| 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
article
SUPPORTING DOOR-TO-DOOR AIR TRAVEL: TOWARDS A PRIVACY PRESERVING VIRTUAL ASSISTANT FOR PASSENGERS
Abstract
<jats:p>Seamless and personalised door-to-door air transport, supported by virtual assistants, has the potential to make air travel more convenient and profitable. However, processing passengers’ data comes with major privacy concerns. Commercial interests and functionalities need to be reconciled with data protection. Current concepts do not meet these requirements. Filling this gap, this paper conceptualises an architecture for a travel assistant that mediates between mobility and air transport providers as well as passengers while assuring privacy through local computation. The concept targets a time horizon of 10+ years and addresses steady growth of air passenger volume (post-Covid) with a technical solution that includes an open, modular platform. The proposed architecture can support business advantages like network effects, the improvement of passengers’ overall travel experience, and a new approach that ensures traveller’s privacy online. Further research and the development of a prototype are necessary for first simulations and implications.</jats:p>
Topics
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