Fundamental diagram and stability analysis of mixed traffic considering heterogeneous car-following behaviors and platoon factors

Abstract

Abstract With the advancement of connected automated vehicles (CAVs), it is anticipated that mixed traffic environments, where human-driven vehicles (HVs) coexist with CAVs, will become prevalent in the future. The study aims to investigate the impact of heterogeneous car-following behaviors of HVs (e.g. aggressive, normal, and mild driving styles) and platoon factors of CAVs (i.e. platoon intensity and maximum platoon size) on the fundamental diagram and stability of mixed traffic. Firstly, a Markov chain approach is employed to describe the probability distributions of different leader-follower combinations, enabling us to construct a comprehensive mixed traffic model. Subsequently, a general modeling framework based on the mixed traffic model is established to examine the effects of heterogeneous car-following behaviors and platoon factors on the fundamental diagram and stability of mixed traffic. The results from numerical experiments reveal several findings: 1. an increase in the proportion of aggressive driving style enhances both the capacity and stability of mixed traffic; 2. larger platoon intensity and maximum platoon size contribute to improved capacity, particularly in scenarios where a large fraction of HVs exhibit aggressive driving behavior; 3. platoon intensity has a positive impact on traffic flow stability, while larger maximum platoon size leads to reduced stability; and 4. increasing CAV penetration without considering platoon intensity may lead to reduced stability compared to scenarios with a substantial proportion of aggressive drivers.