Simulating Semi-on-Demand Hybrid Route Transit Feeders with Shared Autonomous Mobility Services

Abstract

This study simulates transit feeder services in semi-on-demand hybrid route, integrating fixedroute efficiency with demand-responsive flexibility, operated by shared autonomous vehicles (SAVs). Adapting the simulation framework FleetPy, we assess its performance against traditional fixed and flexible routes on a bus route in Munich, Germany, focusing on cost and service quality. The findings reveal the hybrid model’s potential to improve service accessibility and journey times, contingent on the fixed-flexible route balance. It evaluates the stochastic effects on waiting and riding times due to the on-demand portion, and the optimal settings of route form, fleet size, and headway.