[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(05):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(05):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05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;

Author(s):

ZHANG Sanchuan;  MING Zhu

School of Mechanical and Power Engineering, Zhengzhou University;

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:

为提高智能车辆在局部路径规划中的能力，在传统人工势场基础上，通过引入附加力与调节因子来解决存在的局部极小值与目标不可达的问题，提出了一种基于主动安全的改进人工势场局部路径规划算法，并构建了改进人工势场评价指标与模型。Matlab仿真结果表明：两种算法均用时0.26s，改进人工势场算法将安全指标由0.0188提升至0.305，本算法在不影响时效性的前提下大大提高了局部路径规划的安全性。

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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