Research on path planning of intelligent vehicles

Qiyan Yan; Xia Liu; Zhoulin Chang

doi:10.1117/12.3050813

20 January 2025 Research on path planning of intelligent vehicles

Qiyan Yan, Xia Liu, Zhoulin Chang

Author Affiliations +

Proceedings Volume 13422, Fourth International Conference on Intelligent Traffic Systems and Smart City (ITSSC 2024); 134220T (2025) https://doi.org/10.1117/12.3050813
Event: Fourth International Conference on Intelligent Traffic Systems and Smart City (ITSSC 2024), 2024, Xi'an, China

Abstract

With the continuous improvement of intelligence and driving safety requirements, accurately sensing the external environment and planning paths reasonably and efficiently has become one of the research hotspots in intelligent vehicles. Based on the study of intelligent vehicle architecture and predictive control schemes, this article focuses on the research of trajectory planning algorithms. This article proposes an improved RRT* algorithm based on the principle of fast random tree algorithm (RRT). This algorithm introduces a bidirectional random tree search strategy to shorten the convergence time and improve computational efficiency; by using redundant point clipping and B-spline curve fitting methods, the algorithm generates relatively smooth paths. Build a narrow channel environment and a multi obstacle environment in MATLAB software environment for simulation verification. The simulation results show that compared to the traditional RRT* algorithm, the improved RRT* algorithm outperforms the traditional RRT* algorithm in terms of planning speed, path length, and number of sampling nodes.

(2025) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Qiyan Yan, Xia Liu, and Zhoulin Chang "Research on path planning of intelligent vehicles", Proc. SPIE 13422, Fourth International Conference on Intelligent Traffic Systems and Smart City (ITSSC 2024), 134220T (20 January 2025); https://doi.org/10.1117/12.3050813

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