Semi-on-demand off-peak transit services with shared autonomous vehicles — service planning, simulation, and analysis in Munich, Germany

Shared Autonomous Vehicles (SAVs) enable transit agencies to provide more agile and responsive services. This study investigates the implementation of semi-on-demand (SoD) hybrid-route services using SAVs on existing transit lines at off-peak hours, leveraging the additional capacity brought by lower operating costs of SAVs. SoD services combine the cost efficiency of fixed-route buses with the flexibility of on-demand services. SAVs first serve all scheduled fixed-route stops, then drop off and pick up passengers in the pre-determined flexible-route portion, and return to the fixed route. This study addresses three key questions: optimal fleet and vehicle sizes for peak-hour fixed-route services with SAVs, optimal off-peak SoD service planning, and service feasibility during a gradual transition from drivers to autonomous vehicles. The methodology combines analytical modeling for service planning with agent-based simulation for operational analysis. We examine ten bus routes in Munich, Germany and demonstrate that the lower operating costs of SAVs improve service quality through increased frequency and smaller vehicles, even in transition scenarios. At off-peak hours, SoD service satisfies up to 80% more requests and reduces generalized costs by up to 50% compared to traditional fixed routes. However, during transition, maintaining a mixed fleet heavily limits headway improvements, thereby limiting the benefits to short flexible-route lengths.