1. An improved risk estimation model of lane change using naturalistic vehicle trajectories;Xue QW;Journal of Transportation Safety & Security.,2023
2. Examining lane change gap acceptance, duration and impact using naturalistic driving data;Yang M;Transportation Research Part C: Emerging Technologies,2019
3. Fitch, G., Lee, S., Klauer, S., Hankey, J., Sudweeks, J. & Dingus, T. Analysis of lane-change crashes and near-crashes. Report No. DOT HS 811 147; National Highway Traffic Safety Administration: Washington, DC, USA, 2009.
4. Traffic Administration Bureau of the Ministry of Public Security of the People’s Republic of China. Annual Report on Road Traffic Accident Statistics of the People’s Republic of China, Jiangsu Wuxi, China, 2020.
5. Wijnands Jasper, S. A hybrid deep learning approach for driver anomalous lane changing identification;Fan PC;Accident Analysis and Prevention.,2022