Prediction of seasonal variation in traffic collisions on rural highways: A case study in the province of British Columbia

Traffic collisions are one of the world's major problems. According to the World Health Organization (WHO), about 1.25 million people die every year in traffic collisions across the world and a further 20-50 million are injured or disabled. 24% of all collisions are weather-related. Collision risk usually increases from 50 to 100 percent during precipitation. Various tools/methods were developed in order to assess highway safety. Historically, collision rates, linear regression and generalized linear regression methods have been used as the basis for safety analysis. Research has shown that there are limitations with such approaches due to the non-linear relationship between collision frequency and exposure. Collision prediction modelling is the recommended technique for estimating road safety in the American Association of State Highway and Transportation Officials (AASHTO) Highway Safety Manual (HSM). However, the prediction modelling does not really take into consideration of traffic seasonal variation and weather impacts as the annual average daily traffic (AADT) is one of main variables having a direct impact on safety. Previous studies indicate that weather especially winter weather is associated with traffic collisions. This study analyzed the seasonal variations of traffic and collisions on rural highways in British Columbia, Canada. Collision risks related to winter weather were investigated and assessed. It concludes that traditional techniques of highway safety assessment without the consideration of seasonal variation of traffic collisions, especially impacts of winter condition in Canada, might result in underestimating the collision risk. This paper suggests that further study of highway safety with a focus on the seasonal variation of collisions and traffic volumes will help to improve the highway safety assessment and provide valuable inputs for winter road maintenance. Furthermore, it also suggests a real need for an interdisciplinary approach in highway safety assessment in order to integrate all factors including human, vehicle, traffic and road/environment and provide a clear and comprehensive understanding of causes of collisions. Other countermeasures, including new material applications in pavement, intelligent transportation systems (ITS) and winter maintenance methods/strategies, in addition to traditional methods (Snow plowing, sanding and salting) of preventing traffic collisions during winter should also be considered.