Paper Info
Title
Toward Immersive Self-Driving Simulations: Reports from a User Study across Six Platforms
Abstract
As self-driving car technology matures, autonomous vehicle research is moving toward building more human-centric interfaces and accountable experiences. Driving simulators avoid many ethical and regulatory concerns about self-driving cars and play a key role in testing new interfaces or autonomous driving scenarios. However, apart from validity studies for manual driving simulation, the capabilities of driving simulators in replicating the experience of self-driving cars have not been widely investigated. In this paper, we build six self-driving simulation platforms with varying levels of visual and motion fidelities ranging from a screen-based in-lab simulator to the mixed-reality on-road simulator we propose. We compare the sense of presence and simulator sickness for each simulator composition, as well as its visual and motion fidelities with a user study. Our novel mixed-reality automotive driving simulator, named MAXIM, showed highest fidelity and presence. Our findings suggest how visual and motion configurations affect experience in autonomous driving simulators.
Year
DOI
Venue
2020
10.1145/3313831.3376787
CHI '20: CHI Conference on Human Factors in Computing Systems Honolulu HI USA April, 2020
DocType
ISBN
Citations 
Conference
978-1-4503-6708-0
0
PageRank 
References 
Authors
0.34
0
3
Name
Order
Citations
PageRank
Dohyeon Yeo100.34
Gwangbin Kim200.34
Seung-Jun Kim3100362.52