Heavy vehicle multi-body dynamic simulations to estimate skidding distance

Zamzamzadeh, Mahdieh and Saifizul, Ahmad Abdullah and Ramli, Rahizar and Soong, Ming Foong (2018) Heavy vehicle multi-body dynamic simulations to estimate skidding distance. Baltic Journal of Road and Bridge Engineering, 13 (1). pp. 23-33. ISSN 1822-427X

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Official URL: https://doi.org/10.3846/bjrbe.2018.384

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.

Item Type: Article
Uncontrolled Keywords: Crash avoidance; Emergency braking; Road safety; Road surface; Skid mark; Wet road; Wheel lock-up
Subjects: T Technology > TJ Mechanical engineering and machinery
Divisions: Faculty of Engineering
Depositing User: Ms. Juhaida Abd Rahim
Date Deposited: 28 Jan 2019 02:49
Last Modified: 28 Jan 2019 02:49
URI: http://eprints.um.edu.my/id/eprint/20181

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