Agent-based Impact Assessment of Regional Air Mobility

This study addresses the limited demand-based evidence on Regional Air Mobility (RAM) by estimating its potential demand for regional and inter-regional travel (40–1000 km) from Germany to domestic and intra-European cross-border destinations. We extend a Germany-centered agent-based model to simulate RAM demand in an early-deployment scenario, a few years after the initial ramp-up phase. RAM adoption is modeled using stated-preference data capturing willingness to pay for travel-time savings and socio-demographic heterogeneity. Results indicate that RAM can reduce average door-to-door travel times by 1.2 h compared with travelers’ current modes, with the greatest benefits on routes over 400 km by driving distance. Emissions reductions are achievable when RAM replaces conventional air or car travel, though net impacts depend on first- and last-mile mode. Adoption and accessibility benefits are concentrated among business and higher-income travelers, while improvements for non-urban areas remain modest, raising concerns about spatial and social equity. Routes with the highest RAM shares differ from those with the highest RAM demand, and high-share routes tend to be lower-volume but show clearer benefits. Implications for planning and policy include ensuring sufficient aircraft range, pricing that broadens uptake, and targeted service design, alongside low-carbon first- and last-mile connections. Deployment decisions should balance potential demand, expected market share, and system impacts to maximize benefits. Early coordination is needed to address potential constraints in regional airport energy infrastructure.