Strategy Research on Modularized Formation Mode of Trains Based on Intelligent Connected Vehicles

With the rapid advancement of intelligent connected vehicle technologies, vehicle platooning has emerged as a key strategy for enhancing traffic efficiency. However, achieving efficient and safe dynamic docking and decoupling in complex traffic environments remains a challenge, particularly for maintaining precise formation control. This study proposes a novel hard-connected modular platooning strategy for intelligent connected vehicles (ICVs), integrating multi-attribute Fuzzy C-Means (FCM) clustering and an improved A* algorithm to address the limitations of existing wireless-based methods. Unlike conventional distance-only clustering, our approach enables precise coordination between the roadside unit and vehicle (RSU-V2X) for docking with 0.5–0.61m inter-vehicle spacing. It also optimizes decoupling path planning with kinematic constraints, reducing travel time by 5.1–7.1s and path length by 8.2–12.4%. The hard-connection mechanism reduces communication latency, improving speed synchronization stability by 50 to 70% compared to methods dependent on VANET. Simulations demonstrate 89.8–91.7% higher road space utilization and superior performance in dynamic traffic, offering a groundbreaking solution for modular autonomous driving. Future work will extend the validation to high-speed real road scenarios.