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Abstract
Multi-vehicle autonomous driving has attracted significant attention from academia and industries due to its ability to improve traffic efficiency and enhance the safety of drivers and passengers. In this paper, a distributed motion planning strategy based on the artificial potential field method is proposed to achieve overtaking of the autonomous vehicle fleet in dynamic environments. Firstly, a dynamic target tracking control protocol is constructed for an autonomous vehicle fleet using a modified artificial potential field. The target tracking control protocol overcomes the disadvantage of the traditional artificial potential field method (i.e., the dynamic target cannot be reached). Besides, a distributed obstacle avoidance control protocol is also designed to avoid potential collisions during the overtaking process. Finally, simulation experiments are performed to verify the feasibility and effectiveness of the proposed algorithm.
Original language | English |
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Title of host publication | 2021 20th International Conference on Advanced Robotics, ICAR 2021 |
Pages | 873-878 |
Number of pages | 6 |
ISBN (Electronic) | 9781665436847 |
DOIs | |
Publication status | Published - 6 Dec 2021 |
Publication series
Name | 2021 20th International Conference on Advanced Robotics, ICAR 2021 |
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Fingerprint
Dive into the research topics of 'Collaborative Overtaking of Multi-Vehicle Systems in Dynamic Environments: A Distributed Artificial Potential Field Approach'. Together they form a unique fingerprint.Projects
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Robotics and Artificial Intelligence for Nuclear (RAIN)
Lennox, B. (PI), Arvin, F. (CoI), Brown, G. (CoI), Carrasco Gomez, J. (CoI), Da Via, C. (CoI), Furber, S. (CoI), Luján, M. (CoI), Watson, S. (CoI), Watts, S. (CoI) & Weightman, A. (CoI)
2/10/17 → 31/03/22
Project: Research