Abstract
Reconstruction of traffic accidents has been so crucial scientific process in order to make impartial and judicious decisions. This study focuses on impact speed prediction of accident sufferers just before the collision in a comprehensive scientific way by using an accident reconstruction software called “vCrash” and Function Fitting Neural Network (FITNET) artificial intelligence method (predictor) in case of absence of skid marks or other clues about calculating impact speeds. A sample real world accident was simulated on the software several times by changing collision speeds to form different deformation on the collision regions of the vehicles in every simulation. Every single deformation amount corresponding to each impact velocity was recorded and used as teaching data for FITNET prediction model. Using 10-fold cross validation, mean squared error (MSE) and multiple correlation coefficients (R) were observed to exhibit performance of the prediction model. The model performed high R (close to 1) and acceptable MSE values. This method aims that, in a probable similar accident scene in future, it will be possible to analyze the impact speeds just by entering average deformation amounts into an application on a portable device at the accident scene without requirement of expensive reconstruction tools and it will be a guide for analysis of other accident types.
Highlights
Traffic engineering focuses on safety and efficiency in transportation
Two different training algorithms within Fitting Neural Network (FITNET) were used in order to compare the R and mean squared error (MSE) values. “trainlm” is a network training function that updates weight and bias values according to LevenbergMarquardt optimization. “trainlm” is often the fastest backpropagation algorithm in the toolbox, and is highly recommended as a first-choice supervised algorithm, it does require more memory than other algorithms. “trainrp” is a network training function that updates weight and bias values according to the resilient backpropagation algorithm
It may be possible that an application that can run on portable devices may be coded in order to estimate impact speeds by entering average deformations on the collision regions of vehicles
Summary
Traffic engineering focuses on safety and efficiency in transportation. Public agencies strive to reduce traffic accidents on roadways in most countries all over the world. In Turkey, fatalities and injuries due to traffic accidents are major problems for public [2]. Xu et al [13] studied on effects of vehicle impact speed in pedestrian–vehicle accident by comprising reconstruction model and they verified their analysis by ten real-world accident cases to validate their results and to yield an approach for investigators. Yannis et al conducted [15] an analysis on driver age and vehicle engine size effects on fault and severity in young motorcyclists accidents. They concluded that accident severity modeling revealed a significant second-order interaction between severity, driver age and two-wheeler engine size.
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