Stochastic Game-Based Anti-Jamming Control Method for Heavy-Haul Train Group Operation

With the growing global demand for mineral resources, enhancing the transport capacity of heavy-haul railways (HHR) has emerged as a key area of research. As an emerging train formation technology, the virtual coupling train system (VCTS) has the potential to substantially increase the traffic density of heavy-haul trains (HHT) and thereby improve transport efficiency. However, the stable operation of virtually coupled fleets relies on train-to-train (T2T) communication, which is vulnerable to jamming attacks (JAs) within the complex operational environments of HHR. To address issues such as train decoupling and emergency braking in the VCTS that may be caused by JAs, this study proposes a stochastic game-based anti-jamming control (SGAC) strategy aimed at ensuring the stability and operational safety of the VCTS operating within HHR. The proposed approach models both JAs and defensive actions as a stochastic game and employs an H∞-based cross-layer control method to mitigate their adverse effects. The control performance is analyzed through frequency-domain mapping, and a quantitative evaluation is conducted using the H∞ norm. The simulation results demonstrate that the SGAC scheme significantly enhances the resilience of VCTS cooperative control under JAs, offering a robust solution for ensuring the stable operation of HHR.