Probabilistic risk assessment for heavy duty vehicles rollover under crosswind environment

This study delves into the complex interplay of factors contributing to heavy-duty vehicle (HDV) rollover accidents, with a particular emphasis on the role of crosswinds. The research introduces a novel probabilistic risk assessment model that integrates vehicle dynamics, environmental conditions, and driver behavior to provide a more accurate prediction of rollover risk. Key topics covered include the development of a vehicle aerodynamic model that accounts for the effects of wind speed and direction, the establishment of a lateral load-transfer ratio (LTR) model to assess rollover risk, and the application of reliability theory to determine adaptive rollover thresholds. The study also explores the impact of various vehicle parameters, such as speed, load, and turning radius, on rollover risk. Through extensive simulations and numerical applications, the research validates the model's predictions and demonstrates its potential to enhance the reliability of rollover warning systems. The findings highlight the significant influence of crosswinds on vehicle stability and underscore the need for advanced modeling techniques to improve road safety.