Vehicle collisions analysis on highways based on multi-user driving simulator and multinomial logistic regression model on US highways in Michigan

Abstract

Traffic collision on the highway has become a serious issue because they delay the sustainable development of society. Highway accidents on I-69 have one of the highest crash rates in the U.S. in Michigan and a higher fatality rate than average. This study aimed to identify the factors contributing to highway user crashes on I-69 in Flint, Michigan. This study also aims to find the relationship between the change in the speed limit in certain weather conditions and the number of crashes that are likely to occur as a sequence of this change. A multi-user driving simulator is applied in this study with ten driving simulator scenarios. The multinomial logistic regression (MNL) model has been investigated in this study to identify statistically significant factors that contribute to crashes. The analyses indicated that speeding and speed limits during inclement road/weather conditions significantly affected crashes. Most frequent crashes occur during snowy and icy weather conditions and by changing the speed limit during these weather conditions. Therefore, driver speed is suspected to be the most factor that caused the Vehicle crash on I-69. The method of developing Crash modification factors (CMFs) used in this study will help to reduce crashes and improve traffic system safety performance on highways in Michigan.