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Predicting how MaaS and self-driving will affect a major region

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The Oslo Study explores how Mobility as a Service (MaaS) and autonomous vehicles will affect Norway’s capital and its region. Based on PTV Group’s software, the findings provide the basis for decisions on infrastructure investments and urban development.

The Oslo Study – How Autonomous Cars May Change Transport in Cities was conducted by COWI consultancy and PTV Group, on behalf of Ruter, the Oslo region public transport company. It was published in 2019.

Using PTV models, researchers analyzed how shared on-demand fleets of autonomous vehicles may impact travel around Oslo, and how they will integrate with the existing public transport system.

The PTV models focused on three elements: the operator performance (costs), the passenger level of service (convenience) and the city-wide social benefits (congestion and environment). The modeling demonstrated how fleets of autonomous vehicles will potentially impact kilometers traveled, the number of cars to cover demand, and level of service to customers.

The study consisted of six scenarios, each modeling up to 55,000 vehicles and 37 million trips, representing different levels of ride sharing and public transport usage. They were compared to a base scenario of a traditional transport model. Among the main findings:

  • The number of cars can be reduced by between 84%-93%.
  • If all the region’s people share cars and use ridesharing, just 7% of the cars used today will be sufficient to cover all journeys in the rush hours. 
  • The scenario with the biggest reduction in traffic – 14% - is where users of public transport continue to do so, while car drivers switch to ridesharing. 
  • The volume of traffic would increase by 97% if all current drivers and public transport users switched to car-sharing, but without ridesharing. 

Another finding is that the integration of MaaS with an attractive public transport system and active modes of mobility is important. 

Due to the uncertainty that autonomous cars bring, planning the right infrastructure investment is challenging. PTV technology, however, enables cities and regions to test many variables of MaaS operations, such as travel demand, fleet size, waiting times, and detours. Combining these variables produces a range of scenarios, enabling customers to choose the best business model.

The results


PTV models create diverse scenarios of mobility usage and demand

Benefit tile ecology

Models reveal massive reduction in cars and traffic can be achieved

Planning future investment and development becomes clearer

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