摘要：

为提高车辆在无信号交叉路口的通行效率，以车辆加速度变化率和目标车辆通行时间为目标，提出一种车路协同下无信号交叉路口车辆的通行策略。通过建立车路协同场景，划分动态冲突区域和静态冲突区域，定义模型输入参数，构建车辆通行顺序模型和车辆运动状态控制模型，并通过SIMULINK进行仿真，验证模型有效性。实验结果表明，采用该模型后，在常见交通场景中，车辆减速阶段加速度最大变化率平均减少17.27%，车辆加速度变化幅度平均减少37.06%，最大加速度平均降低37.53%，通行时间平均减少41.33%；在特殊交通场景中，车辆减速阶段加速度最大变化率平均减少45.95%，车辆加速度变化幅度平均减少38.89%，最大加速度平均降低48.2%，通行时间平均可减少44.31%；另外，与同类算法优化率相比，该策略模型的平均通行时间和平均车速分别优化42.82%和45.8%，优化效果显著，且两项指标更为均衡，同时车辆速度无频繁波动，乘坐舒适性更佳。因此，在较小牺牲部分车辆舒适性能的条件下，该策略模型大幅提升了整体通行效率。

关键词: 车路协同, 通行策略, 冲突区域, 模糊控制, 决策模型

Abstract:

This study proposes a traffic strategy to improve the efficiency of vehicles passing through unsignalized intersections under vehicle-infrastructure cooperation, with the objectives of reducing vehicle acceleration change rate and target vehicle travel time. The study establishes a vehicle road collaboration scenario, divides dynamic conflict areas and static conflict areas, defines model input parameters, constructs a vehicle traffic sequence model and vehicle motion state control model, and verifies the effectiveness of the models through SIMULINK simulation. In common and special traffic scenarios, the strategy reduces the average maximum acceleration change rate during the vehicle deceleration phase by 17.27% and 45.95%, average amplitude of vehicle acceleration change by 37.06% and 38.89%, average maximum acceleration by 37.53% and 48.2%, and average travel time by 41.33% and 44.31%, respectively. In addition, compared to similar algorithms in the literature, this strategy optimizes the average travel time by 42.82% and average vehicle speed by 45.8%. The optimization effect is significant, and both indicators are more balanced. Simultaneously, the vehicle speed does not fluctuate frequently, and the ride comfort improves. Therefore, this strategy significantly improves overall traffic efficiency without much sacrifice to the comfort performance of partial vehicles.

Key words: vehicle-infrastructure cooperation, traffic strategy, conflict areas, fuzzy control, decision-making model