Augmented reality cues to assist older drivers with gap estimation for left-turns

Michelle L. Rusch, Mark C. Schall, John D. Lee, Jeffrey D. Dawson, Matthew Rizzo

Research output: Contribution to journalArticle

19 Citations (Scopus)

Abstract

The objective of this study was to assess the effects of augmented reality (AR) cues designed to assist middle-aged and older drivers with a range of UFOV impairments, judging when to make left-turns across oncoming traffic. Previous studies have shown that AR cues can help middle-aged and older drivers respond to potential roadside hazards by increasing hazard detection without interfering with other driving tasks. Intersections pose a critical challenge for cognitively impaired drivers, prone to misjudge time-to-contact with oncoming traffic. We investigated whether AR cues improve or interfere with hazard perception in left-turns across oncoming traffic for drivers with age-related cognitive decline. Sixty-four middle-aged and older drivers with a range of UFOV impairment judged when it would be safe to turn left across oncoming traffic approaching the driver from the opposite direction in a rural stop-sign controlled intersection scenario implemented in a static base driving simulator. Outcome measures used to evaluate the effectiveness of AR cueing included: Time-to-Contact (TTC), Gap Time Variation (GTV), Response Rate, and Gap Response Variation (GRV). All drivers estimated TTCs were shorter in cued than in uncued conditions. In addition, drivers responded more often in cued conditions than in uncued conditions and GRV decreased for all drivers in scenarios that contained AR cues. For both TTC and response rate, drivers also appeared to adjust their behavior to be consistent with the cues, especially drivers with the poorest UFOV scores (matching their behavior to be close to middle-aged drivers). Driver ratings indicated that cueing was not considered to be distracting. Further, various conditions of reliability (e.g., 15% miss rate) did not appear to affect performance or driver ratings.

Original languageEnglish (US)
Pages (from-to)210-221
Number of pages12
JournalAccident Analysis and Prevention
Volume71
DOIs
StatePublished - Jan 1 2014
Externally publishedYes

Fingerprint

Augmented reality
Cues
driver
Hazards
Roadsides
traffic
contact
Simulators
Outcome Assessment (Health Care)
rating
scenario

Keywords

  • Aging
  • Augmented reality
  • Displays
  • Driver behavior
  • Left-turns
  • UFOV

ASJC Scopus subject areas

  • Human Factors and Ergonomics
  • Safety, Risk, Reliability and Quality
  • Public Health, Environmental and Occupational Health
  • Law

Cite this

Augmented reality cues to assist older drivers with gap estimation for left-turns. / Rusch, Michelle L.; Schall, Mark C.; Lee, John D.; Dawson, Jeffrey D.; Rizzo, Matthew.

In: Accident Analysis and Prevention, Vol. 71, 01.01.2014, p. 210-221.

Research output: Contribution to journalArticle

Rusch, Michelle L. ; Schall, Mark C. ; Lee, John D. ; Dawson, Jeffrey D. ; Rizzo, Matthew. / Augmented reality cues to assist older drivers with gap estimation for left-turns. In: Accident Analysis and Prevention. 2014 ; Vol. 71. pp. 210-221.
@article{aee0d443182a4c23a0422ddb769b7d9a,
title = "Augmented reality cues to assist older drivers with gap estimation for left-turns",
abstract = "The objective of this study was to assess the effects of augmented reality (AR) cues designed to assist middle-aged and older drivers with a range of UFOV impairments, judging when to make left-turns across oncoming traffic. Previous studies have shown that AR cues can help middle-aged and older drivers respond to potential roadside hazards by increasing hazard detection without interfering with other driving tasks. Intersections pose a critical challenge for cognitively impaired drivers, prone to misjudge time-to-contact with oncoming traffic. We investigated whether AR cues improve or interfere with hazard perception in left-turns across oncoming traffic for drivers with age-related cognitive decline. Sixty-four middle-aged and older drivers with a range of UFOV impairment judged when it would be safe to turn left across oncoming traffic approaching the driver from the opposite direction in a rural stop-sign controlled intersection scenario implemented in a static base driving simulator. Outcome measures used to evaluate the effectiveness of AR cueing included: Time-to-Contact (TTC), Gap Time Variation (GTV), Response Rate, and Gap Response Variation (GRV). All drivers estimated TTCs were shorter in cued than in uncued conditions. In addition, drivers responded more often in cued conditions than in uncued conditions and GRV decreased for all drivers in scenarios that contained AR cues. For both TTC and response rate, drivers also appeared to adjust their behavior to be consistent with the cues, especially drivers with the poorest UFOV scores (matching their behavior to be close to middle-aged drivers). Driver ratings indicated that cueing was not considered to be distracting. Further, various conditions of reliability (e.g., 15{\%} miss rate) did not appear to affect performance or driver ratings.",
keywords = "Aging, Augmented reality, Displays, Driver behavior, Left-turns, UFOV",
author = "Rusch, {Michelle L.} and Schall, {Mark C.} and Lee, {John D.} and Dawson, {Jeffrey D.} and Matthew Rizzo",
year = "2014",
month = "1",
day = "1",
doi = "10.1016/j.aap.2014.05.020",
language = "English (US)",
volume = "71",
pages = "210--221",
journal = "Accident Analysis and Prevention",
issn = "0001-4575",
publisher = "Elsevier Limited",

}

TY - JOUR

T1 - Augmented reality cues to assist older drivers with gap estimation for left-turns

AU - Rusch, Michelle L.

AU - Schall, Mark C.

AU - Lee, John D.

AU - Dawson, Jeffrey D.

AU - Rizzo, Matthew

PY - 2014/1/1

Y1 - 2014/1/1

N2 - The objective of this study was to assess the effects of augmented reality (AR) cues designed to assist middle-aged and older drivers with a range of UFOV impairments, judging when to make left-turns across oncoming traffic. Previous studies have shown that AR cues can help middle-aged and older drivers respond to potential roadside hazards by increasing hazard detection without interfering with other driving tasks. Intersections pose a critical challenge for cognitively impaired drivers, prone to misjudge time-to-contact with oncoming traffic. We investigated whether AR cues improve or interfere with hazard perception in left-turns across oncoming traffic for drivers with age-related cognitive decline. Sixty-four middle-aged and older drivers with a range of UFOV impairment judged when it would be safe to turn left across oncoming traffic approaching the driver from the opposite direction in a rural stop-sign controlled intersection scenario implemented in a static base driving simulator. Outcome measures used to evaluate the effectiveness of AR cueing included: Time-to-Contact (TTC), Gap Time Variation (GTV), Response Rate, and Gap Response Variation (GRV). All drivers estimated TTCs were shorter in cued than in uncued conditions. In addition, drivers responded more often in cued conditions than in uncued conditions and GRV decreased for all drivers in scenarios that contained AR cues. For both TTC and response rate, drivers also appeared to adjust their behavior to be consistent with the cues, especially drivers with the poorest UFOV scores (matching their behavior to be close to middle-aged drivers). Driver ratings indicated that cueing was not considered to be distracting. Further, various conditions of reliability (e.g., 15% miss rate) did not appear to affect performance or driver ratings.

AB - The objective of this study was to assess the effects of augmented reality (AR) cues designed to assist middle-aged and older drivers with a range of UFOV impairments, judging when to make left-turns across oncoming traffic. Previous studies have shown that AR cues can help middle-aged and older drivers respond to potential roadside hazards by increasing hazard detection without interfering with other driving tasks. Intersections pose a critical challenge for cognitively impaired drivers, prone to misjudge time-to-contact with oncoming traffic. We investigated whether AR cues improve or interfere with hazard perception in left-turns across oncoming traffic for drivers with age-related cognitive decline. Sixty-four middle-aged and older drivers with a range of UFOV impairment judged when it would be safe to turn left across oncoming traffic approaching the driver from the opposite direction in a rural stop-sign controlled intersection scenario implemented in a static base driving simulator. Outcome measures used to evaluate the effectiveness of AR cueing included: Time-to-Contact (TTC), Gap Time Variation (GTV), Response Rate, and Gap Response Variation (GRV). All drivers estimated TTCs were shorter in cued than in uncued conditions. In addition, drivers responded more often in cued conditions than in uncued conditions and GRV decreased for all drivers in scenarios that contained AR cues. For both TTC and response rate, drivers also appeared to adjust their behavior to be consistent with the cues, especially drivers with the poorest UFOV scores (matching their behavior to be close to middle-aged drivers). Driver ratings indicated that cueing was not considered to be distracting. Further, various conditions of reliability (e.g., 15% miss rate) did not appear to affect performance or driver ratings.

KW - Aging

KW - Augmented reality

KW - Displays

KW - Driver behavior

KW - Left-turns

KW - UFOV

UR - http://www.scopus.com/inward/record.url?scp=84903169464&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84903169464&partnerID=8YFLogxK

U2 - 10.1016/j.aap.2014.05.020

DO - 10.1016/j.aap.2014.05.020

M3 - Article

VL - 71

SP - 210

EP - 221

JO - Accident Analysis and Prevention

JF - Accident Analysis and Prevention

SN - 0001-4575

ER -