Assessing the Impact of Electric Vehicles on Traffic Emissions: An Agent-Based Modeling Approach considering Traveler Behavior Changes

The COVID-19 pandemic has significantly altered commuter behavior in New York City, leading to decreased public transit ridership and increased personal vehicle use, which exacerbates traffic congestion and greenhouse gas emissions. This study employs an agent-based modeling approach using the multi-agent transport simulation framework to evaluate the impact of electric vehicle adoption on traffic emissions under various post-pandemic transit recovery scenarios. A case study is conducted for New York City to assess potential electrification plans in order to meet climate goals. In the optimistic scenario, where transit ridership recovers to 92% of pre-pandemic levels in the near future, resulting car trips increase by 110%, vehicle miles traveled rise by 107%, and greenhouse gas emissions grow to 106% of baseline levels. Under these conditions, implementing electric vehicle penetration rates above 40% can achieve a 40% reduction in GHG emissions from pre-COVID levels, significantly contributing to improved air quality and climate goals.