Toward Immersive Self-Driving Simulations: Reports from a User Study across Six Platforms

要旨

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.

キーワード
Autonomous driving
driving simulator
user studies
Immersive technology
mixed reality
on-road simulation
著者
Dohyeon Yeo
Gwangju Institute of Science and Technology, Gwangju, Republic of Korea
Gwangbin Kim
Gwangju Institute of Science and Technology, Gwangju, Republic of Korea
Seungjun Kim
Gwangju Institute of Science and Technology, Gwangju, Republic of Korea
DOI

10.1145/3313831.3376787

論文URL

https://doi.org/10.1145/3313831.3376787

動画

会議: CHI 2020

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2020.acm.org/)

セッション: Automotive & pedestrian interfaces

Paper session
317AB KAHO'OLAWE
5 件の発表
2020-04-27 23:00:00
2020-04-28 00:15:00
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