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基于改进人工势场法前车切入场景下的主动避撞路径规划

Active obstacle avoidance path planning based on improved artificial potential field method in front vehicle cut-in scenario

  • 摘要: 为保证自动驾驶汽车在前车切入场景下转向避撞的主动安全性,提出了基于改进人工势场法的主动避撞路径规划方法.在传统人工势场法的基础上,改变了斥力势场函数,通过增加道路边界斥力势场,保证车辆避撞结束后仍保持直线行驶,同时,引进速度调节因子建立动态障碍物势场,解决人工势场在动态障碍物下的避撞路径规划.利用MATLAB与Carsim的联合仿真在前车切入这一动态场景下对所提出的路径规划方法进行仿真试验.结果表明:利用改进后的算法可获得平滑且安全的局部避撞路径,自动驾驶汽车沿该路径行驶时满足车辆动力学要求.

     

    Abstract: To ensure the active safety of self-driving cars steering to avoid collisions in the front vehicle cut-in scenario, an active obstacle avoidance path planning method was proposed based on the improved artificial potential field method. Based on the traditional artificial potential field method, the repulsive potential field function was changed to ensure that the vehicle drived in a straight line after the end of collision avoidance by increasing the road boundary repulsive potential field. The speed adjustment factor was introduced to establish dynamic obstacle potential field to solve the artificial potential field for collision avoidance path planning under dynamic obstacles. The proposed path planning method was simulated using the joint simulation of MATLAB and Carsim in the dynamic scenario for the front vehicle cut-in. The results show that the smooth and safe localized collision avoidance path can be obtained by the improved algorithm, and the vehicle dynamics requirements are met when the self-driving car travels along this path.

     

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