Modeling car-following behaviors is critical in traffic flow simulation and analysis. However, the investigation of car-following behaviors was limited in the small sample size of vehicle trajectories and different vehicle types. To overcome such shortcomings, this research calibrates and analyzes car-following behaviors based on a naturalistic trajectory dataset recorded in German highways. We divide vehicles into four types and calibrate an IDM car-following model for each vehicle based on a genetic algorithm. The calibration results based IDM model shows heterogeneous and interesting parameters, which undoubtedly reveals heterogeneous car-following behaviors among different vehicle type on highways. A final simulation case study validates the performance of the vehicle type based car-following model and, further pointed out potential applications of the research, for instance, models more realistic traffic simulations and provides parameters for adaptive cruise control systems for different type of vehicles.

CICTP