Impacts of On-Demand Shuttle System Parameters on its Metrics: A Microsimulation Study

The essence of an on-demand shuttle system is an intelligent matching algorithm, where vehicles and passenger requests are matched to each other in an optimized way. Many studies have touched upon this issue by using macroscopic simulation or agent-based simulation. Modelling on-demand shuttle systems in microsimulation can be very advantageous since it is in general a good means to analyze traffic management measures and new mobility concepts. The aim of this paper is to model an on-demand shuttle system in microsimulation environment and analyze the impact of its system parameters which are fleet size, vehicle capacity, maximum waiting time and maximum detour ratio on some metrics such as served requests ratio, shared rides ratio, average waiting time and average detour time.