This paper focuses on the study of the optimization of accuracy rate for traffic safety early warning mechanism. The traffic safety problem has become one of harms to the global society. A prediction technology and emergency management mechanism for traffic safety has been put forward to solve the problem of traffic congestion and road traffic imbalance, especially the parameter of traditional warning algorithm is too demanding and the algorithm is too complex. The plan adopts the technology of Internet of Things, monitoring the real-time traffic condition which affords the reliable data for the traffic management department, and designs the targeted safety early warning index according to the collected traffic information, and sets up the emergency management mechanism based on the time and space model of 2D Markov chain. The simulation experiment and mathematical analysis show that the improved early warning methods can help the traffic management department to timely forecast the traffic safety risks and hidden dangers and take the effective solutions to guarantee the benign and stable state of overall transport system.
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