Two-Stage Optimal Trajectory Planning Based on Resilience Adjustment Model for Virtually Coupled Trains

Virtual coupling is proposed as an innovative solution to meet the growing transport demand and to further improve the service quality of railways. Nevertheless, obtaining the optimal driving strategy that enhances its transport capacity and energy efficiency remains a challenging task. In order to achieve these objectives, this paper presents a novel convoy optimization method that optimizes the recommended trajectories for virtually coupled trains. A resilience adjustment model is firstly proposed to evaluate the coupling process and generate candidate trajectories according to the adjustment rules. In addition, the convoy optimization problem is formulated as a two-stage programming model consisting of a multi-objective programming stage and a least-cost goal programming stage, which determine the optimal trajectories for trains. Taking into account the requirements of practical applications, the solution method is finally designed to solve the proposed model and achieve dynamic updates of the recommended trajectories throughout train operations. Based on the field data from the Wuhan-Guangzhou high-speed railway line, numerical experiments are conducted to validate the effectiveness of the proposed method. The experimental results indicate that the proposed method shows the best performance in terms of infrastructure utilization and energy consumption, and the spacing between virtually coupled trains is well maintained regardless of ideal or disturbing conditions.