Analysis of the relationship between adverse weather conditions and traffic accidents in Hebei Province based on order relationship

Abstract

Based on the data of traffic accident number, casualty number, economic loss and meteorological elements in the Hebei Express-way from 2013 to 2017, the number and grade of accidents were quantified into accident index. The interannual, interlunar and diurnal varia-tion characteristics of the fog, rain and snow days with high impact on highway traffic are analyzed. The daily average traffic accident index and the nonlinear regression model of meteorological factors are constructed. The results show that:(1) The total number of traffic accidents, fatalities and economic losses under bad weather conditions at the time of traffic accidents are in the order of foggy, rainy, and snowy, while the number of injuries and casualties are in the order of rainy, foggy, and snowy. (2) The peak value of traffic accidents in rainy and snowy days is related to the extreme weather events in that year, and the direct economic loss of single traffic accident in foggy days is on the rise. There are significant differences in the month and day distribution of accidents. The month with the highest incidence of foggy accidents is from September to February of the next year. The month with the highest incidence of accidents in rainy days is from May to October. The snow days are mostly in January-December, and the time between 05:00-08:00 BT and 00:00 BT is the high incident time period. (3) Us-ing precipitation, visibility and traffic accident index, higher-than-normal traffic accident prediction models are established, and their effect as judged by non-linear regression is very significant.

Keywords

• highway
• adverse weather conditions
• traffic accident index
• order relationship analysis method
• nonlinear regression model