Nationwide Impact of Air Taxis on Energy Consumption and Road Traffic Dynamics

Abstract: The deployment of electric air taxis (eVTOLs) promises a transformative impact on urban mobility by alleviating traffic congestion and reducing energy consumption. This study introduces the Nationwide Energy Estimation for Air Taxis (NEAT) model, an advanced agent-based framework that evaluates the impact of air taxis on energy consumption and road dynamics in various urban settings. NEAT integrates an agent-based behavioral simulation, an energy estimation model, and a scale-up methodology, providing a comprehensive analysis from corridor level to national level assessments.The findings reveal that air taxis can significantly reduce fuel consumption and traffic congestion, especially during peak hours in heavily congested corridors. Covering the 15 most congested cities in the United States, the study highlights the potential for a 3.35\% reduction in energy use on Interstate highways and a 6. 92\% reduction in local arterials throughout the country with the scale-up model. Cities such as Boston, Washington DC, and Seattle demonstrate higher percentages of energy savings due to their severe congestion levels, which make air taxis a more attractive option. The study provides valuable information for policy makers and urban planners, emphasizing the role of air taxis in promoting energy efficiency and reducing urban congestion.

Although we refer to this as a nationwide impact quantification, it is important to note that the current study area represents only the initial phase of our research. The scope of our study is expected to expand in subsequent phases to include additional cities and regions, providing a more comprehensive analysis of the potential nationwide impact. This initial effort is a critical step in understanding the feasibility and effectiveness of air taxis in high-density urban environments, which are likely to see the earliest and most significant adoption of this technology. Hence, future research directions include exploring the scalability of the model to other cities and regions, refining the assumptions related to demographic factors and road characteristics, and incorporating more detailed data on travel behaviors and preferences. Furthermore, future studies could focus on economic implications, including cost-benefit analyses and potential market adoption rates, to better understand the commercial viability and policy implications of air taxi deployment.