基于风险势场的网联自主车辆换道行为建模

Modeling of Lane Change Behavior of Connected Autonomous Vehicles Based on Risk Potential Field

为提高智能网联环境下网联自主车辆的换道安全,针对网联自主车辆环境感知及实时通讯的特点,以势场理论为基础,分析车辆不同方向所面临风险变的差异性,对动态车间距进行修正,构建车辆风险势场模型,将网联自主车辆驾驶过程中所面临的风险进行量化,以此为基础建立网联自主车辆安全换道距离模型,反映不同运动状态的换道车辆所需要的安全换道距离的变化趋势。对模型进行数值模拟分析,结果表明:当前车道和目标车道上车辆的运动状态直接影响换道时所需要的安全距离的大小。可见车辆进行换道操作时需调整自身的运动状态来改变风险势场的分布情况,避免与其他车辆的风险势场发生冲突,影响行车安全性。

In order to improve the lane change safety of networked autonomous vehicles in the intelligent networked environment,according to the characteristics of environment perception and real-time communication of networked autonomous vehicles,based on the potential field theory,the differences of risk changes faced by vehicles in different directions were analyzed,the dynamic vehicle spacing was corrected,the vehicle risk potential field model was constructed,and the risks faced by the networked autonomous vehicles in the driving process were quantified.Numerical simulation analysis of the model show that the motion state of the vehicle in this lane and the target lane directly affects the safety distance required when changing lanes.It can be seen that the vehicle needs to adjust its own motion state to change the distribution of the vehicle's risk potential field when changing lanes,so as to avoid conflicts with the risk potential field of other vehicles and affect driving safety.