Investigating Platoon Formation With Reduced-Scale Robots

This research investigates platoon formation and retention in various traffic conditions using five well-known car-following models, implemented as controllers on reduced-scale mobile robots (RSMRs). Our study moves beyond traditional simulations by directly applying these controllers in a controlled physical environment to observe and measure the dynamic interactions within a platoon of RSMRs. We adapted the Gazis-Herman-Rothery (GHR) model, Gipps model, intelligent driver model (IDM), proportional-integral-derivative (PID) model, and adaptive cruise control (ACC) model into controllers. Experiments were designed to assess controller performance across steady-flow, congested, and stop-and-go traffic conditions, with a preliminary scaling test to support comparison with full-scale vehicles. Overall, the IDM-inspired controller achieved the best safety-efficiency balance, with compact platooning and the smallest speed fluctuations, while ACC was typically second-best; PID and Gipps showed larger oscillations and gaps, and GHR led to collisions. The results also demonstrate noticeable differences between physical and simulation experiments, highlighting the necessity of studying platooning in a physical environment. The fundamental diagram analysis confirms that theoretical and experimental results are generally consistent, reinforcing the usefulness of RSMRs in studying traffic dynamics and providing reproducible baselines for controller evaluation.