ROAR: Robust accident recognition and anticipation for autonomous driving.

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Bibliographic Details
Title: ROAR: Robust accident recognition and anticipation for autonomous driving.
Authors: Liu X; State Key Laboratory of Internet of Things for Smart City and Department of Computer and Information Science, University of Macau, Macao Special Administrative Region of China., Guan Y; State Key Laboratory of Internet of Things for Smart City and Department of Computer and Information Science, University of Macau, Macao Special Administrative Region of China., Liao H; State Key Laboratory of Internet of Things for Smart City and Department of Computer and Information Science, University of Macau, Macao Special Administrative Region of China., He Z; Senseable City Lab, Massachusetts Institute of Technology, Cambridge MA, United States., Li Z; State Key Laboratory of Internet of Things for Smart City and Departments of Civil and Environmental Engineering and Computer and Information Science, University of Macau, Macao Special Administrative Region of China. Electronic address: zhenningli@um.edu.mo.
Source: Accident; analysis and prevention [Accid Anal Prev] 2026 Apr; Vol. 228, pp. 108414. Date of Electronic Publication: 2026 Jan 16.
Publication Type: Journal Article
Journal Info: Publisher: Pergamon Press Country of Publication: England NLM ID: 1254476 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1879-2057 (Electronic) Linking ISSN: 00014575 NLM ISO Abbreviation: Accid Anal Prev Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:1879-2057
DOI:10.1016/j.aap.2026.108414