Heavy vehicle multi-body dynamic simulations to estimate skidding distance

Abstract

The skid mark is valuable for accident reconstruction as it provides information about the braking behaviour drivers and the speed of heavy vehicles. However, despite its importance, there is currently no mathematical model available to estimate skidding distance (SD) as a function of vehicle characteristics and road conditions. This paper attempts to develop a non-linear regression model that is capable of reliably predicting the skidding distance of heavy vehicles under various road conditions and vehicle characteristics. To develop the regression model, huge data sets were derived from complex heavy vehicle multi-body dynamic simulation. An emergency braking simulation was conducted to examine the skidding distance of a heavy vehicle model subject to various Gross Vehicle Weight (GVW) and vehicle speeds, as well as the coefficient of friction of the road under wet and dry conditions. The results suggested that the skidding distance is significantly affected by Gross Vehicle Weight, speeds, and coefficient of friction of the road. The improved non-linear regression model provides a better prediction of the skidding distance than that of the conventional approach thus suitable to be employed as an alternative model for skidding distance of heavy vehicles in accident reconstruction.