@inproceedings{91f24ba097b0465c9ea1b7102718df2e,
title = "Multi-Target Tracking and Trajectory Planning Framework for Autonomous Vehicles Based on Monocular Vision",
abstract = "In the pursuit of enhancing autonomous vehicle capabilities, efficient multi-object tracking and trajectory planning are critical components. This paper proposes an integrated framework for multi-Target tracking and motion planning, leveraging monocular vision. The framework employs the You Only Look Once v8 (YOLOv8) algorithm as the object detector, which accurately identifies multiple obstacles in real-Time. For tracking these detected obstacles, the Deep Simple Online and Realtime Tracking (DeepSORT) algorithm is utilized, which ensures robust multi-Target tracking by associating detected objects across consecutive frames. Based on the trajectories of tracked obstacles, the Probabilistic Roadmap (PRM) algorithm is utilized to generate a reliable and efficient path for the self-driving vehicles. To evaluate the feasibility and effectiveness of the proposed framework, we designed and executed a series of experiments.",
keywords = "autonomous vehicle, multi-Target tracking, target detection, trajectory planning",
author = "Zixuan Xu and Haobing Pang and Jianshan Zhou and Daxin Tian and Xuting Duan and Chunmian Lin and Kaige Qu and Yanyan Chen",
note = "Publisher Copyright: {\textcopyright} 2025 The Authors.; 9th International Conference on Intelligent Transportation Engineering, ICITE 2024 ; Conference date: 18-10-2024 Through 20-10-2024",
year = "2025",
month = jul,
day = "17",
doi = "10.3233/ATDE250487",
language = "英语",
series = "Advances in Transdisciplinary Engineering",
publisher = "IOS Press BV",
pages = "872--881",
editor = "Guoqiang Mao",
booktitle = "Intelligent Transportation Engineering - Proceedings of the 9th International Conference, ICITE 2024",
address = "荷兰",
}