Simulation-Based Assessment of Parking Constraints for Automated Mobility on Demand: A Case Study of Zurich

In a coordinated mobility-on-demand system, a fleet of vehicles is controlled by a central unit and serves transportation requests in an on-demand fashion. An emerging field of research aims at finding the best way to operate these systems given certain targets, e.g., customer service level or the minimization of fleet distance. In this work, we introduce a new element of fleet operation: the assignment of idle vehicles to a limited set of parking spots. We present two different parking operating policies governing this process and then evaluate them individually and together on different parking space distributions. We show that even for a highly restricted number of available parking spaces, the system can perform quite well, even though the total fleet distance is increased by 20% and waiting time by 10%. With only one parking space available per vehicle, the waiting times can be reduced by 30% with 20% increase in total fleet distance. Our findings suggest that increasing the parking capacity beyond one parking space per vehicle does not bring additional benefits. Finally, we also highlight possible directions for future research such as to find the best distribution of parking spaces for a given mobility-on-demand system and city.