Advancing cooperative adaptive cruise control: a comprehensive review of control methodologies and traffic impacts

Adaptive Cruise Control (ACC) and Cooperative Adaptive Cruise Control (CACC) are transforming transportation by enhancing traffic flow, safety and efficiency. ACC uses onboard sensors to maintain safe spacing, while CACC integrates Vehicle-to-Vehicle (V2V) communication for coordinated platooning. Despite their potential, challenges persist in mixed-traffic environments where human-driven vehicles introduce unpredictability. This study evaluates ACC/CACC impacts on traffic capacity, stability, congestion and energy consumption. Results indicate improved efficiency in controlled settings, but real-world deployment is hindered by low penetration rates, communication infrastructure gaps and integration with non-autonomous vehicles. Future advancements require adaptive algorithms, hybrid control strategies and large-scale validation. Machine learning, robust V2V/Vehicle-to-Infrastructure (V2I) systems and human behaviour analysis are critical to optimising these technologies. By addressing these challenges, ACC/CACC systems can advance toward scalable, sustainable transportation networks. This work provides actionable insights for refining CACC frameworks and guiding research priorities in intelligent transportation.