Linear internal stability for mixed traffic flow of CAVs with different automation levels

With the development of autonomous driving and vehicle-to-infrastructure technologies, connected automated vehicles (CAVs) will gradually replace human-driven vehicles (HDVs). However, during the widespread adoption of CAVs, the roads will experience a new type of mixed traffic flow composed of vehicles with different automation levels for an extended period. To analyze the impact of different automation levels on mixed traffic flow, this paper proposes a stability analysis framework for mixed traffic flow that considers different automation levels. The influence of automation level classification on the composition of mixed traffic flow is analyzed first, and the degradation of CAVs in mixed traffic flow is further explored. Then, a stability analysis framework for mixed traffic flow considering different automation levels is proposed, and the impact of key parameters on the stability is analyzed. Finally, simulation experiments are designed to validate the theoretical analysis results. The research findings indicate that (1) the stability of mixed traffic flow improves with the increase in steady-state speed. When vehicle speed exceeds 20m/s, mixed traffic flow remains stable. (2) When the CAV penetration rate is low, the stability of mixed traffic flow is poor due to the degradation of CAVs. However, with the increase in the penetration rate and automation level of CAVs, mixed traffic flow rapidly tends toward a stable state. (3) Numerous factors influence the stability of mixed traffic flow, with the order of importance being the CAV penetration rate, automation level, headway, and maximum acceleration. Therefore, this study can provide theoretical support for managing and controlling mixed traffic flow with different automation levels in the future.