Education, Science, Technology, Innovation and Life
Open Access
Sign In

Driver distraction and the role of cognitive and visual abilities for Road Safety Practices

Download as PDF

DOI: 10.23977/aetp.2018.21027 | Downloads: 9 | Views: 137


S. Keffane 1


1 PhD in Psychology, Researcher, Department of Psychology, University Setif 2, Setif, Algeria.

Corresponding Author

S. Keffane


Driver distraction represents a significant problem in a motor vehicle is a complex activity. This study exist for evaluated part of the Multifactorial Model of distraction, Driving Safety to elucidate the relative importance of cognitive function and measures of visual function in the capacity to Drive Safely. This article investigates the nature of driver distraction at a major Algerian a motor vehicle. At present, increasing amounts of visual information from sources such as roadside advertising create visual clutter in the road environment, including the sources of distraction present, and their effects on driver performance, cognitive and visual function (CV) capacity supports goal-directedness which minimizes the influence of distracting stimuli in favor of driving-relevant stimuli. Cognitive and visual function (CV) capacity can be discriminated and are both addressed during driving. This study investigated for driving experience (n= 300, age= 18-25), These included an adaptation of the well validated Useful Field of View (UFOV) and two newer measures, namely a Hazard Perception Test (HPT), and a Hazard Change Detection Task (HCDT).


Driver distraction, Cognitive Vision abilities, Driving experience, Safety driving, Road Safety Practices.


S. Keffane, Driver distraction and the role of cognitive and visual abilities for Road Safety Practices, Advances in Educational Technology and Psychology (2018) 2: 234-251.


[1]Hosking, S.G., Young, K.L., Regan, M.A., 2009. The effects of text messaging on young drivers. Human Factors 51, 581e592.
[2] Regan, M.A., Lee, J.D., Young, K.L., 2008a. Driver Distraction: Theory, Effects and Mitigation. CRC Press, Boca Raton, Florida.
[3] Salmon, P.M., Stanton, N.A., Jenkins, D.P., Walker, G.H., 2010a. Hierarchical Task Analysis Versus Cognitive Work Analysis: Comparison of Theory, Methodology, and Contribution to System Design. Theoretical Issues in Ergonomics Science. Ifirst, 2nd February, pp. 1e28.
[4] Young, K.L., Lenné, M.G., 2010. Driver engagement in distracting activities and the strategies used to minimise risk. Safety Science 48, 326–332.
[5] Klauer, S.G., Dingus, T.A., Neale, V.L., Sudweeks, J.D., Ramsey, D.J., 2006. The Impact of Driver Inattention on Near-crash/crash risk: An Analysis Using the 100-Car Naturalistic Driving Study Data. Virginia Tech Transportation Institute, Blacksburg, Virginia.
[6] Rakauskas, M.E., Gugerty, L.J., Ward, N.J., 2004. Effects of naturalistic cell phone conversations on driving performance. Journal of Safety Research 35 (4), 453–464.
[7] Strayer, D.L., Drews, F.A., 2004. Profiles in driver distraction: effects of cell phone conversations on younger and older drivers. Human Factors 46, 640.
[8] Engström, J., Johansson, E., Ostlund, J., 2005. Effects of visual and cognitive load in real and simulated motorway driving. Transportation Research Part F 8, 97e120.
[9] Reed, M.P., Green, P.A., 1999. Comparison of driving performance on-road and in a low-cost simulator using a concurrent telephone dialling task. Ergonomics 42, 1015e1037.
[10] Kass, S.J., Cole, K.S., Stanny, C.J., 2007. Effects of distraction and experience on situation awareness and simulated driving. Transportation Research Part F: Traffic Psychology and Behaviour 10, 321e329.
[11] Burns, P.C., Parkes, A., Burton, S., Smith, R.K., Burch, D., 2002. How Dangerous is Driving with a Mobile Phone? Benchmarking the Impairment to Alcohol. TRL Limited, Crowthorne, UK.
[12] Lee, J.D., Caven, B., Haake, S., Brown, T.L., 2001. Speech-based interaction with invehicle computers: Tthe effect of speech-based e-mail on drivers’ attention to the roadway. Human Factors 43, 631e 640.
[13] Nunes, L.M., Recarte, M.A., 2002. Cognitive demands of hands-free phone conversation while driving. Transportation Research Part F: Traffic Psychology and Behaviour 5, 133e144.
[14] Anstey, K.J., Wood, J., Lord, S., Walker, J.G., 2005b. Cognitive, sensory and physical factors enabling driving safety in older adults. Clin. Psychol. Rev. 25 (1), 45–65.
[15] Horswill, M.S., Anstey, K.J., Hatherly, C., Wood, J.M., Pachana, N.A., 2011. Older drivers’ insight into their hazard perception ability. Accid. Anal. Prev. 43, 2121–2127.
[16] Okonkwo, O.C., Crowe, M., Wadley, V.G., Ball, K., 2008. Visual attention and selfregulation of driving among older adults. Int. Psychogeriatr. 20 (1), 162–173.
[17] Cole, B.L., 2002. Who’s responsible for safe vision on the roads? Clin. Exp. Optom. 85 (4), 207–209.
[18] Jobe, J.B., Smith, D.M., Ball, K.K., Tennestedt, S.L., Marsiske, M., Willis, S.L., Rebok, G.W., Morris.
[19] Roenker, D.L., Cissell, G.M., Ball, K.K., Wadley, V.G., Edwards, J.D., 2003. Speedof- processing and driving simulator training result in improved driving performance. Hum. Factors 45 (2), 218–233.
[20] Edwards, J.D., Ross, L.A., Wadley, V.G., Clay, O.J., Crowe, M., Roenker, D.L., Ball, K.K., 2006. The useful field of view test: normative data for older adults. Arch. Clin. Neuropsychol. 21 (4), 275–286.
[21] Horswill, M.S., Kemala, C.N., Wetton, M., Scialfa, C.T., Pachana, N.A., 2010b. Improving older drivers’ hazard perception ability. Psychol. Aging 25 (2), 464–469.
[22] Ball, K.K., Owsley, C., 1993. The useful field of view test: a new technique for evaluat-ing age-related declines in visual function. Journal of the American OptometricAssociation 64 (1), 71–79.
[23] Clay, O.J., Wadley, V.G., Edwards, J.D., Roth, D.L., Roenker, D.L., Ball, K.K.,2005. Cumulative meta-analysis of the relationship between usefulfield of view and driving performance in older adults: current andfuture implications. Optometry and Vision Science 82 (8), 724–731.
[24] Mathias, J.L., Lucas, L.K., 2009. Cognitive predictors of unsafe driving in olderdrivers: a meta-analysis. International Psychogeriatrics 21 (4), 637–653.
[25] Gentzler, M.D., Smither, J.A., 2012. A literature review of major perceptual, cognitive,and/or physical test batteries for older drivers. Work 41 (Suppl.1), 5381–5383.
[26] Ball, K.K., Owsley, C., 1993. The useful field of view test: a new technique for evaluat-ing age-related declines in visual function. Journal of the American OptometricAssociation 64 (1), 71–79.
[27] Clay, O. J., Wadley, V., Edwards, J. D., Roth, D., Roenker, D. L., & Ball, K. 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, 724–731.
[28] Gentzler, M.D., Smither, J.A., 2012. A literature review of major perceptual, cognitive,and/or physical test batteries for older drivers. Work 41 (Suppl.1), 5381–5383,
[29] Edwards, J.D., Vance, D.E., Wadley, V.G., Cissell, G.M., Roenker, D.L., Ball, K.K., 2005.Reliability and validity of useful field of view test scores as administered bypersonal computer. Journal of Clinical and Experimental Neuropsychology 27(5), 529–543.
[30] Ball, K.K., Roenker, D.L., Bruni, J.R., 1990. Developmental changesin attention and visual search throughout adulthood. In: Enns,J.T. (Ed.), Advances in Psychology. North-Holland, pp. 489–508.
[31] Ball, K.K., 1997. Attentional problems and older drivers. AlzheimerDisease and Associated Disorders 11 (Suppl. 1), 42–47.
[32] Carrasco, M., 2011. Visual attention: the past 25 years. Vision Research 51 (13),1484–1525.
[33] Lunsman, M., Edwards, J.D., Andel, R., Small, B.J., Ball, K.K., Roenker, D.L., 2008. Whatpredicts changes in useful field of view test performance? Psychology and Aging23 (4), 917–927.
[34] Hoffman, L., Yang, X., Bovaird, J.A., Embretson, S.E., 2006. Measuring atten-tional ability in older adults: development and psychometric evaluation ofDriverscan. Educational and Psychological Measurement 66 (6), 984–1000.
[35] Rensink, R.A., O’Regan, J.K., Clark, J.J., 1997. To see or not to see: the need forattention to perceive changes in scenes. Psychological Science 8 (5), 368–373.
[36] Rensink, R.A., 2002. Change detection. Annual Review of Psychology 53, 245–277.
[37] Anstey, K.J., Wood, J., 2011. Chronological age and age-related cognitive deficits are associated with an increase in multiple types of driving errors in late-life. Neuropsychology, PMID: 21574713.
[38] Horswill, M.S., Marrington, S.A., Mccullough, C.M., Wood, J., Pachana, N.A., Mcwilliam, J., Raikos, M.K., 2008. The hazard perception ability of older drivers. J. Gerontol.: Psychol. Sci. 63B (4), 212–218.
[39] Mckenna, F.P., Horswill, M.S., 1999. Hazard perception and its relevance for driver licensing. J. Int. Assoc. Traffic Saf. Sci. 23, 26–41.
[40] McKenna, F.P., Crick, J.L., 1991. Hazard Perception in Drivers: A Methodology for Testing and Training (Final Report). Transport and Road Research Laboratory, Crowthorne, England.
[41] Simons, D.J., Rensink, R.A., 2005. Change blindness: past, present, and future. Trends Cogn. Sci. 9 (1), 16–20.
[42] Rensink, R.A., 2002. Change detection. Annu. Rev. Psychol. 53, 245–277.
[43] Caird, J.K., Edwards, C.J., Creaser, J.I., Horrey, W.J., 2005. Older driver failures of attention at intersections: using change blindness methods to assess turn decision accuracy. Hum. Factors 47 (2), 235–249.
[44] Pringle, H.L., Irwin, D.E., Kramer, A.F., Atchley, P., 2001. The role of attentional breadth in perceptual change detection. Psychon. Bull. Rev. 8 (1), 89–95.
[45] Wetton, M.A., Horswill, M.S., Hatherly, C., Wood, J.M., Pachana, N.A., Anstey, K.J., 2010. The development and validation of two complementary measures of drivers’ hazard perception ability. Accid. Anal. Prev. 42 (4), 1232–1239.
[46] Consiglio, W., Driscoll, P., Witte, M., Berg, W.P., 2003. Effect of cellular telephone conversations and other potential interference on reaction time in a braking response. Accident Analysis and Prevention 35 (4), 495e500.
[47] Amditis, A., Pagle, K., Joshi, S., Bekiaris, E., 2010. Driver–vehicle–environment monitoring for on-board driver support systems: lessons learned from design and implementation. Applied Ergonomics 41 (2), 225–235.
[48] Lansdown, T.C., Burns, P.C., Parkes, A.M., 2004. Perspectives on occlusion and requirements for validation. Applied Ergonomics 35 (3), 225–232.
[49] Noy, Y.I., Lemoine, T.L., Klachan, C., Burns, P.C., 2004. Task interruptability and duration as measures of visual distraction. Applied Ergonomics 35 (3), 207e213.
[50] Hanowski, R.J., Perez, M.A., Dingus, T.A., 2005. Driver distraction in long-haul truck drivers. Transportation Research Part F: Traffic Psychology and Behaviour 8 (6), 441e458.
[51] Olson, R.L., Hanowski, R.J., Hickman, J.S., Bocanegra, J., 2009. Driver Distraction in Commercial Vehicle Operations. Report no. FMCSA-RRR-09-242. Federal Motor Carrier Safety Administration, Washington, DC.
[52] Chen, W.-H., Lin, T.-W., Su, J.-M., Lee, S.-W., Hwang, S.-L., Hsu, C.-C., Lin, C.-Y., 2006. The effect of using in-vehicle communication system on bus drivers’ performance in car-following tasks. In: 13th World Congress on Intelligent Transport Systems, London, UK.
[53] Stutts, J., Feaganes, J., Reinfurt, D., Rodgman, E., Hamlett, C., Gish, K., Staplin, L., 2005. Drivers’ exposure to distractions in their natural driving environment. Accident Analysis and Prevention 37, 1093e1101.
[54] Senders, J., Kristofferson, A., Levison, W., Dietrich, C., & Ward, J. (1967). The Attentional Demand of Automobile Driving. Highway Research Record, 195, 15-32.
[55] Sheridan, T. B. (2004). Driver distraction from a control theory perspective. Human Factors, 46(4), 587-599.    
[56] Wickens, C. D. (1987). Attention. In P. A. Hancock (Ed.), Human Factors Psychology (pp. 29-70). Amsterdam: Elsevier Science.
[57] Allen, T. M., Lunenfeld, H., & Alexander, G. J. (1971). Driver information needs. Highway Research Record, 366, 102-114. van der Molen, H. H., & Botticher, A. M. T. (1988). A hierarchical risk model for traffic participants. Ergonomics, 31(4), 537-555.
[58] van der Molen, H. H., & Botticher, A. M. T. (1988). A hierarchical risk model for traffic participants. Ergonomics, 31(4), 537-555.
[59] Flach, J. M. (1999). Beyond error: the language of coordination and stability. In P. A. Hancock (Ed.), Human Performance and Ergonomics (pp. 109-128). San Diego: Academic Press.
[60] Rasmussen, J. (1987). Cognitive control and human error mechanisms In J. Rasmussen, K. Duncan & J. Leplat (Eds.), New Technology and Human Error (pp. 53-61). Chicester, UK: John Wiley & Sons.
[61] Ranney, T. A. (1994). Models of driving behavior: A review of their evolution. Accident Analysis & Prevention, 26(6), 733-750.
[62] Reid, G. B., & Nygren, T. E. (1988). The subjective workload assessment technique: a scaling procedure for measuring mental workload. In P. A. Hancock & N. Meshkati (Eds.), Human Mental Workload (pp. 185-218). North-Holland: Elsevier Science Publishers.
[63] de Waard, D. (2002). Mental Workload. In R. Fuller & J. Santos (Eds.), Human factors for highway engineers.
[64] Kantowitz, B. H. (1987). Mental Workload. In P. A. Hancock (Ed.), Human Factors Psychology.
[65] Wickens, C. D. (1993). Engineering Psychology and Human Performance (2 ed.). New York: HarperCollins.
[66] de Waard, D., & Brookhuis, K. (1997). On the measurement of driver workload. In T. Rothengatter & E. Carbonell Vaya (Eds.), Traffic and Transport Psychology (1 ed., pp. 161-171). 
[67] Wright, P. (1974). The harassed decision maker: time pressures, distractions, and the use of evidence. Journal of Applied Psychology, 59(5), 555-561.
[68] Cooper, P. J., & Zheng, Y. (2002). Turning gap acceptance decision-making: the impact of driver distraction. Journal of Safety Research, 33, 321-335.
[69] Lee, P. N. J., & Triggs, T. J. (1976). The effects of driving demand and roadway environment on peripheral visual detections. ARRB Proceedings, 8(Session 25), 7-12.
[70] Martens, M. H., & van Winsum, W. (2000). Measuring distraction: the Peripheral Detection Task. From
[71] Baldwin, C. L., and J. T. Coyne. 2003. “Mental Workload as a Function of Traffic Density: Comparison of Physiological, Behavioral, and Subjective Indices.” In Proceedings of the 2nd International Driving Symposium on Human Factors in Driver Assessment, Training and Vehicle Design, edited by D.V.
[72] Wood, C., Gray, R., Young, J., Summers, J., Torkkola, K., & Massey, N. (2003). Inattentional blindness while driving. Paper presented at the Driving Assessment 2003: Second International Driving Symposium on Human Factors in Driver Assessment, Training, and Vehicle Design. From
[73] Hoyos, C. G. (1988). Mental load and risk in traffic behaviour. Ergonomics, 31(4), 571-584.
[74] Slick, R. F., Cady, E. T., & Tran, T. Q. (2005). Workload changes in teenaged drivers driving with distractions. Paper presented at the Driving Assessment 2005: Third International Driving Symposium on Human Factors in Driver Assessment, Training and Vehicle Design. From
[75] Hancock, P. A., & Warm, J. (1989). A dynamic model of stress and sustained attention. Human Factors, 31(5), 519-537.
[76] Sivak, M. (1996). The information that drivers use: is it indeed 90% visual? Perception, 25, 1081-1089.
[77] Wierda, M. (1996). Beyond the eye: cognitive factors in drivers' visual perception. In A. G. Gale, I. D. Brown, C. M. Haslegrave & S. P. Taylor (Eds.), Vision in Vehicles - V (pp. 97-105). Amsterdam: Elsevier.
[78] Summala, H., Lamble, D., & Laakso, M. (1998). Driving experience and perception of the lead car's braking when looking at in-car targets. Accident Analysis & Prevention, 30(4), 401-407.
[79] Summala, H., Nieminen, T., & Punto, M. (1996). Maintaining lane position with peripheral vision during in-vehicle tasks. Human Factors, 38(3), 442-451.
[80] Broadbent, D. E. (1958). Immediate memory and the shifting of attention. In Perception and communication (pp. 210-243). Elmsford, NY, US.: Pergamon Press.
[81] Findlay, J. M., & Gilchrist, I. D. (2003). Active Vision: The Psychology of Looking and Seeing. New York: Oxford University Press.
[82] Posner, M. I. (1980). Orienting of attention. Quarterly Journal of Experimental Psychology, 32, 3-25.
[83] Theeuwes, J. (1993). Visual selective attention: A theoretical analysis. Acta Psychologica, 83, 93-154.
[84] Theeuwes, J. (1994). Endogenous and exogenous control of visual selection. Perception, 23, 429-440.
[85] Wood, J.M., Anstey, K.J., Kerr, G.K., Lacherez, P.F., Lord, S., 2008. A multidomain approach for predicting older driver safety under in-traffic road conditions. J. Am. Geriatr. Soc. 56 (6), 986–993.
[86] Anstey, K.J., Wood, J., Kerr, G., Caldwell, H., Lord, S.R., 2009. Different cognitive profiles for single compared with recurrent fallers without dementia. Neuropsychology 23 (4), 500–508.
[87] Miyake, A., Friedman, N.P., Emerson, M.J., Witzki, A.H., Howerter, A., Wager, T.D., 2000. The unity and diversity of executive functions and their contributions to complex “Frontal lobe” Tasks: a latent variable analysis. Cogn. Psychol. 41 (1), 49–100.
[88] Salthouse, T.A., 2005. Relations between cognitive abilities and measures of executive functioning. Neuropsychology 19 (4), 532–545.
[89] Staplin, L., Lococo, K., Gish, K.W., Decina, L., 2003b. Model Driver Screening and Evaluation Program Final Technical Report, vol. 2: Maryland Pilot Older Driver Study. National Highway Transport Safety Administration, Washington, DC.
[90] Ball, K.K., Roenker, D.L., Wadley, V.G., Edwards, J.D., Roth, D.L., Mcgwin Jr., G., Raleigh, R., Joyce, J.J., Cissell, G.M., Dube, T., 2006. Can high-risk older drivers be identified through performance-based measures in a department of motor vehicles setting? J. Am. Geriatr. Soc. 54 (1), 77–84.
[91] Folstein, M.F., Folstein, S.E., McHugh, P.R., 1975. ‘Mini mental state’.A practical method for grading the cognitive state of patientsfor the clinician. Journal of Psychiatric Research 12 (3), 189–198.
[92] Molloy, D.W., Standish, T.I.M., 1997. A guide to the standardized Mini-Mental State Examination. International Psychogeriatrics 9 (Suppl. 1), 87–94.
[93] Vertesi, A., Lever, J.A., Molloy, D.W., Sanderson, B., Tuttle, I., Pokoradi, L., Principi,E., 2001. Standardized mini-mental state examination: use and interpretation.Canadian Family Physician 47 (October) 2018–2023.
[94] French, J.W., Ekstrom, R.B., Price, L.A., 1963. Manual for Kit of Reference Tests for Cognitive Factors. Educational Testing Service, Princeton, New Jersey.
[95] Bailey, I.L., Lovie, J.E., 1976. New design principles for visual acuity letter charts. Am. J. Optom. Physiol. Opt. 53, 740–745.
[96] Pelli, D.G., Robson, J.G., Wilkins, A.J., 1988. The design of a new letter chart measuring contrast sensitivity. Clin. Vis. Sci. 2, 187–199.
[97] Bach, M., 1996. The Freiburg visual acuity test – automatic measure-ment of visual acuity. Optometry and Vision Science 73 (1), 49–53.
[98] Wechsler, D., 1997. Wechsler Adult Intelligence Scale, 3rd ed. The Psychological Corporation, San Antonio, TX.
[99] Anstey, K.J., Smith, G.A., 1999. Interrelationships among biological markers of aging, health, activity, acculturation, and cognitive performance in late adulthood. Psychol. Aging 14 (4), 605–618.
[100] Wetton, M.A., Horswill, M.S., Hatherly, C., Wood, J.M., Pachana, N.A., Anstey, K.J., 2009. The development and validation of two complementary measures of older drivers’ hazard perception ability. In: Experimental Psychology Conference, Wollongong, NSW, Australia.
[101] Horswill, M.S., Anstey, K.J., Hatherly, C.G., Wood, J.M., 2010a. The crash involvement of older drivers is associated with their hazard perception latencies. J. Int. Neuropsychol. Soc., 1–6.
[102] Marrington, S.A., Horswill, M.S., Wood, J.M., 2008. The effect of simulated cataracts on drivers’ hazard perception ability. Optom. Vis. Sci. 85 (12), 1121–1127.
[103] Daigneault, G., Joly, P., Frigon, J.Y., 2002. Executive functions in the evaluation of accident risk of older drivers. J. Clin. Exp. Neuropsychol. 24 (2), 221–238.
[104] Decker, S.L., Hill, S.K., Dean, R.S., 2007. Evidence of construct similarity in executive functions and fluid reasoning abilities. Int. J. Neurosci. 117 (6), 735–748.
[105] Finkel, D., Pedersen, N.L., Pedersen, 2004. Processing speed and longitudinal trajectories of change for cognitive abilities: the Swedish adoption/twin study of aging. Aging Neuropsychol. Cogn. 11, 325–345.
[106] Wood, J.M., Anstey, K.J., Lacherez, P.F., Kerr, G.K., Mallon, K., Lord, S.R., 2009a. The onroad difficulties of older drivers and their relationship with self-reported motor vehicle crashes. J. Am. Geriatr. Soc. 57 (11), 2062–2069.
[107] Wolfe, J.M., Horowitz, T.S., 2004. What attributes guide the deployment of visualattention and how do they do it? Nature Reviews Neuroscience 5 (6), 495–501,1038/nrn1411.
[108] Barr, L.C., Yang, D.C.Y., Ranney, T.A., 2003. Exploratory analysis of truck driver distraction using naturalistic driving  data. In: Proceedings of the 82nd Annual Meeting of the Transportation Research Board, Washington, DC, 2003.
[109] Cosman, J.D., Lees, M.N., Lee, J.D., Rizzo, M., Vecera, S.P., 2012. Impaired atten-tional disengagement in older adults with useful field of view decline. Journalsof Gerontology - Series B Psychological Sciences and Social Sciences 67B (4).
[110] J.N., Helmers, K.F., Leveck, M.D., Kleinman, K., 2001. Active: a cognitive intervention trial to promote independence in older adults. Control. Clin. Trials 22 (4), 453–479.
[111] Racette, L., & Casson, E. J. (2005). The impact of visual field loss on driving performance: Evidence from on-road driving assessments. Optometry and Vision Science, 82(8), 668–674.

All published work is licensed under a Creative Commons Attribution 4.0 International License.

Copyright © 2016 - 2031 Clausius Scientific Press Inc. All Rights Reserved.