Modeling of the Chinese driver's braking behavior in the simulated traffic scene of rear-end collision avoidance

Abstract

Drivers who exceed the speed limit and cut in aggressively are the majority in China. Their behaviors inevitably send other drivers into an execution cycle of irrational braking frequently in the complex traffic flow. So the main cause of severe traffic accidents and great casualties is Chinese drivers' raking behaviors. In this paper, Neural Network model of driver's braking behavior characteristics during ending-collision avoidance was set up. The driving behavior test under the scene of the simulated traffic environment was carried out on the fixed driving simulator (ADSL) improved by the State Key Laboratory of Automobile Dynamic Simulation of Jilin University. Neural Network GUI was set by Matlab to select the appropriate network structure and learning arithmetic, and finally the driver's braking behavior model was built up for the simulated ending-collision avoidance scene. It can be concluded that the Neural Network model can simulate driver's braking behavior during ending-collision avoidance exactly, and in our future researches this model with other simulated driving behaviors will be used to evaluate driving reliability on traffic safety.