Fleet control algorithms for automated mobility: A simulation assessment for Zurich

Abstract

The performance of four different dispatching and rebalancing algorithms for the control of an automated mobility-on-demand system is evaluated in a simulation environment.The case study conducted with an agent-based simulation scenario of the city of Zurich shows that the choice of an intelligent rebalancing algorithm decreases the average wait time in the system.For a wait time of four minutes at peak hours the best performing algorithm requires the same price per vehicle kilometer as a private car today.The results indicate that shared mobility systems of automated vehicles will reach higher occupancy rates than conventional private cars.