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Path Departure Risk Assessment and Hierarchical Longitudinal Control for Autonomous Mining Trucks

  • Beihang University

科研成果: 书/报告/会议事项章节会议稿件同行评审

摘要

Autonomous Mining Trucks (AMT) are extensively deployed in open-pit mining areas. When AMT experience path departure, collisions with road boundaries or obstacles may occur, leading to severe consequences. This necessitates specialized path departure risk assessment and safety control strategies. In this paper, an enhanced Time to Lane Crossing (TLC)-based departure risk quantification method and a collision detection-based collision risk quantification method are proposed, and a hierarchical longitudinal control strategy is developed building upon these quantifications. Experiments using actual AMT operational data from mining sites demonstrate that the proposed safety protection control strategy computes appropriate deceleration commands based on risk quantification results, enabling timely safety interventions before path departure or collisions occur, thereby ensuring AMT operational safety.

源语言英语
主期刊名2025 5th International Conference on Robotics, Automation, and Artificial Intelligence, RAAI 2025
出版商Institute of Electrical and Electronics Engineers Inc.
885-889
页数5
ISBN(电子版)9798331558734
DOI
出版状态已出版 - 2025
活动2025 5th International Conference on Robotics, Automation, and Artificial Intelligence, RAAI 2025 - Singapore, 新加坡
期限: 18 12月 202520 12月 2025

出版系列

姓名2025 5th International Conference on Robotics, Automation, and Artificial Intelligence, RAAI 2025

会议

会议2025 5th International Conference on Robotics, Automation, and Artificial Intelligence, RAAI 2025
国家/地区新加坡
Singapore
时期18/12/2520/12/25

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