-making,and lower level distributed trajectory planning.Firstly,the intersection model based on the conflict point was established,the connected vehicles were added to the queue to be searched,the Monte Carlo tree search process of the traffic sequence was designed according to the vehicle traffic characteristics in the intersection,the evaluation function was established with the total traffic time as the index,and then the adaptive exploration coefficient and other super parameters were designed for different traffic situations,so that the algorithm could maintain the best state in solving different vehicle numbers and different search periods.In the trajectory planning process,the acceleration two norm was taken as the objective function,and the speed,acceleration and the position of the starting point were taken as constraints to establish the optimal control proposition to solve the vehicle trajectory.Finally,experiments were carried out,and the results show that compared with other algorithms,the maximum optimization amplitude of this algorithm in numerical simulation and micro platform experiment is 33.42%and 38.04%respectively,which provides an effective solution for vehicle traffic scheduling at unsignalized intersections.

关 键 词：智能交通 无信号交叉口车辆通行调度 蒙特卡罗树搜索 智能网联车 微缩平台 

分 类 号：U495[交通运输工程—交通运输规划与管理]