International Journal of Transportation Science and Technology2025，Vol.18Issue(2)：P.272-284,13.DOI:10.1016/j.ijtst.2024.07.002
Graph convolutional LSTM algorithm for real-time crash prediction on mountainous freeways
Yesihati Azati 1Xuesong Wang 2Mohammed Quddus 3Xuefang Zhang4
作者信息
- 1. School of Transportation Engineering,Tongji University,Shanghai 201804,China The Key Laboratory of Road and Traffic Engineering,Ministry of Education,Shanghai 201804,China
- 2. School of Transportation Engineering,Tongji University,Shanghai 201804,China The Key Laboratory of Road and Traffic Engineering,Ministry of Education,Shanghai 201804,China National Engineering Laboratory for Integrated Optimization of Road Traffic and Safety Analysis Technologies,88 Qianrong Rd,Wuxi 214151,China
- 3. Centre for Transport Engineering and Modelling,Department of Civil and Environmental Engineering,Faculty of Engineering,Imperial College London,London SW72AZ,United Kingdom
- 4. School of Transportation Engineering,Tongji University,Shanghai 201804,China Centre for Transport Engineering and Modelling,Department of Civil and Environmental Engineering,Faculty of Engineering,Imperial College London,London SW72AZ,United Kingdom
- 折叠
摘要
关键词
Traffic safety/Hourly crash prediction/Mountainous freeway/Graph convolutional network-long short-term memory(GCN-LSTM)分类
交通工程引用本文复制引用
Yesihati Azati,Xuesong Wang,Mohammed Quddus,Xuefang Zhang..Graph convolutional LSTM algorithm for real-time crash prediction on mountainous freeways[J].International Journal of Transportation Science and Technology,2025,18(2):P.272-284,13.
