Exploring Policy Interventions to Promote Equitable Electric Vehicle Adoption Using Agent-Based Modelling
T.L. Dert (TU Delft - Technology, Policy and Management)
C.N. van der Wal – Graduation committee member (TU Delft - System Engineering)
M. Comes – Graduation committee member (TU Delft - Transport and Logistics)
Yashar Araghi – Mentor (TNO)
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Abstract
This master’s thesis investigates how policy interventions affect the speed and equity of electric vehicle (EV) adoption in the Netherlands, using an agent-based model (ABM) grounded in behavioural decision-making. The model simulates household-level adoption decisions between 2022 and 2035, drawing on the CODEC framework to reflect attention, enabling conditions, and intention formation. Socio-demographic diversity is represented through spatially clustered household archetypes based on income, education, and infrastructure access. The model is calibrated to reflect Dutch conditions and includes an explicit application to The Hague.
The study explores how different combinations of government interventions, including targeted subsidies, infrastructure investment, awareness campaigns, and zero-emission zones, an shape adoption trajectories across neighbourhoods. A key focus is the trade-off between accelerating overall EV uptake and ensuring an equitable transition across socio-economic contexts. In addition to literature-based policy scenarios, an exploratory modelling approach was used to generate and test a wide range of policy timing combinations under uncertainty.
The findings show that while comprehensive strategies (e.g. combining subsidies, marketing, and zero-emission zone regulation) perform best overall, they deliver only modest gains over simpler, well-timed interventions. Improvements of around 5 percentage points in EV share and moderate reductions in inequality are possible, but come with distinct implementation demands. Simpler strategies, such as infrastructure and marketing alone or early subsidies with infrastructure, often achieve comparable outcomes with less complexity.
Overall, the results highlight the importance of behavioural diversity, timing, and adaptability in policy design. A just and accelerated EV transition is feasible, but not automatic, and requires deliberate, strategically layered interventions. Achieving this requires planning further ahead and having adaptive responses ready for an uncertain future. This thesis contributes to the literature on sustainable mobility transitions by integrating behavioural realism, spatial equity, and exploratory policy design into a unified simulation framework.