Optimizing timetabling and platoon formation of shuttle transit with modular autonomous vehicles considering time-dependent passenger demand

Traditional public transit with fixed vehicle capacity often leads to underutilization, especially during off-peak hours. Modular autonomous vehicles (MAVs) enable flexible capacity through coupling and decoupling. This study jointly optimizes timetabling and platoon formation for an MAV-based shuttle system under time-dependent demand. A bi-objective model balances operator and passenger costs, solved via the ε-constraint method to obtain Pareto-optimal solutions. A case study confirms the model’s effectiveness, demonstrating that the MAV system reduces total operating costs and improves service—achieving a 73.70% decrease in empty seat time and a 29.75% reduction in passenger waiting time compared to traditional fixed-capacity transit.