We aimed to develop and test a new dynamic measure of transient changes to the useful field of view (UFOV), utilizing a gaze-contingent paradigm for use in realistic simulated environments.
Background:
The UFOV, the area from which an observer can extract visual information during a single fixation, has been correlated with driving performance and crash risk. However, some existing measures of the UFOV cannot be used dynamically in realistic simulators, and other UFOV measures involve constant stimuli at fixed locations. We propose a gaze-contingent UFOV measure (the GC-UFOV) that solves the above problems.
Methods:
Twenty-five participants completed four simulated drives while they concurrently performed an occasional gaze-contingent Gabor orientation discrimination task. Gabors appeared randomly at one of three retinal eccentricities (5°, 10°, or 15°). Cognitive workload was manipulated both with a concurrent auditory working memory task and with driving task difficulty (via presence/absence of lateral wind).
Results:
Cognitive workload had a detrimental effect on Gabor discrimination accuracy at all three retinal eccentricities. Interestingly, this accuracy cost was equivalent across eccentricities, consistent with previous findings of “general interference” rather than “tunnel vision.”
Conclusion:
The results showed that the GC-UFOV method was able to measure transient changes in UFOV due to cognitive load in a realistic simulated environment.
Application:
The GC-UFOV paradigm developed and tested in this study is a novel and effective tool for studying transient changes in the UFOV due to cognitive load in the context of complex real-world tasks such as simulated driving.
AndersenG. J.NiR. (2005). The spatial extent of attention during driving. Proceedings of the Third International Driving Symposium on Human Factors in Driver Assessment, Training, and Vehicle Design (pp. 403–408). Iowa City, Iowa: University of Iowa.
2.
AtchleyP.ChanM. (2011). Potential benefits and costs of concurrent task engagement to maintain vigilance: A driving simulator investigation. Human Factors, 53, 3–12.
3.
AtchleyP.DresselJ. (2004). Conversation limits the functional field of view. Human Factors, 46(4), 664–673.
4.
BallK. K.BeardB. L.RoenkerD. L.MillerR. L.GriggsD. S. (1988). Age and visual search: Expanding the useful field of view. Journal of the Optical Society of America, 5(12), 2210–2219.
5.
BallK. K.EdwardsJ. D.RossL. A.McGwinG.Jr. (2010). Cognitive training decreases motor vehicle collision involvement of older drivers. Journal of the American Geriatrics Society, 58(11), 2107–2113.
6.
BallK. K.OwsleyC.BeardB. (1990). Clinical visual perimetry underestimates peripheral field problems in older adults. Clinical Vision Sciences, 5(2), 113–125.
7.
BallK. K.RoenkerD. L.WadleyV. G.EdwardsJ. D.RothD. L.McGwinG.… DubeT. (2006). Can high-risk older drivers be identified through performance-based measures in a department of motor vehicles setting?Journal of the American Geriatrics Society, 54(1), 77–84. doi: 10.1111/j.1532-5415.2005.00568.x
BianZ.KangJ.AndersenG. (2010). Changes in extent of spatial attention with increased workload in dual-task driving. Transportation Research Record: Journal of the Transportation Research Board, 2185(-1), 8–14. doi: 10.3141/2185-02
10.
CarrascoM. (2011). Visual attention: The past 25 years. Vision Research, 51(13), 1484–1525. doi: 10.1016/j.visres.2011.04.012
11.
ChanH.CourtneyA. J. (1998). Stimulus size scaling and foveal load as determinants of peripheral target detection. Ergonomics, 41(10), 1433–1452.
12.
ClayO.WadleyV.EdwardsJ.RothD.RoenkerD. L.BallK. K. (2005). Cumulative meta-analysis of the relationship between useful field of view and driving performance in older adults: Current and future implications. Optometry and Vision Science, 82(8), 724–731.
13.
CorreaÁ.LupianezJ.MillikenB.TudelaP. (2004). Endogenous temporal orienting of attention in detection and discrimination tasks. Perception & Psychophysics, 66(2), 264–278. doi: 10.3758/bf03194878
14.
CrundallD. E.UnderwoodG.ChapmanP. R. (1999). Driving experience and the functional field of view. Perception, 28, 1075–1087.
15.
CrundallD. E.UnderwoodG.ChapmanP. R. (2002). Attending to the peripheral world while driving. Applied Cognitive Psychology, 16(4), 459–475.
GildmanE.UnderwoodG. (2003). Restricting the field of view to investigate the perceptual spans of pianists. Visual Cognition, 10, 201–232.
18.
GreeneH. H.SimpsonD.BennionJ. (2012). The perceptual span during foveally-demanding visual target localization. Acta Psychologica, 139(3), 434–439. doi: http://dx.doi.org/10.1016/j.actpsy.2011.12.015
19.
HeJ.McCarleyJ. S. (2011). Effects of cognitive distraction on lane-keeping: Performance loss or improvement?Proceedings of the Human Factors and Ergonomics Society 55th Annual Meeting (pp. 1894–1898). Santa Monica, CA: Human Factors and Ergonomics Society.
20.
HorreyW. J.WickensC. D.ConsalusK. P. (2006). Modeling drivers’ visual attention allocation while interacting with in-vehicle technologies. Journal of Experimental Psychology: Applied, 12(2), 67.
21.
IkedaM.TakeuchiT. (1975). Influence of foveal load on the functional visual field. Perception & Psychophysics, 18, 255–260.
22.
JahnG.OehmeA.KremsJ. F.GelauC. (2005). Peripheral detection as a workload measure in driving: Effects of traffic complexity and route guidance system use in a driving study. Transportation Research. Part E, Logistics and Transportation Review, 8(3), 255–275.
23.
KirchnerW. K. (1958). Age differences in short-term retention of rapidly changing information. Journal of Experimental Psychology, 55(4), 352–358.
24.
KontsevichL. L.TylerC. W. (1999). Bayesian adaptive estimation of psychometric slope and threshold. Vision Research, 39(16), 2729–2737.
25.
KowlerE.AndersonE.DosherB.BlaserE. (1995). The role of attention in the programming of saccades. Vision Research, 35(13), 1897–1916.
26.
LiangY.LeeJ. D. (2010). Combining cognitive and visual distraction: Less than the sum of its parts. Accident Analysis & Prevention, 42(3), 881–890.
27.
LoschkyL. C.McConkieG. W. (2002). Investigating spatial vision and dynamic attentional selection using a gaze-contingent multi-resolutional display. Journal of Experimental Psychology: Applied, 8(2), 99–117.
McConkieG. W.RaynerK. (1975). The span of the effective stimulus during a fixation in reading. Perception & Psychophysics, 17(6), 578–586. doi: 10.3758/bf03203972
30.
McConkieG. W.RaynerK. (1976). Identifying the span of the effective stimulus in reading: Literature review and theories of reading. In SingerH.RuddellR. B. (Eds.), Theoretical models and processes of reading (pp. 137–162). Newark, DE: International Reading Association.
31.
Medeiros-WardN.CooperJ. M.StrayerD. L. (2014). Hierarchical control and driving. Journal of Experimental Psychology: General, 143(3), 953–958.
32.
MitchellJ. P.MacraeC. N.GilchristI. D. (2002). Working memory and the suppression of reflexive saccades. Journal of Cognitive Neuroscience, 14(1), 95–103. doi: 10.1162/089892902317205357
33.
MiuraT. (1986). Coping with situational demands: A study of eye movements and peripheral vision performance. In GaleA. G. (Ed.), Vision in vehicles (pp. 205–221). Amsterdam: Elsevier Science Publishers B.V.
34.
MotterB. C.SimoniD. A. (2008). Changes in the functional visual field during search with and without eye movements. Vision Research, 48(22), 2382–2393. doi: http://dx.doi.org/10.1016/j.visres.2008.07.020
35.
NuthmannA. (2014). How do the regions of the visual field contribute to object search in real-world scenes? Evidence from eye movements. Journal of Experimental Psychology: Human Perception and Performance, 40(1), 342–360. doi: 10.1037/a0033854
36.
OwsleyC.WoodJ. M.McGwinG. (2015). A roadmap for interpreting the literature on vision and driving. Survey of Ophthalmology, 60(3), 250–262.
37.
ParkG. D.ReedC. L. (2010). Distribution of peripheral vision for a driving simulator functional field of view task. Proceedings of the Human Factors and Ergonomics Society 54th Annual Meeting (pp. 1526–1530). Santa Monica, CA: Human Factors and Ergonomics Society.
38.
PlainisS.MurrayI. J.ChauhanK. (2001). Raised visual detection thresholds depend on the level of complexity of cognitive foveal loading. Perception, 30(10), 1203–1212.
39.
PringleH. L.IrwinD. E.KramerA. F.AtchleyP. (2001). The role of attentional breadth in perceptual change detection. Psychonomic Bulletin & Review, 8(1), 89–95.
40.
PringleH. L.KramerA. F.IrwinD. E. (2004). Individual differences in the visual representation of scenes. In LevinD. T. (Ed.), Thinking and seeing: Visual metacognition in adults and children (pp. 165–185). Boston, MA: MIT Press.
41.
RantanenE. M.GoldbergJ. H. (1999). The effect of mental workload on the visual field size and shape. Ergonomics, 42(6), 816–834.
42.
RaynerK. (1975). The perceptual span and peripheral cues in reading. Cognitive Psychology, 7(1), 65–81.
43.
RaynerK. (1998). Eye movements in reading and information processing: 20 years of research. Psychological Bulletin, 124, 372–422.
44.
RaynerK.SmithT. J.MalcolmG. L.HendersonJ. M. (2009). Eye movements and visual encoding during scene perception. Psychological Science, 20(1), 6–10. doi: 10.1111/j.1467-9280.2008.02243.x
45.
RecarteM. A.NunesL. M. (2003). Mental workload while driving: Effects on visual search, discrimination, and decision making. Journal of Experimental Psychology-Applied, 9(2), 119–137. doi: 10.1037/1076-898x.9.2.119
46.
ReimerB. (2009). Impact of cognitive task complexity on drivers’ visual tunneling. Transportation Research Record: Journal of the Transportation Research Board, 2138(1), 13–19.
47.
ReimerB.MehlerB.WangY.CoughlinJ. F. (2012). A field study on the impact of variations in short-term memory demands on drivers’ visual attention and driving performance across three age groups. Human Factors, 54, 454–468. doi: 10.1177/0018720812437274
48.
ReingoldE. M.LoschkyL. C.McConkieG. W.StampeD. M. (2003). Gaze-contingent multi-resolutional displays: An integrative review [review]. Human Factors, 45, 307–328.
49.
RingerR. V.JohnsonA. P.GasparJ. G.NeiderM. B.CrowellJ.KramerA. F.LoschkyL. C. (2014). Creating a new dynamic measure of the useful field of view using gaze-contingent displays. Proceedings of the Symposium on Eye Tracking Research and Applications (pp. 59–66). New York, NY: ACM.
50.
RingerR. V.ThroneburgZ.JohnsonA. P.KramerA. F.LoschkyL. C. (2016). Impairing the Useful Field of View in natural scenes: Tunnel vision versus general interference. Journal of Vision, 16(2), 1–25. doi:10.1167/16.2.7 .
51.
RoenkerD. L.CissellG. M.BallK. K.WadleyV. G.EdwardsJ. D. (2003). Speed-of-processing and driving simulator training result in improved driving performance. Human Factors, 45, 218–233.
52.
SagiD.JuleszB. (1985). Detection versus discrimination of visual orientation. Perception, 14, 619–628.
53.
SekulerA. B.BennettP. J.MamelakM. (2000). Effects of aging on the useful field of view. Experimental Aging Research, 26(2), 103–120.
54.
SeyaY.NakayasuH.YagiT. (2013). Useful field of view in simulated driving: Reaction times and eye movements of drivers. i-Perception, 4(4), 285–298.
55.
SonJ.ParkM.OhH. (2012). Detecting cognitive workload using driving performance and eye movement in a driving simulator. Paper presented at the AVEC12—The 11th International Symposium on Advanced Vehicle Control, Seoul, Korea.
56.
StrasburgerH.RentschlerI.JuttnerM. (2011). Peripheral vision and pattern recognition: A review. Journal of Vision, 11(5), 13. doi: 10.1167/11.5.13
57.
SummalaH.LambleD.LaaksoM. (1998). Driving experience and perception of the lead car’s braking when looking at in-car targets. Accident Analysis & Prevention, 30(4), 401–407. doi: http://dx.doi.org/10.1016/S0001-4575(98)00005-0
58.
SummalaH.NieminenT.PuntoM. (1996). Maintaining lane position with peripheral vision during in-vehicle tasks. Human Factors, 38, 442–451. doi: 10.1518/001872096778701944
59.
van DiepenP. M.WampersM.d’YdewalleG. (1998). Functional division of the visual field: Moving masks and moving windows. In UnderwoodG. et al. (Ed.), Eye guidance in reading and scene perception (pp. 337–355). Oxford, UK: Anonima Romana.
60.
WilliamsL. J. (1985). Tunnel vision induced by a foveal load manipulation. Human Factors, 27, 221–227.
61.
WilliamsL. J. (1988). Tunnel vision or general interference? Cognitive load and attentional bias are both important. American Journal of Psychology, 101, 171–191.
62.
WilliamsL. J. (1989). Foveal load affects the functional field of view. Human Performance, 2, 1–28.
63.
WolfeJ. M.O’NeillP.BennettS. C. (1998). Why are there eccentricity effects in visual search? Visual and attentional hypotheses. Perception & Psychophysics, 60(1), 140–156. doi: 10.3758/bf03211924
Supplementary Material
Please find the following supplemental material available below.
For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.
For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.
