Electric vehicle market dynamics: A multi-agent approach to policy, infrastructure, and consumer behavior

The transition to sustainable mobility is a critical component to reducing carbon emissions. However, the adoption of electric vehicles (EVs) is influenced by complex interactions among various stakeholders, including consumers, energy companies, and government bodies. This paper presents an agent-based model (ABM) of electric vehicle adoption and a multi-agent system (MAS) implemented to simulate and analyze these interactions within the EV market. By means of year-based temporal simulations, the framework provides insights into the factors driving EV adoption, consumer satisfaction, and the economic viability of energy infrastructure investments. A key strength of our ABM approach is its ability to capture the emergent dynamics arising from local interactions among heterogeneous agents. These micro-level behaviors collectively form a complex ecosystem that can influence the decision-making processes of higher-level stakeholders such as governments and firms, an aspect that is typically unaddressed in more aggregated, non-agent-based approaches. We test our model by simulating the EV market of a mid-sized city (170,000 inhabitants). Across several experimental scenarios, the system demonstrates how local strategic interactions among heterogeneous agent types give rise to emergent global outcomes and collective behavioral patterns. For example, improvements in charging speed and station availability can enhance user experience and facilitate broader EV adoption. Likewise, optimizing service station configurations can influence driver decision-making, leading to increased profitability for energy providers. This framework captures emerging market behaviors and serves as a robust tool to evaluate the impacts of various policies and market conditions, supporting informed decisions toward sustainable transportation solutions.