Study Of Driving Behavior Under Fog Weather Condition Based On Driving Simulator Experiment

At present, a rapid increment of motor vehicles and drivers in China contributes to a high traffic accident frequency. One of major factors resulting in the accident occurrence is a negative effect of adverse traffic environments on driving behavior. Under the fog weather conditions, the traffic accident rate could be up to ten times higher than normal weather conditions.This thesis focuses on investigating the influences of fog conditions on driving behaviors using the BJTU high-fidelity driving simulator.This study introduces a hierarchical driving behavior research method that is especially appropriate for driving simulation experiment studies. Based on the method, this research classifies driving behaviors into three categoriesin terms of low, middle, and high levels of driving risks. The three classes of driving behaviors are vehicle control behavior, dynamic decision behavior, and precrash behavior. Then, driving experimental driving scenarios corresponding to the three risk levels of driving behaviors are designed in the driving simulator system. Choosing light fog and heavy fog as adverse weather conditions, subjects were recruited and tested in the driving simulator and their driving behavior data were collected for each scenario. Last, the Multivariate Analysis of Variance (MANOVA) and Logistic regression analysis are conducted to investigate the influences of fog conditions on the driving behaviors for the three risk levels. The most significant findings is that fog condition reduce the lane control ability on the bend section, increasing the possibility of polling out of the lane; when drivers follows a vehicle, fog contributes to driving too close to the lead vehicle, drivers are likely to collide with the leading vehicle; in the emergency, fog can extend the brake reaction time and the longer reaction time need, the greater likelihood of collision.Study is to provide a scientific experimental analysis method for systematically analyzing and evaluating the impacts of interventions on driving behavior and safety.