A variable time headway model for mixed car-following process considering multiple front vehicles information in foggy weather

Abstract

The aim of this work is to investigate the Fog-related variable time headway (FVTH) model of connected and automated mixed flow considering multi-front vehicles information in a reduced visibility environment for driving safety. The car-following modes of mixed vehicles are analysed and the vehicle ratio for each mode based on Markov chain models is derived, where the number of front vehicles, CAVs penetration rate, and platoon intensity are considered. The combined coupling effect of visibility and driving speed on time headway is explored, and a variable time headway strategy is proposed. Their relationship equations are deduced as the FVTH model. The perturbation method is used to discuss the stability of traffic flow and obtain its stability judgment conditions. The proposed model was validated and the effects were discussed via simulation experiments. The results indicate that the acceleration and deceleration times of vehicles and collision possibility decrease significantly using the proposed method. When penetration rate is 50%, the number of front vehicles is three and platoon intensity is zero, the time to return to a stable state is reduced by 18.9%-30.3% and 24.7%-39.4%, respectively, and Time Exposed Time-to-collision (TET) is reduced by 26.1%-48.9% and 43.7%%-65.4%, respectively, compared with the basic IDM method and IDM method that considers multi-front vehicles information. As visibility decreases, the reduced degree of these indicator values increases. The driving efficiency and safety level can be enhanced.