9,653 research outputs found
Too sick to drive : how motion sickness severity impacts human performance
There are multiple concerns surrounding the development and rollout of self-driving cars. One issue has largely gone unnoticed - the adverse effects of motion sickness as induced by self-driving cars. The literature suggests conditionally, highly and fully autonomous vehicles will increase the onset likelihood and severity of motion sickness. Previous research has shown motion sickness can have a significant negative impact on human performance. This paper uses a simulator study design with 51 participants to assess if the scale of motion sickness is a predictor of human performance degradation. This paper finds little proof that subjective motion sickness severity is an effective indicator of the scale of human performance degradation. The performance change of participants with lower subjective motion sickness is mostly statistically indistinguishable from those with higher subjective sickness. Conclusively, those with even acute motion sickness may be just as affected as those with higher sickness, considering human performance. Building on these results, it could indicate motion sickness should be a consideration for understanding user ability to regain control of a self-driving vehicle, even if not feeling subjectively unwell. Effectiveness of subjective scoring is discussed and future research is proposed to help ensure the successful rollout of self-driving vehicles
Towards Design Principles for Experimental Simulations in Virtual Reality – Learning from Driving Simulators
Experiments play an important role in Information Systems research. In this area, Virtual Reality (VR) technologies can serve as a tool for enabling and conducting research. e.g., to investigate human behavior in specific situations. A prime example is VR-supported driving simulators that allow researchers in the automotive domain to gather knowledge while reducing cost and complexity compared to field studies with real cars. We argue that the use of carefully designed VR-supported experiments might allow researchers to get deeper insights into human behavior. Thus, we derive design principles for VR Experiments as an artifact from the literature about VR-supported driving simulations that have been accepted as a useful tool for research in their domain
Remote Monitoring and Teleoperation of Autonomous Vehicles Is Virtual Reality an Option?
While the promise of autonomous vehicles has led to significant scientific
and industrial progress, fully automated, SAE level 5 conform cars will likely
not see mass adoption anytime soon. Instead, in many applications, human
supervision, such as remote monitoring and teleoperation, will be required for
the foreseeable future. While Virtual Reality (VR) has been proposed as one
potential interface for teleoperation, its benefits and drawbacks over physical
monitoring and teleoperation solutions have not been thoroughly investigated.
To this end, we contribute three user studies, comparing and quantifying the
performance of and subjective feedback for a VR-based system with an existing
monitoring and teleoperation system, which is in industrial use today. Through
these three user studies, we contribute to a better understanding of future
virtual monitoring and teleoperation solutions for autonomous vehicles. The
results of our first user study (n=16) indicate that a VR interface replicating
the physical interface does not outperform the physical interface. It also
quantifies the negative effects that combined monitoring and teleoperating
tasks have on users irrespective of the interface being used. The results of
the second user study (n=24) indicate that the perceptual and ergonomic issues
caused by VR outweigh its benefits, like better concentration through
isolation. The third follow-up user study (n=24) specifically targeted the
perceptual and ergonomic issues of VR; the subjective feedback of this study
indicates that newer-generation VR headsets have the potential to catch up with
the current physical displays
From Manual Driving to Automated Driving: A Review of 10 Years of AutoUI
This paper gives an overview of the ten-year devel- opment of the papers presented at the International ACM Conference on Automotive User Interfaces and Interactive Vehicular Applications (AutoUI) from 2009 to 2018. We categorize the topics into two main groups, namely, manual driving-related research and automated driving-related re- search. Within manual driving, we mainly focus on studies on user interfaces (UIs), driver states, augmented reality and head-up displays, and methodology; Within automated driv- ing, we discuss topics, such as takeover, acceptance and trust, interacting with road users, UIs, and methodology. We also discuss the main challenges and future directions for AutoUI and offer a roadmap for the research in this area.https://deepblue.lib.umich.edu/bitstream/2027.42/153959/1/From Manual Driving to Automated Driving: A Review of 10 Years of AutoUI.pdfDescription of From Manual Driving to Automated Driving: A Review of 10 Years of AutoUI.pdf : Main articl
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