Autonomous Ride-Poooling in Hamburg - Results from an Integrated Travel Demand and Fleet Simulation Model

More and more mobility services are appearing on the market that provide customers with a good alternative to private cars through demand-responsive offerings. Since the impact of these services is not always positive, hopes are currently pinned on ride-pooling. Currently, the effects of these bundled trips on the transportation system is limited due to e.g., to small fleets. As drivers account for a large proportion of operating costs, an automated fleet holds great potential for cost reduction and hence a large-scale roll-out. In this study, the traffic effects of an automated ride-pooling service are investigated using the city of Hamburg, Germany as an example. For this purpose, an agent-based travel demand model (mobiTopp) is coupled with a fleet simulation to model the demand and supply sides in detail, respectively. Simulations show that a reduction of fares and a larger service area as well as a larger fleet help to decrease the total vehicle kilometers traveled of private vehicles and mobility services combined. The ride-pooling demand increases by factor while fleet performance indicators improve: The empty mileage decreases from 28.7% to 15.9% and the vehicle occupancy increases from 1.3 to 1.7. A larger service area leads to longer trips on average. However, a base fare guarantees that the number of trips for both active modes and public transportation is hardly affected.