Estimation of vehicle pre-braking speed

Wen-Kung Tseng, S. X. Liao

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

An expert system has been proposed to estimate the relationship between the vehicle pre-braking speed and the length of the skid mark. Since the length of the skid mark varies with many factors, there is no a single formula or equation which can represent the relationship between the vehicle pre-braking speed and the length of the skid mark. Therefore in this paper an expert system is built to estimate the relationship between the vehicle pre-braking speed and the length of the skid mark. The radial basis function (RBF) neural network is used for the expert system due to its shorter training time and higher accuracy. There are many factors affecting the skid mark. In this paper we choose 7 factors, i.e. brand of vehicle, vehicle displacement, year of manufacture, vehicle weight, vehicles with and without ABS, roadway surface, and vehicle speed for the training in the RBF neural network. The total number of the training data for the RBF neural network is 2619. The results showed that high accuracy is obtained for estimating the relationship between the vehicle pre-braking speed and the length of the skid mark. Thus the expert system proposed in this paper is demonstrated to be a suitable system for estimating the relationship between the vehicle pre-braking speed and the length of the skid mark.

Original languageEnglish
Title of host publicationNew Trends in Mechatronics and Materials Engineering
Pages165-169
Number of pages5
DOIs
Publication statusPublished - 2012 Feb 13
Event2011 International Conference on Mechatronics and Materials Engineering, ICMME 2011 - Qiqihar, China
Duration: 2011 Dec 102011 Dec 12

Publication series

NameApplied Mechanics and Materials
Volume151
ISSN (Print)1660-9336
ISSN (Electronic)1662-7482

Other

Other2011 International Conference on Mechatronics and Materials Engineering, ICMME 2011
CountryChina
CityQiqihar
Period11-12-1011-12-12

All Science Journal Classification (ASJC) codes

  • Engineering(all)

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