Exploring Factors Contributing to Crash Injury Severity at Al-Diwaniyh City Streets: Random Parameter Ordered Probit Model Technique

Abstract

Traffic crashes are among the problems that affect societies because the losses caused by these crashes directly impact the citizen due to the psychological suffering it leaves. Therefore, care must be taken, and strenuous efforts must be made in order to reduce the percentage of crash victims and losses. Depending on the characteristics of the local transportation environment, the study outcomes of traffic crash data may differ. Therefore, in order to comprehend the factors that contribute to and are involved in traffic crashes in Iraq, it is important to concentrate on the city's unique characteristics. So, the purpose of this study is to pinpoint the contributing factors that substantially impact how serious traffic crashes are in Al-diwaniya City for the years (2017-2022). RStudio was used to examine complex interactions and assess the fundamental elements that influence the severity of the crash by applying the ordered Probit model, the random parameter ordered Probit model and the marginal effect of the significant factors. The results showed a random parameter ordered Probit model well performed over the ordered Probit model. Moreover, many statistically significant variables were found to impact how severe the injury is, like road features, vehicle characteristics, crash cause, crash reason, time distribution, and crash type. Addressing these contributing factors through effective policies and programs promoting safe driving practices can create safer roads for everyone.