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Inferring crowd crush accidents in typical high-density pedestrian movement zones via the vision-trajectory fusion neural network.

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Title: Inferring crowd crush accidents in typical high-density pedestrian movement zones via the vision-trajectory fusion neural network.
Authors: Thomas Xie CZ; School of Intelligent Systems Engineering, Sun Yat-sen University, China; Guangdong Provincial Key Laboratory of Intelligent Transportation System, China., Zhang H; PCA Lab, School of Computer Science and Engineering, Nanjing University of Science and Technology, China., Zhang Y; Research Centre for Smart Urban Resilience and Firefighting, Department of Building Environment and Energy Engineering, The Hong Kong Polytechnic University, Hong Kong., Yang X; School of Information and Control Engineering, Qingdao University of Technology, China., He Z; School of Intelligent Systems Engineering, Sun Yat-sen University, China; Guangdong Provincial Key Laboratory of Intelligent Transportation System, China., Tian Y; Department of Computer Science and Engineering, University of Notre Dame, United States. Electronic address: yijun.tian@alumni.nd.edu.
Source: Accident; analysis and prevention [Accid Anal Prev] 2026 Jun; Vol. 230, pp. 108482. Date of Electronic Publication: 2026 Mar 02.
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
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  Data: <searchLink fieldCode="AU" term="%22Thomas+Xie+CZ%22">Thomas Xie CZ</searchLink>; School of Intelligent Systems Engineering, Sun Yat-sen University, China; Guangdong Provincial Key Laboratory of Intelligent Transportation System, China.<br /><searchLink fieldCode="AU" term="%22Zhang+H%22">Zhang H</searchLink>; PCA Lab, School of Computer Science and Engineering, Nanjing University of Science and Technology, China.<br /><searchLink fieldCode="AU" term="%22Zhang+Y%22">Zhang Y</searchLink>; Research Centre for Smart Urban Resilience and Firefighting, Department of Building Environment and Energy Engineering, The Hong Kong Polytechnic University, Hong Kong.<br /><searchLink fieldCode="AU" term="%22Yang+X%22">Yang X</searchLink>; School of Information and Control Engineering, Qingdao University of Technology, China.<br /><searchLink fieldCode="AU" term="%22He+Z%22">He Z</searchLink>; School of Intelligent Systems Engineering, Sun Yat-sen University, China; Guangdong Provincial Key Laboratory of Intelligent Transportation System, China.<br /><searchLink fieldCode="AU" term="%22Tian+Y%22">Tian Y</searchLink>; Department of Computer Science and Engineering, University of Notre Dame, United States. Electronic address: yijun.tian@alumni.nd.edu.
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        Value: 10.1016/j.aap.2026.108482
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              Text: 2026 Jun
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