Extension Cloud Model for Road Traffic Safety Situation Study
Cuijiao Chen, Lidong Zhang, Guanghong Qian · CICTP 2020 · 2020
In order to prevent traffic accidents form “passive processing” to “active prevention”, we build a multi-index and hierarchical road traffic safety evaluation index system. In the system, we take the human-vehicle-road-environment as the first level index, and the significant influencing factors among them as the second level index. We predict the value of each index in the next year with the grey Markov model, and determine the indexes’ weights using the analytic hierarchy process (AHP)-entropy method. The extension cloud model evaluates the comprehensive level of road traffic safety level. We are able to predict the comprehensive level of the road in advance. Taking a city in Shandong Province as an example, the extension cloud model can accurately examine the safety level and problems of urban roads.