Mode choice modeling of electric air taxis for long-distance airport trips

This research examines consumer preferences for electric air taxis (EATs) as a transportation option for long-distance trips to and from airports. The study conducted a stated choice experiment with 1,028 US adults traveling 75-200 miles to and from airports, comparing EATs with private vehicles, public transportation, and transportation network companies. Using integrated choice and latent variable models, the research found that in-vehicle travel time, cost, and access time significantly influence mode choice, with access time being particularly critical for Electric Assisted Travel (EAT). The study revealed that EATs had the highest value of travel time savings at $46.09 per hour. Autonomy in travel modes presented disutility across all options, with the strongest negative impact on EATs. Perceived ease of use was highest for EATs, while perceived trust was highest for public transport. The findings offer valuable insights for stakeholders regarding the EAT market's potential and implementation strategies.

This white paper examines the market viability and consumer acceptance of electric air taxis for long-distance airport transportation through comprehensive mode choice modeling. As urban congestion and environmental concerns intensify, electric air taxis represent a promising solution for efficient and sustainable airport access.

The research employed a sophisticated stated-choice experiment involving 1,028 US adults who regularly travel 75-200 miles for airport trips, analyzing preferences among electric air taxis, private vehicles, public transportation, and transportation network companies like Uber and Lyft.

The study employed integrated choice and latent variable (ICLV) models to capture both observable attributes and psychological factors that influence mode selection. Key findings revealed that access time is the most critical factor for EAT adoption, with travelers valuing time savings at $46.09 per hour for EATs, which is higher than for any other mode studied. Service frequency emerged as another crucial determinant, with a reduced frequency significantly decreasing the odds of EAT selection. Interestingly, autonomous operation of vehicles showed negative utility across all modes, with EATs experiencing the strongest adverse effect.

Psychological factors played a substantial role in mode choice. While EATs scored highest in perceived ease of use, public transport maintained the greatest perceived trust among travelers. The research demonstrated that bundling luggage costs into total EAT fares significantly increased preference compared to separate fee structures. Demographics also influenced choices, with higher-income individuals and those with positive environmental attitudes showing a greater preference for EAT.

These findings offer critical insights for the emerging air taxi industry. Airlines, airport operators, and policymakers can leverage this data to develop effective EAT implementation strategies, pricing models, and service designs. The research suggests that successful EAT deployment requires addressing access infrastructure, maintaining frequent service, building consumer trust, and implementing transparent pricing strategies.

This comprehensive analysis provides a foundation for understanding the transformative potential of electric air taxis in revolutionizing long-distance air travel.