Abstract:

The traditional autonomous driving vehicles designed the conflict resolution algorithm based on the assumption of the right of way. However, the right of way was not clear in most cases of the mixed traffic of manual and autonomous driving, which will bring great trouble to the decision-making of autonomous vehicles. This paper proposed a conflict resolution optimization method for autonomous vehicles at intersections. The multiobjective optimal control theory was used to plan the speed for the conflicting vehicles, so as to achieve the purpose of cooperative driving. Finally, the simulation experiments of cooperative and non- cooperative conflict resolution were carried out. The results show that the conflict resolution of multi-vehicle cooperative driving can optimize the speed trajectory of vehicles to improve the overall driving efficiency, and the performance of various stakeholders is balanced relatively. Compared with non-cooperative conflict resolution, the time of conflict resolution is shortened, and the average delay per vehicle is reduced by 1~2 s at the intersection, and the average reduction is approximately 5%. The research results can provide a reference for an autonomous cooperative driving when the conflict occurred.

Key words: intelligent transportation, conflict resolution, genetic algorithm, autonomous driving, intersection, multi-vehicle cooperative driving

摘要：

传统自动驾驶车辆以假设通行权为前提设计冲突消解算法，但在无信号交叉口存在道路通行权不明确情况，给自动驾驶车辆决策带来困扰.本文提出基于多车协作优化的无信号交叉口冲突消解方法，将多个自动驾驶车辆看成一个整体，利用多目标优化控制理论，计算分配给相互冲突车辆的期望速度规划，达到协作行驶的目的.设置协作与非协作式冲突消解仿真实验.结果表明：多车协作的冲突消解方法通过优化车辆联合行动，使交叉口车辆整体收益最大，各利益体间的收益更为均衡；与非协作行驶决策相比，冲突消解时间缩短，减少交叉口单车平均延误1~2 s，平均减少量约为5%.本文可为无信号交叉口自动驾驶车辆冲突时自主协同行驶提供参考.

关键词: 智能交通, 冲突消解, 遗传算法, 自动驾驶, 交叉口, 多车协作