[1]张三川,明珠.基于主动安全的改进人工势场局部路径规划研究[J].郑州大学学报(工学版),2021,42(5):32-36.[doi:10.13705/j.issn.1671-6833.2021.05.008]
　ZHANG Sanchuan,MING Zhu.Research on Improved Local Path Planning of Artificial Potential Field Based on Active Safety[J].Journal of Zhengzhou University (Engineering Science),2021,42(5):32-36.[doi:10.13705/j.issn.1671-6833.2021.05.008]

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基于主动安全的改进人工势场局部路径规划研究()

分享到：

《郑州大学学报(工学版)》[ISSN:1671-6833/CN:41-1339/T]

卷:

42

期数:

2021年5期

页码:

32-36

栏目:

出版日期:

2021-09-10

文章信息/Info

Title:

Research on Improved Local Path Planning of Artificial Potential Field Based on Active Safety

作者:

张三川,明珠

郑州大学 机械与动力工程学院，河南 郑州 450001

Author(s):

ZHANG Sanchuan, MING Zhu

School of Mechanic al and Power Engineering， Zhengzhou University， Zhengzhou 450001， China

关键词:

智能网联车辆; 局部路径规划; 改进人工势场; 局部极小值; 附加力

Keywords:

intelligent network vehicle;  local path planning;  improved artificial potential field;  local minimum;  additional force

DOI:

10.13705/j.issn.1671-6833.2021.05.008

文献标志码:

A

摘要:

局部路径规划是智能驾驶车辆主动安全保障的关键。 为解决传统人工势场方法存在的局部极小值与目标不可达的理论问题,基于毫米波雷达对障碍物方位角 θ0 的测定功能,引入实验车与障碍物距离作为斥力调节因子,确保目标点附近的斥力不至于过大,同时引入方向角为 θ( >θ₀ ) 并受控于目标距离 k·S(M,Mg )的目标引力的附加力,使实验车确定能脱离极小值点,从而改进了传统人工势场的局部路径规划方法。 运用 MATLAB 软件数值仿真,实验结果表明:当附加力增益系数 k 为 5 ~7 时,即可获得稳定安全的局部规划路径,未出现极小值点；改进人工势场斥力峰值的变化随障碍物与路径规划起始点之间的距离增加而呈现出指数级减小的规律,即实验车在目标点附近所受斥力衰减为 0,实现了目标可达；单步计算时长较传统人工势场的略有增加,但其规划路径不再出现震荡区间,仿真时长均为 0.26 s,时效性基本相同,而且安全性指标还由传统人工势场法的 0.018 8 提升到 0.305 0,验证了改进人工势场局部路径规划方法的可行性。

Abstract:

Local path planning is the key to the active safety of intelligent driving vehicles. In order to solve the theoretical problems of local minimum and unreachable target existing in the traditional artificial potential field method, in this paper the distance between the experimental vehicle and the obstacle is introduced as the repulsive force regulator based on the measurement function of the azimuth(θ0)of the obstacle by millimeter-wave radar, which makes sure that the repulsive forces near the target point are not too large. At the same time, the additional force of target gravity is introduced with direction angle θ (>θ0) and controlled by target distance k·S(M,Mg), which makes experimental vehicle break away from the minimum point. The numerical simulation results of MATLAB show that: when the gain coefficient of the additional force (k) is between 5～7, a stable and safe local planning path can be obtained, and no minimum point appears. The variation of the peak value of repulsive force and resultant force in the improved artificial potential field decreases exponentially with the increase of the distance between the obstacle and the starting point of path planning, the repulsive force of the experimental vehicle near the target point attenuates to 0, and the target is reachable; Compared with the traditional artificial potential field, the single-step calculation time is slightly increased, but there is no oscillation interval for the planned path. The simulation time is 0.26 s, and the timelessness is basically the same. The safety index is increased from 0.018 8 of the traditional artificial potential field method to 0.305 0, which greatly improves the safety of local path planning.

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