Modeling a Car-Following Model with Comprehensive Safety Field in Freeway Tunnels

Abstract

Car following is the most common driving behavior in tunnels. However, current car-following models are not completely suitable for tunnels because they do not take into account the environmental factors affecting vehicles in tunnels. In this paper, we present a comprehensive risk-based car-following model to describe car-following behavior in freeway tunnels. Considering the key factors influencing driving behavior in freeway tunnels, we develop a comprehensive safety field (CSF), which consists of the potential, kinetic, and environment fields to estimate the effect of speed limit signs, leading vehicles, and lighting conditions on driving risks. Then, a car-following model based on comprehensive safety field (CF-CSF) was established to determine a vehicular driving strategy in tunnels. The field force is introduced as a quantitative indicator to assess the current driving risk of vehicles and whose increase causes a greater deceleration of vehicles. Furthermore, considering the effect of low-risk levels on driving behavior is generally insignificant, we develop the risk margin (RM) as a safety indicator to determine whether current driving risk affects the driving behavior, and the driving strategy under a free condition is proposed as well. Finally, the proposed CF-CSF model is validated using a real vehicle test trajectory dataset. The comparison with real driving data and some classic car-following models indicate that our proposed CF-CSF model can more accurately predict actual driving behavior in tunnels. It is expected that the findings in this study could be valuable in modeling, understanding, and replicating features of driving behavior in freeway tunnels.