Qidan Yan
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Research Interests
Qidan Yan has a total of 4 co-authors. Here are the top co-authors by number of shared publications:
- Ali Askari
Inclusive Human-Robot Interaction, TU Dortmund University, Dortmund, Germany
1 shared publication - Hauke Sandhaus
Cornell University, Ithaca, New York, USA
1 shared publication - Ina Koniakowsky
BMW Group, Germany
1 shared publication - Tamara von Sawitzky
Human-Computer Interaction Group, Technische Hochschule Ingolstadt, Germany and Johannes Kepler University Linz, Austria
1 shared publication
Latest Publications
- Open Access
- 18 September 2023
- Published by Association for Computing Machinery (ACM)
- p. 340-341
Exploring Interactions for Collaborative Driving in Fully Automated Vehicles
In a fully automated vehicle (SAE L5), the vehicle performs lateral and longitudinal vehicle controls entirely. The former driver no longer has to intervene in the driving process, monitor it, or respond to take-over requests. At this automation level, vehicle occupants can focus exclusively on non-driving-related tasks. However, passengers might still want to influence driving behavior by choosing a different route or altering travel speed. Therefore, collaborative driving could be a viable option. However, it needs to be clarified how to realize those interactions with the vehicle best, as previous input modalities such as steering wheel and pedals could be left out in the future. In a prototyping workshop, we explored different interactions for collaborative driving with automated vehicles. We propose two interaction concepts in the accompanying video: 1) a mobile button with a turn and slide function and 2) by shifting weight in the seat to convey the desired intentions.
- 18 September 2023
- Published by Association for Computing Machinery (ACM)
- p. 340-341
Open AccessExploring Interactions for Collaborative Driving in Fully Automated Vehicles
In a fully automated vehicle (SAE L5), the vehicle performs lateral and longitudinal vehicle controls entirely. The former driver no longer has to intervene in the driving process, monitor it, or respond to take-over requests. At this automation level, vehicle occupants can focus exclusively on non-driving-related tasks. However, passengers might still want to influence driving behavior by choosing a different route or altering travel speed. Therefore, collaborative driving could be a viable option. However, it needs to be clarified how to realize those interactions with the vehicle best, as previous input modalities such as steering wheel and pedals could be left out in the future. In a prototyping workshop, we explored different interactions for collaborative driving with automated vehicles. We propose two interaction concepts in the accompanying video: 1) a mobile button with a turn and slide function and 2) by shifting weight in the seat to convey the desired intentions.