Analysis of the Driver Attention under Curved Road Conditions
Driving around curved road is a usual task performed by many on a daily basis but the underlying influences of attention of the driver under different curve conditions largely unknown. Previous research has shown that driving performance and visual performance can be a critical component of bends an...
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| Published in | Journal of the Eastern Asia Society for Transportation Studies Vol. 12; pp. 1931 - 1949 |
|---|---|
| Main Authors | , , , |
| Format | Journal Article |
| Language | English |
| Published |
Eastern Asia Society for Transportation Studies
2017
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| Subjects | |
| Online Access | Get full text |
| ISSN | 1881-1124 |
| DOI | 10.11175/easts.12.1931 |
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| Abstract | Driving around curved road is a usual task performed by many on a daily basis but the underlying influences of attention of the driver under different curve conditions largely unknown. Previous research has shown that driving performance and visual performance can be a critical component of bends analysis. However, with change of road conditions and vehicle information, there is growing competition over the attentional resources that are needed to vehicle maneuver. Here we examined how different curved roads influenced driving attention performance along a simulated curved road. Twenty-eight subjects of different ages and occupations were invited to participate in the experiment. Results showed there are clear differences on attention between the curved road groups. Under the continuous curves, drivers suffer the more complex driving environment and need to observe the more objects, scatter attention, increased the scope of observation which will increase the cognitive workload, decrease attention and UFOV. |
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| AbstractList | Driving around curved road is a usual task performed by many on a daily basis but the underlying influences of attention of the driver under different curve conditions largely unknown. Previous research has shown that driving performance and visual performance can be a critical component of bends analysis. However, with change of road conditions and vehicle information, there is growing competition over the attentional resources that are needed to vehicle maneuver. Here we examined how different curved roads influenced driving attention performance along a simulated curved road. Twenty-eight subjects of different ages and occupations were invited to participate in the experiment. Results showed there are clear differences on attention between the curved road groups. Under the continuous curves, drivers suffer the more complex driving environment and need to observe the more objects, scatter attention, increased the scope of observation which will increase the cognitive workload, decrease attention and UFOV. |
| Author | KIM, Wonchul NAMGUNG, Moon KANG, Xuejian WANG, Weijie |
| Author_xml | – sequence: 1 fullname: KANG, Xuejian organization: Department of Civil & Environmental Engineering, Wonkwang University – sequence: 1 fullname: KIM, Wonchul organization: Department of Regional & Urban Research, Chungnam Institute – sequence: 1 fullname: NAMGUNG, Moon organization: Department of Civil & Environmental Engineering, Wonkwang University – sequence: 1 fullname: WANG, Weijie organization: College of Transportation Science & Engineering, Nanjing Tech University |
| BackLink | https://cir.nii.ac.jp/crid/1390282680267497856$$DView record in CiNii |
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| ContentType | Journal Article |
| Copyright | 2017 Eastern Asia Society for Transportation Studies |
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| DOI | 10.11175/easts.12.1931 |
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Surrogate in-vehicle information systems and driver behaviour: Effects of visual and cognitive load in simulated rural driving. Transportation Research Part F: Traffic Psychology and Behaviour, 8, 79-96. Brookhuis, K.A., De Waard, D. (2000). Assessment of driver´s workload: performance and subjective and physiological indexes. In P.A. Hancock & P. A. Desmond (Eds.), Stress, Workload, and Fatigue. London: Lawrence Erlbaum Associates, Inc, 321-333. Baldwin, C.L., Coyne, J.T. (2003). Mental workload as a function of traffic density: comparison of physiological, behavioral, and subjective indices. Proceedings of the Second International Driving Symposium on Human Factors, 19-24. Wilkie, R. M., Wann, J. P., Allison, R. S. (2008). Active gaze, visual look-ahead, and locomotor control. Journal of Experimental Psychology: Human Perception and Performance, 34(5), 1150-1164. Ball, K., Owsley, C., Sloane, M., Roenker, D., Bruni, J. (1993). 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Journal of Experimental Psychology: Human Perception and Performance, 29(2), 363-378. Elvik, R., Christensen, P., Amundsen, A. (2004). Speed and road accidents. An evaluation of the Power Model. TØI report 740/2004. Institute of Transport Economics TOI, Oslo. Klimesch, W. (1999). EEG alpha and theta oscillations reflect cognitive and memory performance: A review and analysis. Brain Research Reviews, 29(2-3), 169-195. Underwood, G., Crundall, D., Chapman, P. (2011). Driving simulator validation with hazard perception. Transportation Research Part F: Traffic Psychology and Behavior, 14: 435-446. Recarte, M., Nunes, L. (2003). Mental workload while driving: Effects on visual search, discrimination, and decision making. Journal of Experimental Psychology: Applied, 9: 119-137. Jennifer. L.O'Brien, Jennifer .J, Listerb. Carol, L. Peronto, Jerri. Edwards. (2015). Perceptual and cognitive neural correlates of the useful field of view test in older adults. Science Direct, I62435, 167-174. Victor, T. W., Engström, J., Harbluk, J. L. (2008). Distraction assessment methods based on visual behavior and event detection. In M. Regan, J. Lee, & K. Young (Eds.), Driver distraction: Theory. Effects and Mitigation: CRC Press. Young, M.S., Mahfoud, J.M., Stanton, N.A., Salmon, P.M., Jenkins, D.P., Walker, G.H. (2009). The implications of roadside advertising for driver attention and eye movements. Transportation Research Part F: Traffic Psychology and Behaviour, 12, 381-388. Ariën, C., Jongen, E.M.M., Brijs, K., Brijs, T., Daniels, S., Wets, G. (2013). A simulator study on the impact of traffic calming measures in urban areas on driving behavior and workload. Accident Analysis and Prevention, 61, 43-53. Clay, O.J., Edwards, J.D., Ross, L.A., Okonkwo, O., Wadley, V.G., Roth, D.L. (2009). Visual function and cognitive speed of processing mediate age related decline in memory span and fluid intelligence. Jour. Aging Health, 21, 547-566. Taubman-Ben-Ari, O., Mikulincer, M., Gillath, O. (2004). The multidimensional driving style inventory. Scale construct and validation. Accid. Anal. Prevent, 36, 323-332. Cantin, V., Lavallière, M., Simoneau, M. Teasdale, N. (2009). Mental workload when driving in a simulator: effects of age and driving complexity. Accident Analysis and Prevention, 41(4), 763-771. Smith, M.E., Gevins, A., Brown, H., Karnik, A., Du, R. (2001). Monitoring task loading with multivariate EEG measures during complex forms of human.computer interaction. Human Factors, 43(3), 366-380. Owsley,C. (2013). Visual Processing Speed.Vis.Res.90,52-56. Lunsman, M., Edwards, J.D., Andel, R., Small, B.J., Ball, K.K., Roenker, D.L. (2008). What predicts changes in useful field of view test performance? Psychol, 23,917-927. Salvucci, D. D., Beltowska, J. (2008). Effects of memory rehearsal on driver performance: Experiment and theoretical account. Human Factors, 50(5), 834-844. Wang, C.A., Fu, R.A., Peng, J.S.B., Mao, J.A. (2014). Driving style classification method for lane change warning system. J. Transport. Syst. Eng. Inform. Technol, 14 (3), 187-193. Van Orden, K., Jung, T., Makeig, S. (2000). Combined eye activity measures accurately estimate changes in sustained visual task performance. Biological Psychology, Volume 52, Issue 3, March 2000, 221-240. Sanders, A.F. (1970). Some aspects of the selective process in the functional visual field. Ergonomics, 13 (1), 101-117. Lee, H. C., Cameron, D., Lee, A. H. (2003). Assessing the driving performance of older adult drivers: On-road versus simulated driving. Accident Analysis and Prevention, 35, 797-803. Lappi, O., Lehtonen, E., Pekkanen, J., Itkonen, T. (2013). Beyond the tangent point: Gaze targets in naturalistic driving. Journal of Vision, 13, 1-18. Salvucci, D. D., Gray, R. (2004). A two-point visual control model of steering. Perception, 33, 1233-1248. Brookhuis, K.A., De Waard, D. (2010). Monitoring drivers’ workload in driving simulators using physiological measures. Accident Analysis & Prevention, 42, 898-903. Strayer, D. L., Drews, F. A. (2004). Profiles in driver distraction: Effects of cell phone conversations on younger and older drivers. Human Factors, 46, 640-649. Goode, N., Salmon, P. M., Lenné, M. G. (2013). Simulation-based driver and vehicle crew training: Applications, efficacy and future dir |
| References_xml | – reference: Cloete, S., Wallis, G. M. (2011). Visuomotor control of steering: The arte fact of the matter. Experimental Brain Research, 208, 475-489. – reference: Holm, A., Lukander, K., Korpela, J., Sallinen, M., üller, K. M.I. (2009). Estimating brain load from the EEG. Scientific World Journal, 9, 639-651. – reference: Ball, K., Wadley, V., Edwards. J. (1992). Advances in technology used to assess and retrain older drivers. Gerontechnology, 1(4), 251-261. – reference: Patten, C.J.D., Kircher, A., Östlund, J., Nilsson, L., Svenson, O. (2006). Driver experience and cognitive workload in different traffic environments. Accident Analysis and Prevention, 38, 887-894. – reference: Ayaz, H., Shewokis, P.A., Bunce, S., Izzetoglu, K., Willems, B., Onaral, B. (2012). Optical brain monitoring for operator training andmental workload assessment. NeuroImage, 59, 36-47. – reference: Beanland, V., Goode, N., Salmon, P. M., Lenne, M. G. (2013). Is there a case for driver training? A review of the efficacy of pre-and post-licence driver training. Safety Science, 51, 127-137. – reference: Strayer, D. L., Drews, F. A. (2004). Profiles in driver distraction: Effects of cell phone conversations on younger and older drivers. Human Factors, 46, 640-649. – reference: Lunsman, M., Edwards, J.D., Andel, R., Small, B.J., Ball, K.K., Roenker, D.L. (2008). What predicts changes in useful field of view test performance? Psychol, 23,917-927. – reference: Taubman-Ben-Ari, O., Mikulincer, M., Gillath, O. (2004). The multidimensional driving style inventory. Scale construct and validation. Accid. Anal. Prevent, 36, 323-332. – reference: Oh, D., Namgung, M., Park, H. (2015). A research on the characteristics of EEG information on the Drive Behavior. J. Korea Inst. The Journal of The Korea Institute of Intelligent Transport Systems, 5, 23-29. – reference: Hayhoe, M., Ballard, D. (2005). Eye movements in natural behavior. TRENDS in Cognitive Sciences, 9(4). – reference: Cooper, J. M., Medeiros-Ward, N., Strayer, D. L. (2013). The impact of eye movements and cognitive workload on lateral position variability in driving. Human Factors, 55(5), 1001-1014. – reference: Hoedemaeker, M. (2002). Summary Description of Workload Indicators: WP1 Workload Measures. Human Machine Interface and the Safety of Traffic in Europe Growth Project. GRD1-2000-25361. HASTE. Institute for Transport Studies. Leeds, UK: University of Leeds. – reference: Recarte, M., Nunes, L. (2003). Mental workload while driving: Effects on visual search, discrimination, and decision making. Journal of Experimental Psychology: Applied, 9: 119-137. – reference: Jennifer. L.O'Brien, Jennifer .J, Listerb. Carol, L. Peronto, Jerri. Edwards. (2015). Perceptual and cognitive neural correlates of the useful field of view test in older adults. Science Direct, I62435, 167-174. – reference: Chen, S., Epps, J. (2013). Automatic classification of eye activity for cognitive load measurement with emotion interference. Compute Methods Programs Biomed, 110, 111-124. – reference: Jamson, A.H., Merat, N. (2005). Surrogate in-vehicle information systems and driver behaviour: Effects of visual and cognitive load in simulated rural driving. Transportation Research Part F: Traffic Psychology and Behaviour, 8, 79-96. – reference: Sekuler, A., Bennett, P., & Mamelak, M. (2000). Effects of aging on the useful field of view. Experimental Aging Research: An International Journal Devoted to the Scientific Study of the Aging Process, 26(2), 103-120. – reference: Land, M. F., Lee, D. N. (1994). Where we look when we steer. Nature, 369, 742-744. – reference: Land, M. F., Horwood, J. (1998). How speed affects the way visual information is used in steering. Vision in vehicles-VI. – reference: Brookhuis, K.A., De Waard, D. (2002). On the assessment of (mental) workload and other subjective qualifications. Ergonomics, 45(14), 1026-1030. – reference: Smith, M.E., Gevins, A., Brown, H., Karnik, A., Du, R. (2001). Monitoring task loading with multivariate EEG measures during complex forms of human.computer interaction. Human Factors, 43(3), 366-380. – reference: Brookhuis, K.A., De Waard, D. (2000). Assessment of driver´s workload: performance and subjective and physiological indexes. In P.A. Hancock & P. A. Desmond (Eds.), Stress, Workload, and Fatigue. London: Lawrence Erlbaum Associates, Inc, 321-333. – reference: Owsley, C., Ball, K.K., Keeton, D.M. (1995). Relationship between visual sensitivity and target localization in older adults. Vis. Res. 35, 579-587. – reference: Wilkie, R. M., Wann, J. P. (2003). Controlling steering and judging heading: Retinal flow, visual direction, and extraretinal information. Journal of Experimental Psychology: Human Perception and Performance, 29(2), 363-378. – reference: Scerbo, M.W., Freeman, F.G., Mikulka, P.J. (2003). A brain-based system for adaptive automation. Theoretical Issues in Ergonomics Science, 4(1-2), 200-219. – reference: Brookhuis, K.A., Van Driel, C. J., Hof, T., Van Arem, B., Hoedemaeker, M. (2009). Driving with a congestion assistant, mental workload and acceptance. Applied Ergonomics, 40(6), 1019-1025. – reference: Bonsall, P., Liu, R., Young, W., 2005. Modelling safety-related driving behaviour-impact of parameter values. Transport. Res. Part A, 39, 25-44. – reference: Sanders, A.F. (1970). Some aspects of the selective process in the functional visual field. Ergonomics, 13 (1), 101-117. – reference: Ball, K., Owsley, C. (1993). The useful field of view test: a new technique for evaluating age-related declines in visual function. Journal of the American Optometric Association, 64(1), 71-79. – reference: Klimesch, W. (1999). EEG alpha and theta oscillations reflect cognitive and memory performance: A review and analysis. Brain Research Reviews, 29(2-3), 169-195. – reference: Salvucci, D. D., Beltowska, J. (2008). Effects of memory rehearsal on driver performance: Experiment and theoretical account. Human Factors, 50(5), 834-844. – reference: Baldwin, C.L., Coyne, J.T. (2003). Mental workload as a function of traffic density: comparison of physiological, behavioral, and subjective indices. Proceedings of the Second International Driving Symposium on Human Factors, 19-24. – reference: Wilkie, R. M., Wann, J. P., Allison, R. S. (2008). Active gaze, visual look-ahead, and locomotor control. Journal of Experimental Psychology: Human Perception and Performance, 34(5), 1150-1164. – reference: Mehar, A., Chandra, S., Velmurugan, S. (2013). Speed and acceleration characteristics of different types of vehicles on multi-lane highways. Eur. Transport 55, 1-12.Medeiros-Ward, N., Cooper, J. M., & Strayer, D. L. (2014). Hierarchical control and driving. Journal of Experimental Psychology: General, 143(3), 953-958. – reference: Van Orden, K., Jung, T., Makeig, S. (2000). Combined eye activity measures accurately estimate changes in sustained visual task performance. Biological Psychology, Volume 52, Issue 3, March 2000, 221-240. – reference: Reimer, B., Mehler, B., Wang, Y., Coughlin, J. (2010). The impact of systematic variation of cognitive demand on drivers’ visual attention across multiple age groups. Proceedings of the Human Factors and Ergonomics Society Annual Meeting, 54(24): 2052-2055. – reference: Cantin, V., Lavallière, M., Simoneau, M. Teasdale, N. (2009). Mental workload when driving in a simulator: effects of age and driving complexity. Accident Analysis and Prevention, 41(4), 763-771. – reference: Lehtonen, E., Lappi, O., Summala, H. (2012). Anticipatory eye movements when approaching a curve on a rural road depend on working memory load. Transportation Research Part F: Traffic Psychology and Behaviour, 15, 369-377. – reference: Owsley,C. (2013). Visual Processing Speed.Vis.Res.90,52-56. – reference: Ariën, C., Jongen, E.M.M., Brijs, K., Brijs, T., Daniels, S., Wets, G. (2013). A simulator study on the impact of traffic calming measures in urban areas on driving behavior and workload. Accident Analysis and Prevention, 61, 43-53. – reference: Underwood, G., Crundall, D., Chapman, P. (2011). Driving simulator validation with hazard perception. Transportation Research Part F: Traffic Psychology and Behavior, 14: 435-446. – reference: Goode, N., Salmon, P. M., Lenné, M. G. (2013). Simulation-based driver and vehicle crew training: Applications, efficacy and future directions. Applied Ergonomics, 44, 435-444. – reference: Wilkie, R. M., Kountouriotis, G. K., Merat, N., Wann, J. P. (2010). Using vision to control locomotion: Looking where you want to go. Experimental Brain Research, 204(4), 539-547. – reference: Aarts, L., Van Schagen, I. (2006). Driving speed and the risk of road crashes: A review. Accident Analysis and Prevention, 38, 215-224. – reference: Elvik, R., Christensen, P., Amundsen, A. (2004). Speed and road accidents. An evaluation of the Power Model. TØI report 740/2004. Institute of Transport Economics TOI, Oslo. – reference: Radach, R. (1998). Eye guidance and visual information processing: reading, visual search, picture perception and driving. In G. Underwood (Ed.), Eye Guidance in Reading and Scene Perception, Oxford, England: Elsevier, 1-27. – reference: Victor, T. W., Engström, J., Harbluk, J. L. (2008). Distraction assessment methods based on visual behavior and event detection. In M. Regan, J. Lee, & K. Young (Eds.), Driver distraction: Theory. Effects and Mitigation: CRC Press. – reference: Lee, H. C., Cameron, D., Lee, A. H. (2003). Assessing the driving performance of older adult drivers: On-road versus simulated driving. Accident Analysis and Prevention, 35, 797-803. – reference: Lappi, O., Lehtonen, E., Pekkanen, J., Itkonen, T. (2013). Beyond the tangent point: Gaze targets in naturalistic driving. Journal of Vision, 13, 1-18. – reference: Dijksterhuis, C., Brookhuis, K. A., De Waard, D. (2011). Effects of steering demand on lane keeping behaviour, self-reports, and physiology a simulator study. Accident Analysis and Prevention, 43, 1074-1081. – reference: Young, M.S., Mahfoud, J.M., Stanton, N.A., Salmon, P.M., Jenkins, D.P., Walker, G.H. (2009). The implications of roadside advertising for driver attention and eye movements. Transportation Research Part F: Traffic Psychology and Behaviour, 12, 381-388. – reference: P.M. van Leeuwen, R. Happee, J.C.F. de Winter. (2014).Vertical field of view restriction in driver training: A simulator-based evaluation. Transportation Research Part F, 24, 169-182. – reference: Brookhuis, K.A., De Waard, D., (1993). The use of psychophysiology to assess driver status. Ergonomics, 36(9), 1099-1110. – reference: Sharma, N., Gedeon, T. (2012). Objective measures, sensors and computational techniques for stress recognition and classification: a survey. Compute Methods Programs Biomed, 108, 1287-1301. – reference: Brookhuis, K.A., De Waard, D. (2010). Monitoring drivers’ workload in driving simulators using physiological measures. Accident Analysis & Prevention, 42, 898-903. – reference: Cooper, P. J. (1997). The relationship between speeding behavior as measured by violation convictions and crash involvement. Journal of Safety Research, 28, 83-95. – reference: Laura Eboli, Gabriella Mazzulla, Giuseppe Pungillo. (2016). Combining speed and acceleration to define car users’ safe or unsafe driving behaviour. Transportation Research Part C, 68. 113-125. – reference: Wang, C.A., Fu, R.A., Peng, J.S.B., Mao, J.A. (2014). Driving style classification method for lane change warning system. J. Transport. Syst. Eng. Inform. Technol, 14 (3), 187-193. – reference: Ball, K., Owsley, C., Sloane, M., Roenker, D., Bruni, J. (1993). Visual attention problems as a predictor of vehicle crashes in older drivers. Investigative Ophthalmology & Visual Science, 34, 3110-3123. – reference: Clay, O.J., Edwards, J.D., Ross, L.A., Okonkwo, O., Wadley, V.G., Roth, D.L. (2009). Visual function and cognitive speed of processing mediate age related decline in memory span and fluid intelligence. Jour. Aging Health, 21, 547-566. – reference: Salvucci, D. D., Gray, R. (2004). A two-point visual control model of steering. Perception, 33, 1233-1248. – reference: Wickens, C.D. (1992). Engineering Psychology and Human Performance. Harper Collins Publishers, New York. |
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| SubjectTerms | Curved Road Driving Attention Driving Performance Driving Simulation System Visual Performance |
| Title | Analysis of the Driver Attention under Curved Road Conditions |
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| ispartofPNX | Journal of the Eastern Asia Society for Transportation Studies, 2017, Vol.12, pp.1931-1949 |
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