{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,16]],"date-time":"2026-02-16T19:22:53Z","timestamp":1771269773838,"version":"3.50.1"},"reference-count":32,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2025,12,3]],"date-time":"2025-12-03T00:00:00Z","timestamp":1764720000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Ningbo Municipal Major Project of Science and Technology Innovation 2025","award":["2022Z076"],"award-info":[{"award-number":["2022Z076"]}]},{"name":"Zhejiang Provincial Natural Science Foundation of China","award":["LZ24F010004"],"award-info":[{"award-number":["LZ24F010004"]}]},{"name":"Yongjiang Sci-Tech Innovation 2035","award":["2024Z023"],"award-info":[{"award-number":["2024Z023"]}]},{"name":"Yongjiang Sci-Tech Innovation 2035","award":["2024Z122"],"award-info":[{"award-number":["2024Z122"]}]},{"name":"Yongjiang Sci-Tech Innovation 2035","award":["2024Z125"],"award-info":[{"award-number":["2024Z125"]}]},{"name":"Yongjiang Sci-Tech Innovation 2035","award":["2024Z295"],"award-info":[{"award-number":["2024Z295"]}]},{"name":"Yongjiang Sci-Tech Innovation 2035","award":["2025Z040"],"award-info":[{"award-number":["2025Z040"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["61671412"],"award-info":[{"award-number":["61671412"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"name":"Basic Public Welfare Research Project of Zhejiang Provincial","award":["LGN22F010002"],"award-info":[{"award-number":["LGN22F010002"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Information"],"abstract":"<jats:p>Deficiencies in road anomaly detection systems precipitate multifaceted risks, including elevated collision probabilities from unidentified hazards, compromised traffic flow efficiency, and exponential maintenance costs. Contemporary methods struggle with complex road environments, dynamic viewing perspectives, and limited datasets. We present AVD-YOLO, an enhanced YOLO variant that synergistically integrates Active Vision-Driven (AVD) multi-scale feature extraction with Position Modulated Attention (PMA) mechanisms. PMA addresses diminished target-background discriminability under variable illumination and weather conditions by capturing long range spatial dependencies, enhancing weak-feature target detection. The AVD technique mitigates missed detections caused by real-time viewing distance variations through adaptive multi-receptive field mechanisms, maintaining conceptual target fixation while dynamically adjusting feature scales. To address data scarcity, a comprehensive Multi-Class Road Anomaly Dataset (MCRAD) comprising 14,208 annotated images across nine anomaly categories is constructed. Experiments demonstrate that AVD-YOLO improves detection accuracy, achieving a 1.6% gain in mAP@0.5 and a 2.9% improvement in F1-score over baseline. These performance gains indicate both more precise localization of abnormal objects and a better balance between precision and recall, thereby enhancing the overall robustness of the detection model.<\/jats:p>","DOI":"10.3390\/info16121064","type":"journal-article","created":{"date-parts":[[2025,12,3]],"date-time":"2025-12-03T08:44:28Z","timestamp":1764751468000},"page":"1064","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["AVD-YOLO: Active Vision-Driven Multi-Scale Feature Extraction for Enhanced Road Anomaly Detection"],"prefix":"10.3390","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0009-0007-0905-4100","authenticated-orcid":false,"given":"Minhong","family":"Jin","sequence":"first","affiliation":[{"name":"Key Laboratory of Industrial Vision and Industrial Intelligence, Zhejiang Wanli University, Ningbo 315100, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4095-7128","authenticated-orcid":false,"given":"Zhongjie","family":"Zhu","sequence":"additional","affiliation":[{"name":"Key Laboratory of Industrial Vision and Industrial Intelligence, Zhejiang Wanli University, Ningbo 315100, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1702-141X","authenticated-orcid":false,"given":"Renwei","family":"Tu","sequence":"additional","affiliation":[{"name":"Key Laboratory of Industrial Vision and Industrial Intelligence, Zhejiang Wanli University, Ningbo 315100, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-0576-5923","authenticated-orcid":false,"given":"Ang","family":"Lv","sequence":"additional","affiliation":[{"name":"Key Laboratory of Industrial Vision and Industrial Intelligence, Zhejiang Wanli University, Ningbo 315100, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-2232-7508","authenticated-orcid":false,"given":"Zhijing","family":"Yu","sequence":"additional","affiliation":[{"name":"Key Laboratory of Industrial Vision and Industrial Intelligence, Zhejiang Wanli University, Ningbo 315100, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2025,12,3]]},"reference":[{"key":"ref_1","first-page":"1","article-title":"Anomaly detection in road traffic using visual surveillance: A survey","volume":"53","author":"Santhosh","year":"2020","journal-title":"Acm. 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