Global UAM Demand: Concept of a model-based Forecasting Approach

Kurzfassung

Increasing urbanization leads to a growing need for new transportation concepts for urban environments. Therefore, many different mobility solutions have been proposed and investigated in recent years. Due to the increasing advances in new vehicle concepts and technologies, especially in the field of battery technologies, the integration of Urban Air Mobility (UAM) into existing urban transport systems as a supplementary component is becoming more and more conceivable. In general, the term UAM is associated with an air transport system based on a high-density vertidrome network and air taxis services within an urban environment. While initial eVTOL manufacturers plan to have UAM vehicle certification by 2023 and start first operations in 2024, the global market potential of UAM is still unclear. A preliminary estimation of potential UAM demand, the associated number of flight movements and the required number of vehicles would be helpful for manufacturers to plan ahead upcoming production at an early stage. However, forecasting the global UAM demand involves a number of challenges. In order to take into account the different characteristics (e.g. built-up area, number of inhabitants, mobility patterns) of cities worldwide, a forecasting method is needed that is as simple and transferable as possible for all cities without having to create individual, city-specific transport models. Currently, there are only few preliminary estimations for the global UAM market development. In addition to initial estimates from consulting companies, Mayakonda et al, Anand et al, and Straubinger et al in particular have published initial estimates for global UAM demand. All three publications focus on an approach where cities are grouped into clusters and analyses are conducted for one representative city for each cluster. As part of the HorizonUAM project, a different forecasting method is proposed and being set up to provide first estimates of the potential global UAM demand. The concept relies on a model-based approach that uses a limited number of parameters of each city to estimate total transport demand for each city. Based on this, the probability that travelers will choose the air taxi for their individual trips within a city is determined, considering travel distances and characteristics of the air taxi and an alternative means of transport. By summing up all city-specific results, an estimate of global UAM demand is provided. Variation of major characteristics of the UAM transport system allows different scenarios to be developed and analyzed.