详细信息
An Intelligent Security Classification Model of Driver's Driving Behavior Based on V2X in IoT Networks ( EI收录)
文献类型:期刊文献
英文题名:An Intelligent Security Classification Model of Driver's Driving Behavior Based on V2X in IoT Networks
作者:Dai, Songyin[1]; Zhong, Yuan[1]; Xu, Cheng[1]; Liu, Hongzhe[1]; Yuan, Jiazheng[2]; Wang, Pengfei[3]
第一作者:代松银
机构:[1] Beijing Key Laboratory Of Information Service Engineering, College Of Robotics, Beijing Union University, Beijing, China; [2] Beijing Open University, Beijing, China; [3] Communication And Information Center, Ministry Of Emergency Management Of The People's Republic Of China, Beijing, China
第一机构:北京联合大学北京市信息服务工程重点实验室|北京联合大学机器人学院
通讯机构:[1]Beijing Key Laboratory Of Information Service Engineering, College Of Robotics, Beijing Union University, Beijing, China|[11417103]北京联合大学北京市信息服务工程重点实验室;[11417]北京联合大学;[1141739]北京联合大学机器人学院;
年份:2022
卷号:2022
外文期刊名:Security and Communication Networks
收录:EI(收录号:20222212176367);Scopus(收录号:2-s2.0-85130867098)
语种:英文
外文关键词:Accidents - Behavioral research - Vehicle to Everything
摘要:Traffic accidents occur frequently in Internet of Things (IoT) safety system. Traffic accidents are largely caused by drivers' unsafe driving behaviors in the process of driving. Aiming at the problem of low safety of real-time warning in driving, this paper proposes a model to detect driver behavior. Firstly, according to the driver target detection for positioning, combined with the Pose Estimation to identify the driver in the process of driving a variety of driving behaviors, at the same time, a rating model is built to score drivers' driving behaviors. Then, by integrating the driver behavior model and evaluation rules, the system can give timely and active warning when the driver makes unsafe behavior in the process of driving. Finally, in the V2X scenario, feedback and presentation are given to users in the form of points. The experimental results show that, in the scenario of Internet of vehicles, the driving behavior rating model can well analyze and evaluate drivers' driving behaviors, so that drivers can more accurately understand their abnormal driving behaviors and driving scores, which plays a significant role in IoT safety management. ? 2022 Songyin Dai et al.
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