A Coordinated Collision Mitigation Approach for Virtual Coupling Trains by Using Model Predictive Control

Virtual Coupling has attracted significant attention from both industry and academia, which could increase the flexibility and capacity of rail transport. At the same time, the risk of trains collision is greatly increased especially when leader train implements emergency braking. This study proposes a coordinated collision mitigation approach for Virtual Coupling trains by using model predictive control (MPC). In the proposed approach, the problem is modeled with the objective of minimizing the total relative kinetic energy for a virtuallycoupled train formation. The typical scenarios are considered in this paper: 1. Emergency braking for homogeneous fleet; 2. Emergency braking for heterogeneous fleet; 3. Emergency braking for homogeneous fleet with one train losing part of braking deceleration. The performance of the MPC based approach was compared with other two control strategies, basic adaptive cruise control (ACC) and directly maximum braking control (DBC), and the simulation results show that MPC strategy has the best performance among these three strategies in reducing the total relative kinetic energy of virtually-coupled train formation, the DBC control strategy is the second, and the basic ACC control strategy needs to be improved. The proposed MPC based control strategy has the potential to avoid the collision among virtually-coupled train formation especially when the trains have different deceleration abilities.