Author
Ivana Moerland-Masic, Fabian Reimer, Maria Stolz, Thomas-Matthias Bock
Abstract
Within German Aerospace Center (DLR), a project called HorizonUAM was launched in July 2020. Its main goal is to develop and design an aerial vehicle which would support the infrastructure of the ever-growing cities and strengthening the connection between as well the big cities as cities with their suburban areas. The vehicle will be designed for the four different scenarios: airport shuttle, intracity transport, intercity transport and suburban connection. This paper shows the research concerning the potential users of the vehicle including their requirements and shows a possible design solution for an airtaxi cabin. The process has followed the Design Thinking Method, ensuring a central role for the users. To determine whether there are potential passengers willing to use such a vehicle, in-depth research has been done. Data found in previously done research has been compared with results of the in-house research, consisting of a number of workshops with representatives of German population as well as results form questionnaires sent out to a different group of German population. During the workshops, the subjects were asked not only to indicate their opinion on the airtaxis, but also to create their own version of it. This was done following the so-called Disney method, creating the solution in three stages: dreamer, realist and critic. Based on this data, different fictive personas are created, to aid in understanding of the user’s needs. In addition, trend analysis on how the urban mobility is developing, has also been executed. The state-of-the-art solutions available are analyzed and their strengths and weaknesses determined. The entire research has resulted in an extensive list of requirements for the design of the cabin. To address such a complex design challenge, a morphological chart has been created, systematically deconstructing the main function into subfunctions. This has been done by multiple workshops with a constant team.