In order to analyze the factors that affect the driver’s collision avoidance control behavior during the car following, a simplified car following model was set up with model parameters, and a test vehicle was built using radar and video monitoring systems and sensors for testing. Recruiting test personnel to conduct tests, Matlab was used to capture test data, and then filtering algorithms were employed to process the data in order to obtain valid data. Studying the distribution characteristics of individual driving behavior indicators, it was found that THW and TTC showed relatively small changes in the timing of releasing the accelerator pedal and pressing the brake pedal, indicating that THW and TTC were more in line with drivers’ subjective judgment of rear end collision risk. Analyzing the distribution characteristics of THW and TTC parameters in 40 samples of driving behavior, it was found that the distribution characteristics of individual and overall indicators were basically consistent, indicating that different drivers mostly had similar driving behaviors. Correlation analysis is conducted, and the results show that the distance between vehicles is most closely related to the relative speed of the two vehicles. The correlation between the two action moments reached 0.81 and 0.76, respectively, indicating that TTC is more in line with the driver’s judgment of rear end collision risk. The impact of urgency on driving behavior is analyzed, and it is found that the more urgent the deceleration of the vehicle ahead, the shorter the reaction time of the following vehicle driver. Weather conditions can also affect drivers’ judgment of rear end collision risk. In rainy and foggy weather, the following distance significantly increases, indicating that drivers will increase the following distance to cope with rear end collision risk under unfavorable weather conditions. In addition, road conditions can also affect drivers’ following behavior
