城市环境下无人驾驶车辆驾驶规则获取及决策算法

城市道路多源信息环境下换道行为决策是无人驾驶车辆实现实际道路行驶的关键技术之一.为提取复杂动态环境下驾驶员的换道决策规则，利用PreScan软件搭建虚拟城市道路环境，基于Simulink建立6自由度车辆动力学模型，采用粗糙集提取驾驶员换道行为决策规则.结果表明本车与当前车道车辆的相对速度维持在4~7 m/s、相邻车道空间距离在20~35 m时驾驶员就会进行换道决策.研究结果可以为无人驾驶车辆在线机器学习提供规则知识库，并为进一步深入研究换道行为不确定决策提供理论基础. 

Driving Rule Acquisition and Decision Algorithm to Unmanned Vehicle in Urban Traffic

Lane-changing decision of multi-source information on the urban traffic environment is the key technology to unmanned vehicles achieve actual road driving, to extract the driver''s lane-changing decision rules in the complex and dynamic environment, firstly, PreScan software was used and virtual urban traffic environment was built, 6-DOF vehicle dynamics model was based on the Simulink, the decision rules of driver lane-changing behavior was extracted through rough set. The results show that the relative speed of the experimental vehicle and leading vehicle maintains at around 4~7 m/s, and when the space distance between adjacent cars reaches 20~35 m, the driver begins to implement lane-changing, the results provide driving knowledge for unmanned vehicles online machine learning and theoretical basis for the depth study of lane-changing behavior of uncertain decision-making.