Traffic dynamics in cooperative adaptive cruise control (CACC) vehicle platoons: Analyzing congestion and merge behaviors

Abstract

This study investigates the platoon dynamics of Cooperative Adaptive Cruise Control (CACC)-equipped vehicles in mixed traffic environments, focusing on speed reduction, time-headway variations, and their effects on platoon stability. Simulations were conducted using aggressive, nominal, and cautious driver behavior models across mixed vehicle types, including trucks and small vehicles, with varying CACC ratios (20–80 %). Key performance indicators, such as time-headway, traffic density, and flow rate, were evaluated to examine the impact of CACC ratios on vehicular interaction during speed transitions, specifically from 120 kph to 100 kph and subsequent acceleration. Results demonstrated that higher CACC ratios facilitated smoother speed transitions and greater stability within the platoon. Additionally, position-based speed adjustments reduced traffic flow variability, particularly at high CACC ratios. Unlike prior studies, this research integrates a communication-based CACC control model, addressing lane-changing behaviors, vehicle communication, and realistic modeling of human-driven dynamics. The study also evaluates sliding mode control under mixed-traffic scenarios, emphasizing novel methodologies that address real-world constraints such as vehicle safety and physical limitations. These insights contribute to optimizing CACC configurations in mixed-traffic platoons, supporting enhanced cooperative driving strategies for congestion management and highway merging efficiency.