Nationwide MOIA simulation on Autonomous Ridepooling
MOIA’s Mobility Consulting team conducted a comprehensive analysis to assess the impact of a nationwide autonomous ridepooling service. By leveraging mobile network data, the team calculated the scale of daily mobility across Germany: Approximately 300 million trips are taken each day. Of these, 157 million trips fall within the 1.5 to 50-kilometer range, an ideal distance for ridepooling services.
In the simulation, 12 million of these trips were assigned to an autonomous ridepooling service, corresponding to a four-percent modal share. These trips could be served by 300,000 autonomous cars, each averaging 1.7 passengers and a wait time of just ten minutes, across both rural and urban areas. The result? A highly efficient system offering consistently high service levels. Specifically, each autonomous car in the simulation could complete 40 trips per day, with an average trip length of 16 kilometers, totaling 183 million passenger kilometers daily.
What impact could a nationwide autonomous ridepooling service have?
Key findings at a glance:
- In the simulated scenario, the model indicates up to 5 million tonnes lower CO₂ emissions per year compared with the reference scenario.
- Improved accessibility in both urban and rural areas, without the need for new infrastructure
- Greater efficiency, reduced congestion, and new opportunities for industry and society
In the simulation, shifting a share of current private car and public transport trips to a nationwide autonomous ridepooling service increases the transport performance of the mobility modes considered together. Under the assumptions used in the model, this results in up to 5 million tonnes lower CO₂ emissions per year compared with the reference scenario. In the simulated scenario, passenger transport activity across public transport, cycling and ridepooling increases by around 40 percent compared with the baseline scenario.
The simulation also indicates potential reductions in vehicle emissions, congestion-related external costs, and demand for vehicles and parking space under the assumptions used in the model. The simulation assumes a fully electric ridepooling fleet. The vehicles produce no local tailpipe emissions while driving. The model also takes into account potential effects on external costs associated with emissions and noise.
In the simulated scenario, the model indicates a reduction in external costs of around €3.6 billion per year, including external costs associated with emissions, accidents, congestion and noise.
