| People | Locations | Statistics |
|---|---|---|
| Serhiienko, Serhii |
| |
| Schmalz, Ulrike |
| |
| Oliveira, Marisa |
| |
| Ribeiro Pereira, Maria Teresa |
| |
| Bellér, Gábor |
| |
| Araujo, M. |
| |
| Frey, Michael | Karlsruhe |
|
| Coutinho-Rodrigues, João | Coimbra |
|
| Wouters, Christian Guillaume Louise | Aachen |
|
| Kessel, Paul J. Van Van |
| |
| Árpád, István |
| |
| Fontul, Simona |
| |
| Kocsis, Dénes |
| |
| Cigada, Alfredo | Milan |
|
| Oort, Neils Van | Delft |
|
| Agárdi, Anita | Miskolc |
|
| Andrews, Gordon E. |
| |
| Sousa, Nuno |
| |
| Witlox, Frank Jacomina Albert | Ghent |
|
| Dobruszkes, Frederic |
| |
| Kiss, Judit T. |
| |
| Hadachi, Amnir | Saint-Étienne-du-Rouvray |
|
| Hamilton, Carl J. | Kunovice |
|
| Misiura, Serhii |
| |
| Schimpf, Marina |
|
Schmalz, Ulrike
in Cooperation with on an Cooperation-Score of 37%
Topics
- COVID-19
- air travel
- aviation
- air traffic
- data
- simulation
- passenger
- vehicle occupant
- architecture
- supporting
- passenger volume
- prototype
- air shipment
- protection
- privacy
- transportation provider
- data protection
- aircraft
- industry
- ponding
- contaminant
- ownership
- flight
- design
- airport
- market
- travel
- face
- seat
- travel time
- revenue
- liquid
- hydrogen
- business model
- passenger service
- airline
- coalition
- technological innovation
- load factor
- rent
- airline alliance
- perception
- traveller
- drone
- assessment
- driver
- city
- taxicab
- traffic behavior
- platinum
- mode choice
- meta-analysis
- air taxi
- demand responsive transportation
- researcher
- traffic mode
- age
- employed
- data file
- rural area
- questionnaire
- transport market
- indicating instrument
- chain
- passenger demand
- bottleneck
- key performance indicator
- travel chain
- future mobility
- modeling
- computer science
- engineering
- impurity
- data analysis
- complex system
- multidisciplinary team
- transportation engineering
- driving
- behavior
- consumer
- stakeholder
- autonomous driving
- transit rider
- profit
- marketing
- expected value
- variable
- income
- regression analysis
- determinant
- education
- urbanisation
- air transport market
- gross domestic product
- definition
- show 65 more
Publications
- 2023Influence of COVID-19 on air travel - A scenario study toward future trusted aviation
- 2022SUPPORTING DOOR-TO-DOOR AIR TRAVEL: TOWARDS A PRIVACY PRESERVING VIRTUAL ASSISTANT FOR PASSENGERS
- 2021Door-to-door air travel: Exploring trends in corporate reports using text classification modelscitations
- 2021A BUSINESS MODEL ENABLING A PASSENGER-DISTANCE-IMPROVED LONG-HAUL NETWORK TO DECREASE TRANSPORT INEFFICIENCIES
- 2021Lessons Learned from a Two-Round Delphi-based Scenario Studycitations
- 2021Exploring trends, status of research and the impact of COVID-19: a mixed-methods approach
- 2021An explorative study of corporate travellers’ perception at a German airportcitations
- 2020Identifying Demand and Acceptance Drivers for User Friendly Urban Air Mobility Introductioncitations
- 2020A survey of German business air traveller
- 2020Door-to-door travel in 2035 – A Delphi studycitations
- 2019Characteristics of Potential User Groups of New Forms of Mobility Using the Example of Urban Air Mobility
- 2019Assessment of Passenger Requirements Along the Door-to-Door Travel Chaincitations
- 2018The European Air Transport System: A Methodological Perspective on System Dynamics Modeling
- 2018Assessment of Passenger Requirements Along the Door-to-Door Travel Chaincitations
- 2018Profiling Future Air Transport Passengers in Europe
- 2017Factors influencing European passenger demand for air transport
- 2012Open Societal Innovation: The Alemannic Definitioncitations
Places of action
booksection
Identifying Demand and Acceptance Drivers for User Friendly Urban Air Mobility Introduction
Abstract
This research aims to develop an assessment framework to analyze the user friendliness of Urban Air Mobility (UAM), a future mode that enables autonomous inner-city, on-demand transport in passenger drones. The relevant demand and acceptance drivers are derived from a meta-analysis of urban mode choice factors and studies on UAM mode choice and acceptance specifically. By applying this framework, the potential of UAM is analyzed in terms of users’ new options in their daily travel behavior, fostering seamless inter- and multi-modal mobility. Considering the factors relevant for gaining users’ confidence, three different operational concepts [UAMaaS (UAM as a service), UAT (Urban Air Taxi) and UAM platinum] are assessed, showing that the concepts answer different user segments’ needs.
Topics
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