摘要
针对传统人工势场算法在解决无人驾驶汽车换道轨迹规划过程中存在的不足,提出一种基于势能重构人工势场(PER-APF)的无人驾驶汽车换道轨迹规划算法;首先,建立了具有斥力区分的道路边界约束条件和多约束换道轨迹规划模型,通过判断障碍车辆与道路边沿的距离来保证换道过程的安全性与有效性;其次,提出了基于势能重构的改进APF算法,通过构建虚拟区域以及重构物理势能力场,有效地解决了目标不可达以及局部最优问题;仿真结果表明,所设计的PER-APF算法能够快速有效地为无人驾驶汽车规划一条安全合理的换道轨迹。
In order to solve the limitation problem of traditional artificial potential field algorithm in lane changing trajectory planning of driverless vehicle,a algorithm for the lane changing trajectory planning is proposed based on the potential energy reconstruction and artificial potential field(PER-APF)algorithm.Firstly,the road boundary constraints with repulsive force differentiation and the lane changing trajectory planning model with the multiple constraints are established.By judging the distance between obstacle vehicles and road edges,the safety and effectiveness of vehicle lane changing process are ensured.In addition,through the constructed virtual circular area and the reconstructed physical potential energy field,the PER-APF algorithm can solve the problem of the unreachable target and the local optimization effectively.The simulation results show that the PER-APF algorithm can plan a reasonable lane change trajectory for driverless vehicle quickly and effectively.
作者
胡丹丹
张琪
HU Dandan;ZHANG Qi(Civil Aviation University of China,Robotics Institute,Tianjin 300300,China)
出处
《计算机测量与控制》
2022年第6期229-234,241,共7页
Computer Measurement &Control
基金
天津市科技计划项目(17ZXHLGX00120)
中央高校基本科研业务费(3122017003)。
关键词
无人驾驶汽车
势能重构
人工势场算法
车道变换
轨迹规划
driverless vehicle
PER(potential energy reconstruction)
APF(artificial potential field)algorithm
lane changing
trajectory planning
