Research on Multi-Vehicle Trajectory Planning Based on Improved RRT-APF Method

Hao Zhang, Fuyong Feng, Chao Wei*, Botong Zhao

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Multi-intelligent vehicle system can meet the needs of various missions. Efficient collaborative planning method is the key to improve its performance. In this paper, the trajectory planning of multi-vehicle system are studied. Firstly, the RRT algorithm which introduced pruning optimization and local replanning was used to plan the global path of each vehicle as the guide of trajectory planning. Then, deductive planning method and asymmetric potential field force are proposed to improve the artificial potential field method, and multi-vehicle sequence planning and collaborative planning are realized. This paper conducted simulation experiments to verify the effectiveness of the method. The experiments proved that the sequence planning method and collaborative planning method both can complete planning tasks under simple working conditions, and the collaborative planning method has higher efficiency under complex working conditions.

Original languageEnglish
Title of host publication2025 International Conference on Electrical Automation and Artificial Intelligence, ICEAAI 2025
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1416-1420
Number of pages5
ISBN (Electronic)9798331506797
DOIs
Publication statusPublished - 2025
Event2025 International Conference on Electrical Automation and Artificial Intelligence, ICEAAI 2025 - Guangzhou, China
Duration: 10 Jan 202512 Jan 2025

Publication series

Name2025 International Conference on Electrical Automation and Artificial Intelligence, ICEAAI 2025

Conference

Conference2025 International Conference on Electrical Automation and Artificial Intelligence, ICEAAI 2025
Country/TerritoryChina
CityGuangzhou
Period10/01/2512/01/25

Keywords

  • Artificial potential field method
  • Asymmetric potential field force
  • component
  • Deductive planning

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