基于单亲遗传算法的无人驾驶汽车主动避撞方法

Active collision avoidance method of driverless vehicle based on partheno genetic algorithm

为有效提升无人驾驶汽车的主动安全性,提出基于单亲遗传算法的无人驾驶汽车主动避撞方法。利用归一化处理方位角评估函数构建无人驾驶汽车动力学模型。根据行为轨迹预测结果提前采取预制动,并以初始点至终点路径最短为目标,引入单点基因复制策略实施遗传操作,获取无人驾驶汽车主动避撞最优解。仿真结果表明:该方法可在紧急工况下规划出可靠的转向避撞路径,车辆状态参数平稳,路径偏差小,对不同车速及转向路径均具备较强鲁棒性。

To effectively improve the active safety of autonomous vehicles,a single parent genetic algorithm based active collision avoidance method for autonomous vehicles is proposed.Construct a dynamic model for autonomous vehicles using normalized azimuth evaluation functions.Based on the predicted behavior trajectory,pre braking is taken in advance,and a single point gene replication strategy is introduced to implement genetic operations with the goal of minimizing the path from the initial point to the endpoint,in order to obtain the optimal solution for autonomous vehicle active collision avoidance.The simulation results show that this method can plan a reliable turning collision avoidance path under emergency conditions,with stable vehicle state parameters,small path deviation,and strong robustness to different vehicle speeds and turning paths.