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Influencing Human Escape Maneuvers With Perceptual Cues in the Presence of a Visual Task

Authors :
Anirban Mazumdar
Aaron J. ng
Karen M. Feigh
Aakash Bajpai
Source :
IEEE Transactions on Human-Machine Systems. 51:715-724
Publication Year :
2021
Publisher :
Institute of Electrical and Electronics Engineers (IEEE), 2021.

Abstract

Visual engagement is common in many situations where human operators must perform tasks in challenging environments. This visual engagement has the potential to impact the safety of these operators when dealing with dynamic threats. Perceptual cues have been shown to elicit physical evasion maneuvers, thereby improving safety. In this article, we investigate the effects of cues and visual engagement on rapid whole-body responses. The visual task, inspired by the Trail Making Test (TMT), served as a proxy for visual engagement in the real world. Our continuous TMT minigame and threat simulation are implemented in a virtual reality environment. Participants attempt to maximize their performance score by quickly solving TMTs and dodging dynamic threats from various in-plane directions. They are provided with no cues (control), visual cues, and vibrotactile cues indicating impending threat directions. Participant's ability to dodge threats is quantified by failure rate and reaction time within field of view and for all approach directions. An index of difficulty highlighted perceptual cue response sensitivity to varying threat speeds and sizes. This article provides two core key contributions and other interesting findings: 1) the results illustrate that tactile cues enable statistically significantly better dodging rates than visual cues or with human vision alone (control condition); and 2) that visual engagement degrades human evasion performance in a statistically significant way. Finally, tactile cue responses appear to be less sensitive than visual cues to visually engaging tasks within the higher portion of difficulty index range that is investigated.

Details

ISSN :
21682305 and 21682291
Volume :
51
Database :
OpenAIRE
Journal :
IEEE Transactions on Human-Machine Systems
Accession number :
edsair.doi...........f5064924d802f8250425f5f920f87990
Full Text :
https://doi.org/10.1109/thms.2021.3108962