Optimal Scheduling for Customized Bus Charging based on Modular Electric Vehicles

Modular electric vehicles (MEVs) empowered by autonomous vehicle technology have emerged as an efficient solution for demand-responsive transit systems, such as customized buses (CBs). Their modularity allows on-road coupling and decoupling, offering flexibility in terms of capacity, charging, and scheduling. This work introduces a novel modular electric customized bus (MECB) charging scheduling problem, aiming to minimize both travel and charging costs while ensuring service quality. We propose a mixed-integer programming model to jointly determine module routes, schedules, charging, formation, and passenger-to-module assignment, considering non-linear charging behavior and economies of scale in formation. To solve this model, an Adaptive Large Neighborhood Search (ALNS)-based solution approach is developed. Finally, a large-scale data experiment is conducted to validate the efficiency of the introduce methodology.