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J. Hefei Univ. Tech. (Nat. Sci.)

合肥工业大学学报(自然科学版)

JOURNAL OF HEFEI UNIVERSITY OF TECHNOLOGY (NATURAL SCIENCE)

Competent Authorities: Ministry of Education of the People's Republic of China

Sponsor by: Hefei University of Technology

ISSN 1000-1646, CN 34-1001/N

Path planning for driverless racing cars based on Delaunay triangulation and quadratic programming

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基于 Delaunay 三角剖分与二次规划的无人赛车路径规划

Journal Information

J. Hefei Univ. Tech. (Nat. Sci.), Jan.2025, Vol.48 No.1: 1-9, 49

DOI: 10.3969/j.issn.1003-5060.2025.01.001

Authors

ZHANG Chaoqun, ZHANG Daisheng, ZHANG Yifan

(School of Automobile and Traffic Engineering, Hefei University of Technology, Hefei 230009, China)

Abstract and Keywords

Abstract: In the scenario of driverless racing track, in order to give full play to the racing performance and obtain faster lap speed, this paper uses Delaunay triangulation method and quadratic programming (QP) to solve the path planning algorithm. The point cloud data obtained by the perception system is processed and triangulated, the constraint optimization is introduced to eliminate external triangles on the track, and the internal midpoints are selected for interpolation to generate the road centerline. The road centerline is introduced into the path optimization model, and the two optimization directions of the minimum curvature path and the shortest distance path are selected for comparison. The optimization problem is transformed into a QP problem for solution. Through simulation experiments, speed planning analysis was conducted on two types of optimizations, and the results showed that faster lap speeds can be achieved under the minimum curvature path condition. Finally, algorithm validation was conducted on an experimental platform, indicating that the algorithm can effectively and reasonably plan a smooth and suitable path for the racing track, meeting the requirements of racing competitions.

Keywords: racing car; path planning; speed planning; triangulation; quadratic programming(QP)

作者信息

张超群，张代胜，张一凡

(合肥工业大学汽车与交通工程学院，安徽合肥230009)

摘要和关键词

摘要: 为了使无人驾驶方程式赛车的性能得到充分发挥且获得较快的圈速，文章采用 Delaunay 三角剖分法和二次规划求解方法进行路径规划。对感知系统获得的点云数据进行处理，将其三角剖分并剔除外部三角形，选取三角形内部中点进行插值生成道路中线；将道路中线引入路径优化模型，选取最小曲率路径和最短距离路径2个优化方向进行对比，将优化问题转化为二次规划问题求解。通过仿真实验对2类优化进行速度规划分析，结果表明最小曲率路径条件下能够获得更快的圈速。在试验赛车上使用最小曲率路径优化算法进行验证，证明该算法能够有效合理地规划出平滑适合赛道的路径，满足赛车比赛要求。

关键词: 赛车；路径规划；速度规划；三角剖分；二次规划

Funding

国家重点研发计划资助项目（2021YFE0116600）

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