[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,Pearl,Research on improved Local Path Planning of artificial potential Field ba<x>sed 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()
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《郑州大学学报(工学版)》[ISSN:1671-6833/CN:41-1339/T]

卷:
42卷
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 ba<x>sed 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; Pearl;
School of Mechanical and Power Engineering, Zhengzhou University;

关键词:
Keywords:
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:
In order to improve the capability of intelligent vehicles in local path planning, ba<x>sed on the traditional artificial potential field, by introducing additional force and regulators to solve the problem of local minima and unreachable targets, This paper presents an improved artificial potential field local path planning algorithm ba<x>sed on active safety and constructs an improved artificial potential field evaluation index and model . Matlab simulation results show that: Both algorithms take 0.26s while improved artificial potential field algorithm t o raised the safety index from 0.0188to 0.305.This algorithm greatly improves the safety of local path planning without affecting the timeliness
更新日期/Last Update: 2021-10-11