基于驾驶员类型分析的智能车辆交叉口行为决策

Decision Making for Intelligent Vehicles Based on Driver Type Analyzing in an Intersection

提出一种基于车辆行为交互的两阶段智能车辆交叉口行为决策方法.第一阶段通过基于模糊逻辑的驾驶员激进程度判别模型,判断交叉口其他车辆的驾驶员类型;第二阶段通过驾驶员激进程度与碰撞到达时间(TTC)进行行为决策.使用Prescan和Matlab/Simulink进行交叉口联合仿真.结果表明,该方法可以使智能车辆安全有效通过有其他车辆通行的交叉路口.

A two-stage method of intelligent vehicle（IV） decision making for traffic interaction in an intersection was proposed in this paper. In the first stage, a driver type recognition model was presented based on fuzzy logic to get the aggressive rate of social vehicles. In the second stage, a rule-based decision-making algorithm was used to generate the best behavior for IV based on vehicle＇s aggressive ratio and time to collision（TTC）. Finally, a Co-simulation with Prescan and Matlab/Simulink was performed to verify the algorithm. The results show that the method could lead IV get through intersection safely and efficiently.