Modeling and optimizing platooning systems for autonomous vehicles in CARLA

Platooning is a key strategy for improving fuel efficiency, traffic flow, and safety in connected and autonomous vehicle (CAV) systems. This study investigates the optimization of platoon models using the CARLA simulation environment, focusing on the sensitivity of control parameters and their impact on vehicle performance. By implementing and evaluating cooperative adaptive cruise control (CACC) and proportional-integral-derivative (PID)-based controllers, this research explores how different configurations affect platoon integrity, energy efficiency, and safety under various traffic and environmental conditions. The results indicate that a balanced control strategy such as moderate time headway, moderate tau (τ ), and moderate PID tuning yields the best overall performance. Notably, the safest model also ranked among the top third in fuel efficiency, demonstrating that stability-oriented tuning can enhance both safety and energy savings.