Will automated vehicles help to reduce congestion?

Abstract

Automated vehicles are widely expected to bring about various benefits for (urban) transportation, e.g. by increasing road capacities and reducing generalized cost of travel. However, the latter may induce additional demand for road transportation, possibly counteracting gains in accessibility. Hence, the net impact of vehicle automation on road network performance is still unclear. This research uses the macroscopic fundamental diagram (MFD) to address this question for different levels of road capacity increases and modal splits between private and shared (i.e. public) transportation. To this end, various scenarios are tested in a simulation model for the morning peak hour for Zurich, Switzerland, as a case study, for which current demand levels for car and public transport are used. Yet, the results can be generalized to different city types. The analysis indicates that for car-oriented cities, vehicle automation will likely bring substantial benefits in network performance, while for public transport oriented cities, substantial gains in road capacity of 40 % or more will be required to make up for the potentially substantial mode shift from public transport towards (pooled) cars. Moreover, results show that up to 75 % mode share of ride-sharing trips will be required to achieve a system-optimal state.