Norway is leading the way in promoting zero- and low-emission vehicles. The high share of electric cars brings important environmental benefits but also creates new challenges, such as increased congestion, reduced competitiveness of greener transport modes, and lower government revenues. Efficient policies—such as road pricing—can help strike a better balance between costs and benefits for society.
By combining different methods and collecting a rich set of data, A-PLANET seeks to answer research questions that can support the transition to a more sustainable transport system. The project is a collaboration between the Institute of Transport Economics (TØI), the University of Oslo (UiO), and the University Carlos III of Madrid (UC3M).
In spring 2024, the team conducted a large-scale field experiment to test the effects of road pricing on driving behavior and public acceptance. Results show that distance-based charges—varying by location, time of day, and vehicle type—reduce the societal costs of driving by more than 5%. Most of this reduction came from drivers without electric vehicles, during off-peak hours, and on non-work trips. Information about the benefits of road pricing proved to be critical for building public support, whereas direct experience with road pricing had little effect in the short term. The team is now preparing a scientific article and a policy brief on these results. A visiting PhD student from the University of Siena (Italy), has joined the team in 2025 and is studying topics related to EV vehicles and policy responsiveness building on the initial results.
TØI has also invested in new methods for collecting automatic travel data using mobile apps and innovative GPS technology. A close partnership with the German app provider Motiontag has been central to providing high-quality, high-frequency travel data for the WP1 field experiment. In addition, new routines have been developed to strengthen the recruitment process, particularly through the use of representative samples from the population registry.
In Spain, the project partner has recently recruited a PhD student who will work on A-PLANET. Together, the Norwegian and Spanish teams have reviewed relevant academic literature and policy documents, and carried out several rounds of data collection in both countries in 2023 and 2024. Particular attention has been given to the differences between current situation and the potential of introducing road pricing, using electronic surveys and stated-choice experiments. Findings suggest that many respondents prefer universal road pricing over existing tolls and fuel taxes—but support depends on the price level and, importantly, on how revenues are spent. Using advanced methods such as latent class analysis and machine learning, the team has also identified distinct groups of respondents with different preferences and studied the role of social norms in shaping attitudes. The team has published a TØI report and is working on at least two publications.
After evaluating several transport models for simulating the effects of policy measures, we selected the Regional Transport Model (RTM) for Oslo and Viken county. This model makes it possible to conduct cost–benefit analyses and to assess how costs and benefits are distributed between different groups, providing a deeper understanding of acceptability that complements analyses in other work packages. The model has already been used in the design of the field experiment. A scientific article has been submitted to a peer-reviewed journal, where the team also develops political-economy perspectives on why certain road pricing reforms—despite very high social net benefits—are so difficult to implement. The reasons include distributional impacts across demographic groups and regions, vertical tax conflicts between local and national authorities, and timing within the political business cycle.
Researchers in A-PLANET have actively shared results at several conferences, workshops, and seminars, and are now planning a new project meeting to consolidate progress and shape future research. The project has also provided valuable opportunities for students: one master’s thesis examined social norms in travel choices at NMBU, an international student visiting from the US contributed to survey analysis and report in WP2, and two master’s students from the University of Bergen will next semester write theses on gender aspects of transport policy and road pricing. In addition, two PhD students are developing 2–3 scientific articles each, building on the data and research themes of A-PLANET.
A-PLANET is an interdisciplinary project that will create new knowledge and sound empirical evidence acquired by experimentation that will fill important knowledge gaps within transport, behavioral, environmental and political economics. By using a mix of methods from economics, psychology, political and data science, and gathering a rich set of different data, the project aims to answer a set of bold research questions that will contribute to the shift to a sustainable transport system. The overarching focus is to address the tradeoff between policy effectiveness and acceptability in the transport sector, in search for the optimal balance. Results from the use of a newly developed transport model will provide a valuable starting point for identifying the most promising policy options. We will then develop ad-hoc choice experiments to understand how to facilitate policy acceptability, specifically applied to the transport sector. The combination of these results will generate important new insights and enable us to map key factors influencing public acceptability and relevant heterogeneities. The project will then integrate behavioral insights (including gamification techniques) and factors associated with increased public acceptability directly in the design of new policy instruments, which will then be empirically tested through a large scale Randomized Controlled Trial (RCT) in the field, both in isolation and as policy packages. By using an RCT, the gold standard of research, we will identify causal effects of policies on transport behavior. Finally, these results will be used to re-calibrate the transport model and analyze the costs and benefits of policies aiming to strike the optimal balance between efficiency and acceptability when scaled up to city level. The model results combined with sound empirical evidence from the experiments will provide a solid foundation for policy recommendations.
