Integrated Control and Planning of Virtual Coupled Modular Pods for Energy-Efficient Railway Operation

Abstract

Sustainable and demand-adaptive railway operation requires frameworks capable of aligning service capacity with time-varying demand while ensuring safe, operationally feasible, and energy-efficient service. This paper proposes an integrated control-and-planning framework for modular pod-based railway operation based on virtual coupling. The framework combines a convoy control layer, which ensures safe and dynamically feasible virtually coupled operation, with a planning layer formulated as a mixed-integer linear programming (MILP) model for daily service allocation and convoy sizing. This hierarchical automation architecture coordinates real-time convoy control with service-level planning to adapt capacity to passenger demand. The proposed methodology is evaluated through comparative simulations under peak-hour, shoulder-period, and off-peak demand scenarios, as well as over a daily schedule of 20 services. Its performance is compared with a conventional fixed-composition diesel-electric multiple unit (DEMU)-based operation. Results show that the pod-based configuration increases energy consumption under peak-hour conditions, remains comparable during shoulder periods, and substantially reduces energy consumption in off-peak operation, achieving a 57% saving in that regime. At the daily level, total energy consumption decreases from 3864 kWh to 3075 kWh, corresponding to a 20% reduction. These findings indicate that the main value of the proposed framework lies in transforming convoy composition into a demand-adaptive operational variable, thereby improving energy performance at the daily system level while preserving the safe and dynamically feasible operation of virtually coupled pod formations.