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Xingjiao Li

As seen in: MDPI
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Articles

Anti-Collision Path Planning and Tracking of Autonomous Vehicle Based on Optimized Artificial Potential Field and Discrete LQR Algorithm

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By Chaoxia Zhang, Zhihao Chen, Xingjiao Li, Ting Zhao
| MDPI
1. Introduction With the rapid advancements in computer science, technology, and artificial intelligence, the prospect of replacing human drivers with automated driving systems is becoming a reality. The development of autonomous driving has enabled people to progressively relinquish control to these systems [1]. The integration of the Internet of Things and artificial intelligence into vehicles has endowed them with their own decision-making capabilities.
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Anti-collision Path Planning and Tracking of Autonomous Vehicle Based on Optimized Artificial Potential Field and Discrete LQR Algorithm

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By Chaoxia Zhang, Zhihao Chen, Ting Zhao, Xingjiao Li
| preprints.org
Preprint Article Version 1 This version is not peer-reviewed Version 1 : Received: 11 July 2024 / Approved: 11 July 2024 / Online: 12 July 2024 (12:49:28 CEST) Zhang, C.; Chen, Z.; Li, X.; Zhao, T. Anti-collision Path Planning and Tracking of Autonomous Vehicle Based on Optimized Artificial Potential Field and Discrete LQR Algorithm. Preprints 2024, 2024071007. https://doi.org/10.20944/preprints202407.1007.v1 Zhang, C.; Chen, Z.; Li, X.; Zhao, T.
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