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Commuter demand estimation and feasibility assessment for Urban Air Mobility in Northern California

Author

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  • Rimjha, Mihir
  • Hotle, Susan
  • Trani, Antonio
  • Hinze, Nicolas

Abstract

This study aims to estimate passenger demand for Urban Air Mobility (UAM) and analyze the feasibility of operating the system in Northern California. UAM is a concept mode of transportation that is designed to bypass ground congestion for time-sensitive, price-inelastic travelers using autonomous, electric aircraft with Vertical Takeoff and Landing (VTOL) capabilities. This study focuses specifically on commuting trips, which are frequent and considered relatively more time-sensitive than other types of personal trips. The UAM mode's feasibility is studied using sensitivity analysis of UAM demand to cost per passenger mile and the number of vertiports placed in the region. This study also explores the spatial distribution of UAM demand in Northern California, which further helps in identifying the major commuter trip-attraction and trip-production zones for the UAM mode in the region. The results indicate that sufficient UAM demand for commuting trips can only be reached at optimistically low UAM offered fares. These fare levels could be challenging to obtain given the high real estate cost in Northern California's urban regions. Moreover, the reliability of the UAM mode must be comparable to the automobile mode; otherwise, it loses significant demand with increasing delays. The results also show that the commuting flows with promising UAM demand in Northern California are heavily one-directional, with San Francisco Financial District being a major attraction. Other types of trips should also be considered along with commuting trips to generate an economically viable system and reduce deadheading.

Suggested Citation

  • Rimjha, Mihir & Hotle, Susan & Trani, Antonio & Hinze, Nicolas, 2021. "Commuter demand estimation and feasibility assessment for Urban Air Mobility in Northern California," Transportation Research Part A: Policy and Practice, Elsevier, vol. 148(C), pages 506-524.
    • Handle: RePEc:eee:transa:v:148:y:2021:i:c:p:506-524
    DOI: 10.1016/j.tra.2021.03.020
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    1. Li, Zhi-Chun & Sheng, Dian, 2016. "Forecasting passenger travel demand for air and high-speed rail integration service: A case study of Beijing-Guangzhou corridor, China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 94(C), pages 397-410.
    2. Greene, William H. & Hensher, David A., 2007. "Heteroscedastic control for random coefficients and error components in mixed logit," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 43(5), pages 610-623, September.
    3. Larranaga, Ana Margarita & Arellana, Julian & Senna, Luiz Afonso, 2017. "Encouraging intermodality: A stated preference analysis of freight mode choice in Rio Grande do Sul," Transportation Research Part A: Policy and Practice, Elsevier, vol. 102(C), pages 202-211.
    4. Börjesson, Maria & Fosgerau, Mogens & Algers, Staffan, 2012. "On the income elasticity of the value of travel time," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(2), pages 368-377.
    5. Winter, Scott R. & Rice, Stephen & Lamb, Tracy L., 2020. "A prediction model of Consumer's willingness to fly in autonomous air taxis," Journal of Air Transport Management, Elsevier, vol. 89(C).
    6. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521766555.
    7. Arne Risa Hole, 2007. "Fitting mixed logit models by using maximum simulated likelihood," Stata Journal, StataCorp LLC, vol. 7(3), pages 388-401, September.
    8. Li, Weibo & Kamargianni, Maria, 2018. "Providing quantified evidence to policy makers for promoting bike-sharing in heavily air-polluted cities: A mode choice model and policy simulation for Taiyuan-China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 111(C), pages 277-291.
    9. Carrion, Carlos & Levinson, David, 2012. "Value of travel time reliability: A review of current evidence," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(4), pages 720-741.
    10. Cherchi, Elisabetta & Ortúzar, Juan de Dios, 2006. "On fitting mode specific constants in the presence of new options in RP/SP models," Transportation Research Part A: Policy and Practice, Elsevier, vol. 40(1), pages 1-18, January.
    11. Ahmed, Sheikh Shahriar & Fountas, Grigorios & Eker, Ugur & Still, Stephen E. & Anastasopoulos, Panagiotis Ch, 2021. "An exploratory empirical analysis of willingness to hire and pay for flying taxis and shared flying car services," Journal of Air Transport Management, Elsevier, vol. 90(C).
    12. Al Haddad, Christelle & Chaniotakis, Emmanouil & Straubinger, Anna & Plötner, Kay & Antoniou, Constantinos, 2020. "Factors affecting the adoption and use of urban air mobility," Transportation Research Part A: Policy and Practice, Elsevier, vol. 132(C), pages 696-712.
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