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Study Examines Impact of Self-Driving Services on Gothenburg Public Transport
The report was to analyze how self-driving vehicles will affect the city by modelling different scenarios, using Gothenburg’s multimodal modelling platform in PTV Visum software.

The project brought together researchers and traffic analysts from Trivector and the Swedish knowledge center for public transport, K2.
Photo: PTV Group
The PTV Group released a new report based on a simulation model, which explored potentials and risks of electric, shared, and self-driving vehicles in the Swedish city of Gothenburg.
The report was to analyze how self-driving vehicles will affect the city by modelling different scenarios, using Gothenburg’s multimodal modelling platform in PTV Visum software.
The project brought together researchers and traffic analysts from Trivector and the Swedish knowledge center for public transport, K2.
In the virtual environment of PTV Visum, the researchers examined several possible developments. They focused on two forms of AV usage: car-sharing, where people use self-driving services privately, and ride-sharing, where AVs are shared with other passengers, who have a similar destination.
The researchers looked at different scenarios:
What happens if 33% of today’s car trips shift to AV ride-sharing?
What effects occur if 100% of people shift from private cars or public transport to car-sharing or to shared, self-driving services?
The project team analyzed travel times, number of vehicles, and vehicle mileage.
The simulation results show that an increase in the use of self-driving vehicles does not automatically lead to less traffic, as often predicted. The total number of vehicles in the traffic network can vary without reducing the vehicle milage.
With shared self-driving vehicles, the total number of vehicles in the traffic system might be significantly less, but each vehicle drives more.
Several of the simulated scenarios resulted in an increased traffic volume, despite a reduction in the overall number of vehicles.
Here are some other main findings of the study:
The transition to AV car-sharing leads to a 25-30% higher traffic volume than the transition to AV ride-sharing
If people switch from private cars to electric, self-driving ride-sharing options, traffic volume decreases by up to 6%. The shift from today’s private cars to AV car-sharing makes traffic rise up to 15%
If in addition to today’s car users, public transport users switch to AV services, traffic increases in both the car-sharing and the ride-sharing scenario.
The transfer from today's car traffic to AV ride-sharing and AV car-sharing reduces the volume of vehicles on the road by up to four-fifths of today’s volume. This would likely reduce the need for parking spaces and purchase of new vehicles
“There are many uncertainties and open questions on how the autonomous future will develop," said Kim Örn, PTV Group. "For instance, if AVs will increase our desire to travel more? How quickly society will adopt them? Digital models allow us to simulate in multiple combinations of assumptions which produce a range of future outcomes. The range of results enables planers to understand which assumptions have a greater or lesser influence on the outcome, stakeholders can make decisions with increased confidence.”
The researcher said that planning, legislation, and regulations must be aligned around AV ride-sharing services to ensure that AVs contribute to a sustainable mobility ecosystem in the future.
“Our work clearly shows that self-driving vehicles will have a major impact on the transport system and if applied correctly, they will create economic, ecological and social sustainability benefits. But we must continue to develop our understanding of the concept through simulations, test beds and by understanding people's attitudes” said Fredrik Larsson, head of analysis at the Urban transport administration at the city of Gothenburg.
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