Literature DB >> 17240726

Identification of real-time diagnostic measures of visual distraction with an automatic eye-tracking system.

Harry Zhang1, Matthew R H Smith, Gerald J Witt.   

Abstract

OBJECTIVE: This study was conducted to identify eye glance measures that are diagnostic of visual distraction.
BACKGROUND: Visual distraction degrades performance, but real-time diagnostic measures have not been identified.
METHOD: In a driving simulator, 14 participants responded to a lead vehicle braking at -2 or -2.7 m/s2 periodically while reading a varying number of words (6-15 words every 13 s) on peripheral displays (with diagonal eccentricities of 24 degrees, 43 degrees, and 75 degrees).
RESULTS: As the number of words and display eccentricity increased, total glance duration and reaction time increased and driving performance suffered.
CONCLUSION: Correlation coefficients between several glance measures and reaction time or performance variables were reliably high, indicating that these glance measures are diagnostic of visual distraction. It is predicted that for every 25% increase in total glance duration, reaction time is increased by 0.39 s and standard deviation of lane position is increased by 0.06 m. APPLICATION: Potential applications of this research include assessing visual distraction in real time, delivering advisories to distracted drivers to reorient their attention to driving, and using distraction information to adapt forward collision and lane departure warning systems to enhance system effectiveness.

Entities:  

Mesh:

Year:  2006        PMID: 17240726     DOI: 10.1518/001872006779166307

Source DB:  PubMed          Journal:  Hum Factors        ISSN: 0018-7208            Impact factor:   2.888


  4 in total

1.  Predicting visual distraction using driving performance data.

Authors:  Katja Kircher; Christer Ahlstrom
Journal:  Ann Adv Automot Med       Date:  2010

2.  Repeated visual distracter exposure enhances new discrimination learning and sustained attention task performance in rats.

Authors:  Adam H Hirsh; Joshua A Burk
Journal:  Behav Processes       Date:  2012-11-19       Impact factor: 1.777

3.  Eye tracking use in researching driver distraction: A scientometric and qualitative literature review approach.

Authors:  Tina Cvahte Ojstersek; Darja Topolsek
Journal:  J Eye Mov Res       Date:  2019-09-30       Impact factor: 0.957

4.  Searching for Street Parking: Effects on Driver Vehicle Control, Workload, Physiology, and Glances.

Authors:  Canmanie Teresa Ponnambalam; Birsen Donmez
Journal:  Front Psychol       Date:  2020-10-20
  4 in total

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