Research on Early-Warning Mechanism Based on Internet of Things for Traffic Safety
Yun Ke · Jisuanji fangzhen · 2012
Research road safety prediction problem.Due to the stochastic volatility,the prediction accuracy of larger sample data sequence is poor,and the traditional road traffic safety prediction based on grey prediction theory algorithm can not solve the problems of traffic congestion and traffic imbalance.In order to solve the above problems,the paper put forward a safety prediction method of traffic condition monitoring base on Internet of things technology,which mainly used the Internet of things technology to monitor the road traffic situation in real-time.Based on the collected traffic information,the early security warning index was designed,and a road traffic safety prediction model was built based on gray theory.Based on the model,a two-dimensional Marco chain model was introduced to establish a new two-dimensional Marco grey extension theory prediction model of traffic safety.The simulation results show that the new prediction method can effectively predict the road traffic safety risk and hazard,and the prediction precision is higher than the traditional grey model,which provides the basis for traffic safety system design.