欢迎访问《汽车安全与节能学报》，
汽车安全与节能学报

汽车安全与节能学报 ›› 2025, Vol. 16 ›› Issue (3): 496-503.DOI: 10.3969/j.issn.1674-8484.2025.03.016

• 智能驾驶与智慧交通 • 上一篇    

考虑能耗及稳定性的无人驾驶车辆越野环境路径规划

陈晓峰1(), 王兰文2,*(), 马果1, 张垒2, 鲍家定2, 景晖2   

  1. 1.柳州五菱汽车工业有限公司，柳州 545007，中国
    2.桂林电子科技大学 机电工程学院，桂林 541004，中国
  • 收稿日期:2024-12-21 修回日期:2025-04-15 出版日期:2025-06-30 发布日期:2025-07-01
  • 通讯作者: 王兰文，副教授。E-mail：wanglanwen2024@163.com。
  • 作者简介:陈晓峰（1974—），男（汉），广东，高级工程师。E-mail：cxf@wuling.com.cn。
  • 基金资助:
    国家自然基金项目(52262052);广西科技重大专项项目(桂科AA23062003);广西科技重大专项项目(桂科AA24263070)

Energy and stability aware path planning for autonomous vehicles in off road environments

CHEN Xiaofeng1(), WANG Lanwen2,*(), MA Guo1, ZHANG Lei2, BAO Jiading2, JING Hui2   

  1. 1. Liuzhou Wuling Automobile Industry Co., Ltd, Liuzhou 545007, China
    2. Guilin University of Electronic Technology, Guilin 541004, China
  • Received:2024-12-21 Revised:2025-04-15 Online:2025-06-30 Published:2025-07-01

RichHTML

9

PDF

55

摘要：

在无人驾驶车辆越野环境下的路径规划中，为减少能耗，提高侧向行驶稳定性，对传统A*算法的环境建模方式及代价函数进行改进。对数字高程地图（DEM）数据进行Kriging插值及坡度计算，根据车辆性能生成车辆可通行地图；在传统A*算法代价函数中加入车辆俯仰角、侧倾角影响因子，设计新的代价函数；在真实环境地图上，仿真对比了本文算法、传统A*算法及考虑高度的A*算法（HA*算法）。 结果表明：在越野环境中，与传统A*算法及HA*算法规划路径相比，本文算法规划路径的路径长度最多增加7.3%，能耗最多降低10.1%；针对一般性能车辆，行驶俯仰角低于40%；针对高性能车辆，行驶俯仰角低于60%；且两种性能车辆侧倾角均低于36%。因此，应用本文算法可以减少能量消耗，提高车辆侧向行驶稳定性。

关键词: 无人驾驶车辆, 路径规划, 越野环境, 改进A*算法

Abstract:

The traditional A* algorithm was modified in terms of environment modeling and cost function to reduce energy consumption and improve lateral driving stability in off-road path planning for autonomous vehicles. The Digital Elevation Model (DEM) data were processed using the Kriging interpolation and the slope calculation. A vehicle travers ability map was generated based on vehicle performances. Pitch and roll influence factors were added into the cost function of the A* algorithm. The proposed algorithm, the traditional A* algorithm, and the HA* algorithm (Height-Aware A* algorithm) were simulated and compared on the real environment maps. The results show that the proposed algorithm increases path length by up to 7.3% but reduces the energy consumption by up to 10.1% compared with the traditional A* and the HA* algorithms in off-road environments. The driving pitch angle is less than 40% for the general-performance vehicles, with being lower than 60% for the high-performance vehicles; And the roll angle of both types of vehicles is lower than 36%. Therefore, the proposed algorithm reduces energy consumption and improves lateral driving stability.

Key words: autonomous vehicles, path planning, off-road environment, improved A* algorithm

中图分类号: