Acceptance of automated road transport logistics systems
(All Weather Autonomous Real logistics operations and Demonstrations)
Welcome to the second AWARD Acceptance Factors Survey exploring potential benefits, concerns, and other considerations regarding automated road transport logistics systems!
The EU-2020 AWARD project (https://award-h2020.eu/) aims to develop systems for “All Weather Autonomous Real logistics operations and Demonstrations". The goal of this survey is to understand and gain detailed insights into the different factors that determine the acceptance of such systems. We are interested in the needs and concerns of all affected stakeholders (people interacting directly or indirectly with an automated vehicle, people involved in related processes, and other, more general stakeholder groups).
Please take 10-15 min to support the development of well designed future automated road transport logistics systems!
You can find the "Next" button at the bottom of the page.
AWARD faces four automated logistics use cases at different sites including diverse stakeholders and users. Subsequently, the four use cases are sketched. See the next page for a detailed description.
Highly automated Hub-to-Hub shuttle service from warehouse/production site to a logistics hubs.
Highly automated airside baggage transportation
Highly automated loading and transportation with automated forklift.
Highly automated trailer transfer operations and boat loading
This survey is conducted by AIT Austrian Institute of Technology GmbH. If you have any questions please contact firstname.lastname@example.org.
By participating in this survey, you agree to the storage of the data you provide by AIT Austrian Institute of Technology GmbH. The data entered will be stored and processed for scientific purposes in accordance with current data protection regulations. Further information on data protection at AIT Austrian Institute of Technology GmbH can be found at https://www.ait.ac.at/en/disclaimer-data-protection/.
||This project has received funding from the European Union’s Horizon 2020 research and innovation program under Grant Agreement No. 101006817. The content of this presentation reflects only the author’s view. Neither the European Commission nor the INEA are responsible for any use that may be made of the information it contains.