An expert system for estimating vehicle speed based on length of skid mark

• Main Authors: Liao, Shih-Syong, 廖士雄
• Other Authors: Tseng, Wen-Kung
• Format: Others
• Language: en_US
• Published: 2011
• Online Access: http://ndltd.ncl.edu.tw/handle/52724860185385772229

碩士 === 國立彰化師範大學 === 車輛科技研究所 === 99 === This work presents an expert system 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 study 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 study we choose seven 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 work is demonstrated to be a suitable system for estimating the relationship between the vehicle pre-braking speed and the length of the skid mark.