Modeling the Vehicle Merging Behaviors at Urban Expressway On ramp Bottlenecks

Abstract:

Based on the videos of traffic flow at two bottlenecks (Hongxu on ramp and Hongjing on ramp) on Yan’an Expressway in Shanghai, 416 empirical merging behavior samples were collected by extracting trajectories from merging vehicles, as well as each adjacent vehicles. The classification and regression tree (CART) was adopted for modeling three merging situations, the key parameters affecting different merging behaviors were analyzed and the confusion matrix was used to evaluate the result of the classification accuracy. The results show that CART performed well with these data. All the accuracies are over 75%. Moreover, a comparison among CART, classical discrete choice model and naive Bayes classifier was conducted, and the CART shows the best classification results.