Differences in Driving Characteristics between Normal and Emergency Situations and Model of Car-Following Behavior

Abstract

This paper presents results of an exploratory study on differences in driving characteristics between normal and emergency situations and builds up the car-following model under the emergency evacuation situation. The simulation scenario has been given to create a driving environment under the emergency evacuation situations. Questionnaire investigations and the electrocardiogram/heart rate monitor are used to verify the validity of the driving environment from both subjective and objective perspectives. Perception reaction time (PRT) and the critical headway are taken as two indicators to describe driving characteristics. The results show that PRT is in accord with normal distribution under both normal and emergency situations. The value of PRT under the emergency situation is lower than that under the normal situation. The results also show that critical headway under the emergency situation is smaller than that under the normal situation. A back propagation (BP) neural network is designed in this study. A combination of the Levenberg-Marquardt BP algorithm and Bayesian regularization is employed to train the network. Gray-correlation analysis is conducted to determine which factors have a great impact on the acceleration of the following car. Simulation of the BP neural network using data collected from driving simulator reveals that the BP neural network has a high precision in the prediction of the car-following model.