A Socio-Technical Agent-Based Approach for Optimizing Electrical Vehicle Adoption

The transition to sustainable transportation systems is a critical component of global efforts to reduce carbon emissions and mitigate climate change impacts. Among various sustainable technologies, electric vehicles (EVs) have emerged as a promising solution. However, the adoption rate of EVs is influenced by a complex interplay of socio-economic factors, technical variables, and infrastructure development. This paper presents a novel application of Agent-Based Modeling (ABM) to analyze and optimize the adoption process of EVs by capturing the dynamics of multiple interacting agents including households, industries, and power generation companies. A Living Lab approach complements the model by providing empirical data through participatory methods, thereby enriching the model’s applicability and accuracy.