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J. Patt. Recogn. Artif. Intell."],"published-print":{"date-parts":[[2025,10]]},"abstract":"<jats:p> Unmanned underground vehicles (UUVs) offer significant advantages for coal mine transportation. However, the subterranean environment is often complex and prone to unexpected obstacles, particularly pedestrians, which pose substantial safety risks. To mitigate these risks, we developed an automated collision avoidance system. Additionally, we established an information network enabling real-time map tracking of UUVs to facilitate efficient dispatch and operation. <\/jats:p><jats:p> Advanced deep learning algorithms detect tracks, obstacles, and pedestrians. Within the track detection zone, the system employs the Hough transform to identify line segments. These segments are then assigned weighting factors based on clarity, clustering, and fitting techniques, enabling accurate reconstruction of the track\u2019s left and right boundaries. Furthermore, a defined safety zone effectively assesses the distance between pedestrians and vehicles. <\/jats:p><jats:p> In practical operation, UUVs autonomously trigger audible alarms or initiate braking when pedestrians enter a critical proximity, when other UUVs obstruct the roadway, or when vehicles approach from the opposite direction. This integrated system significantly enhances safety for underground coal mine transportation. <\/jats:p>","DOI":"10.1142\/s0218001425500247","type":"journal-article","created":{"date-parts":[[2025,7,17]],"date-time":"2025-07-17T06:02:59Z","timestamp":1752732179000},"source":"Crossref","is-referenced-by-count":0,"title":["Automatic Detection of Obstacles in Underground Railway Tracks for Collision Prevention"],"prefix":"10.1142","volume":"39","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9752-8108","authenticated-orcid":false,"given":"Kai","family":"Zhao","sequence":"first","affiliation":[{"name":"School of Computer and Artificial Intelligence, Hefei Normal University, Hefei, P.\u00a0R.\u00a0China"},{"name":"Research Institute of Anhui CRRC Ruida Electric Co., Ltd, Hefei, P. R. 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