Risk prediction model of passenger car following behavior under truck movement interruption of two-lane highway in mountainous area

Taking the typical mountainous two-lane highway bend and straight road as the research object，based on traffic trajectory data extracted by UAV aerial video，the risk prediction model of passenger car following under the movement interruption of truck was constructed by the light gradient boosting machine algorithm（LGBM）. The support vector machine（SVM）and random forest machine（RF）were used to verify the validity of the model，and the risk mechanism of the key characteristic parameters of the model was analyzed. The experimental results show that the accuracy of the risk prediction model based on the LGBM algorithm is 96.9%，which is superior. The speed difference and the following distance are the key characteristic parameters of the model，and the single factor importance on the straight road is greater. Compared with the curve，the dangerous driving behavior of straight road section is prominent，and the unstable following characteristics such as large lateral offset are obvious； the results of the model interpreter show that when the speed difference is less than 0.5 m/s and the car-following distance is greater than 40 m，it is a safe car-following state. © 2024 Editorial Board of Jilin University. All rights reserved.