A large-scale transition towards electric vehicles would have large environmental benefits regarding energy-efficiency and reduced air pollution in urban areas. Nevertheless, the uptake of electric vehicles is still at a low level. The upfront investment cost and the limited range of electric vehicles are important hindering factors for electric vehicle adoption. On the other hand, the use of electric vehicles is relatively cheap. This is mainly due to the fact that electricity is cheaper per kilometer than petrol or diesel, as well as due to the fact that electric vehicles are more energy efficient. Currently, policy measures are focused on electric vehicle adoption, and in many countries around the world, policy incentives are provided. However, with the low marginal cost of electric vehicle use and battery developments resulting in higher range, there is a risk for increased car travels, which would have negative environmental effects and might increase congestion. In this project, this risk for increased car use is investigated: the conditions under which increased car use is likely to occur and the influence of policy measures and the provision of charging infrastructure are explored using an interdisciplinary approach.

Stated adaptation experiments are used to investigate the behavioral alterations of car users when changing to an electric vehicle. In particular, to combat the negative externalities in increased car uses after EV adoption, the study has designed three incentives that aim to reduce private car trips into the already congested city centers. The incentives were a combination of 1) free EV parking and charging outside of the congestion area(of Stockholm) and an additional reduced-fare 2) public transport- or 3) e-scooter. To test the effectiveness of the incentives, the study has designed a stated adaptation experiment and a custom web map based survey tool that most importantly allowed the respondents to record desired locations for their incentives, thereby providing an indication of public charging infrastructure demand and “entrance parking”(infartsparkering). 400 of the 7000 contacted registered EV users have answered the survey. The so collected data was analyzed using both descriptive statistics and statistical travel behavior modelling. While based on the small sample size the modelling results should be treated with caution, the modelling results can be interpreted as follows:

• The incentives are more effective in deterring female, young (18–24), or part time employed respondents from driving into the city centers than their male, older, or full-time employed counterparts.
• The offer of free parking and charging can “attract” respondents who are currently not parking in the congestion zone or have a difficult time finding parking spot in the congestion zone. Conversely, those who already have confidence in parking opportunities are harder to sway toward leaving the car outside the city center.
• Respondents who are regular public transport users (i.e., are holders of a monthly public transport
• Independent of their public transportation enjoyment level, respondents who have higher perceived safety in public transportation are more likely of choosing an offer of a reduced-fare public transport compared to those who have lower perceived safety levels.
• Respondents who “strongly” enjoy the use of e-scooters and e-bicycles are more likely to take an offer a reduced fare for this mode of transport since this incentive increases their opportunities to use these “enjoyed” modes.

While an initially planned detailed stakeholder analysis could not be carried out during the project period, based on the above results the study outlined several methodologies for stakeholder analysis and policy roadmap creation. Moreover, the above knowledge gained from the travel behavior modelling work is believed to be useful input for ongoing and future policy work towards sustainable electric vehicle use.