Simulation for severity assessment of motor vehicle accidents

Abstract

Battery electric vehicles (BEVs) exhibit distinct vehicle characteristics, including dynamics, increased mass, and acceleration capabilities. To assess the impact of BEVs on traffic hazard classification, a simulation model that accurately captures vehicle behavior in critical traffic scenarios is required. This thesis presents the development and integration of a vehicle model within a traffic scenario simulation using Matlab/Simulink. The vehicle dynamic behavior of the model has been validated using IPG CarMaker, ensuring accurate representation. The outcome of this research is a simulation model that covers both vehicle and driver behaviour in safety-critical situations. The model facilitates the determination of severity levels in the event of a system fault leading to unintended acceleration or deceleration of the vehicle. The findings demonstrate that BEVs give rise to more severe situations, resulting in higher ASIL levels compared to internal combustion engine (ICE) vehicles. Consequently, the introduction of electric propulsion systems will alter the severity classification in common longitudinal scenarios. In conclusion, this thesis emphasizes the transformative impact of electric propulsion systems on traffic hazard classification and establishes the significance of developing simulation tools that accurately capture the behavior of BEVs in safety-critical scenarios.