Investigative Ophthalmology & Visual Science Cover Image for Volume 61, Issue 7
June 2020
Volume 61, Issue 7
Free
ARVO Annual Meeting Abstract  |   June 2020
Gaze scanning behavior predicts hazard detection safety at intersections
Author Affiliations & Notes
  • Alex R Bowers
    Schepens Eye Research Institute of Mass Eye and Ear, Boston, Massachusetts, United States
    Department of Ophthalmology, Harvard Medical School, Massachusetts, United States
  • Lily Zhang
    Schepens Eye Research Institute of Mass Eye and Ear, Boston, Massachusetts, United States
    Department of Ophthalmology, Harvard Medical School, Massachusetts, United States
  • Garrett Swan
    Schepens Eye Research Institute of Mass Eye and Ear, Boston, Massachusetts, United States
    Department of Ophthalmology, Harvard Medical School, Massachusetts, United States
  • Steven William Savage
    Schepens Eye Research Institute of Mass Eye and Ear, Boston, Massachusetts, United States
    Department of Ophthalmology, Harvard Medical School, Massachusetts, United States
  • Footnotes
    Commercial Relationships   Alex Bowers, None; Lily Zhang, None; Garrett Swan, None; Steven Savage, None
  • Footnotes
    Support  NIH grants R01-EY025677, S10-RR028122, and P30-EY003790
Investigative Ophthalmology & Visual Science June 2020, Vol.61, 3510. doi:
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      Alex R Bowers, Lily Zhang, Garrett Swan, Steven William Savage; Gaze scanning behavior predicts hazard detection safety at intersections. Invest. Ophthalmol. Vis. Sci. 2020;61(7):3510.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Purpose : Older drivers are more likely to have at-fault crashes at intersections than experienced younger drivers. Insufficient scanning has been suggested as one reason for this increased crash risk. However, there is little direct evidence of whether scanning behaviors are indeed predictive of hazard detection safety. Using the safe environment of a driving simulator, we evaluated the relationship between scanning behaviors and hazard detection in experienced younger and older drivers.

Methods : Eleven older (mean 67 years, range 61-81) and 18 younger (mean 27 years, range 20-41) current drivers with normal vision, drove in our simulator while both their eye and head movements were tracked using a six-camera remote system. They completed 2 drives in a city, each about 15 minutes with 42 intersections. Moving motorcycle (MC) hazards were programmed at 10 four-way intersections with 7 additional MCs along other parts of the route. Subjects pressed the horn when they detected a MC. Detection safety was based on the speed and distance of both vehicles to the potential collision zone at the time of the horn press.

Results : Older drivers missed more MCs than younger drivers (11 % vs 5 %, p = 0.009). When MCs were detected, older drivers had longer reaction times (mean 1.8 vs 1.5 s, p = 0.04), but were not less safe than younger drivers (83% vs. 83%), because they drove more slowly. When detections were safe, both older and younger drivers made larger (safe 29.4° vs. unsafe 19.0°, p = 0.005) and more numerous gaze scans per intersection (safe 9.4 vs. unsafe 6.2 scans, p < 0.001). Older drivers made more scans than younger drivers when their detections were safe but fewer scans when unsafe (interaction p = 0.004). Large gaze scans incorporating a substantial head movement were more predictive of detection safety than smaller gaze scans comprising only eye movements.

Conclusions : For both younger and older drivers, more gaze scans and larger gaze scans were important for safe detection of hazards. However, older drivers failed to detect more hazards than younger drivers. When a motorcycle was detected, older drivers were slower to respond but were not less safe as they drove more slowly. Our findings underscore the importance of large gaze scans with a substantial head movement in safe detection of hazards on approach to intersections.

This is a 2020 ARVO Annual Meeting abstract.

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