Construction And Implementation Of Grey Prediction Model For Road Traffic Accidents In Hebei Province

Considering the aggravation of the traffic accidents, road accidents forecasting hasbecome the focus which gradually developed into a hot topic in the field of traffic safetyresearch. Road traffic system is a dynamic uncertain system, so the occurrence of thetraffic system is known, but other partial information is unkown grey system theories areadopted to do mainly research on the uncertain problems of “small sample, poorinformation” and the stochastic objects of “explicit extension, inexplicit connotation”, tobuild the mathematical model with a small quantity of data.In this paper, we analyzes the macroscopic characters of road traffic accidents in theway of the Grey relational analysis, aiming to establish the forecasting indexes. Theforecast model and its accuracy test for the traffic accidents are carried out in this paper bywhich effect of grey generator operator weakens data randomicity to excavate datas latentrules, and interchange of grey difference equation and grey differential equation realize theprocess in which continuous dynamic differential rquation is built with the disperse datasequence. Considering the macroscopic factors effecting road traffic accidents offered, weput forward MGM(1, N) forecasting model based on the grey relational analysis in aim offorecasting the road accident in Hebei Province according to the statistic data from2000to2011. The results show that MGM(1, N) grey models are applicable and efficient inforecasting the main indexes, and the result of prediction is super than basic grey modelGM(1,1) to draw; and MGM(1, N) model can fully consider the impact of traffic accidentsfactors that predict better results. Meanwhile, it can measure the level of road safety andguide the road traffic management measures reasonably under the existing trafficconditions, in order to control the traffic safety factors and curb the traffic accidents.