Demand analysis in urban air mobility: A literature review

Abstract

<p>Urban air mobility (UAM) is a novel concept that is revolutionizing urban transportation. This transformation is largely due to the development of electric vertical take-off and landing (eVTOL) vehicles, which have made UAM a reality in the urban region. The success of this emerging mode of transportation is largely dependent on market demand. However, there is a lack of <a href="https://www.sciencedirect.com/topics/social-sciences/systematic-review" title="Learn more about systematic reviews from ScienceDirect's AI-generated Topic Pages">systematic reviews</a> on demand analysis for UAM. To address this gap, we conducted a comprehensive review of the recently published literature on demand analysis for UAM. We firstly identified the demand for UAM in various types of on-demand applications, including passenger services, cargo services, and other services. Secondly, we discussed and identified the factors that influence the market demand in UAM, such as time, cost, distance, congestion, safety, privacy, and noise. Additionally, we examined the existing qualitative and quantitative methods for demand analysis in UAM. We found that the most common techniques include stated-preference surveys, discrete choice models, and clustering algorithms. We further discussed the role of market demand in the UAM life cycle, highlighting the potential impacts of demand on the development, implementation, and regulation of UAM systems. Finally, we concluded our review by highlighting several opportunities for future research related to demand analysis for UAM, and these include feasibility of air shuttle services, potential cargo applications, public acceptance, infrastructure placement, integration with existing transportation, and novel demand estimation methods, while addressing various aspects of UAM life cycle, including vehicle technology, infrastructure, airspace, and <a href="https://www.sciencedirect.com/topics/social-sciences/operations-management" title="Learn more about operation management from ScienceDirect's AI-generated Topic Pages">operation management</a>.</p>