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Eye Movements in Vehicle Control

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Eye Movement Research

Abstract

Measuring gaze behaviour is useful to understand the cognitive processes involved in vehicle control and to test new assistance technology. Most of the research on eye movements in vehicle control was conducted in the context of road traffic and will therefore be focused on in this chapter. In the following, we will first introduce the driving task and outline how the eye-tracking methodology can be used to get insights into the cognitive processes that guide driving behaviour. Furthermore, we will highlight important classical findings and recent developments in the field of eye movements in driving. These include eye movements during basic vehicle control tasks like steering, driving manoeuvres and detecting hazards in the road environment. Additionally, factors influencing task performance (e.g., effects of visual distraction, workload, fatigue, driving experience, and aging) that can be observed by applying the eye-tracking method will be introduced. Conducting an eye-tracking study in the driving context often takes place in complex and highly dynamic environments. Therefore, in the last part of this chapter, we will give a practical guideline of what is important in order to study eye movements in the context of vehicle control including an overview of the most commonly used parameters to describe gaze behaviour in the context of driving. We will sum up this introductory chapter with an outline for future research on the topic of eye movements in vehicle control.

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Notes

  1. 1.

    Although the information a driver uses is predominantly visual (Sivak, 1996), the driver also processes information from other perceptual systems. For example, it has been shown that the driver uses auditory information in order to judge the driving speed (Evans, 1970) or vestibular information during lane changing (Macuga, Beall, Kelly, Smith, & Loomis, 2007). However, in this chapter, we focus on visual information.

  2. 2.

    However, there are slight differences between these terms, e.g., a gaze consists of multiple fixations on the same object (Crundall & Underwood, 2011).

References

  • Ahlstrom, C., Nyström, M., Holmqvist, K., Fors, C., Sandberg, D., Anund, A., et al. (2013). Fit-for-duty test for estimation of drivers’ sleepiness level: Eye movements improve the sleep/wake predictor. Transportation Research Part C: Emerging Technologies, 26, 20–32.

    Article  Google Scholar 

  • Alberti, C. F., Shahar, A., & Crundall, D. (2014). Are experienced drivers more likely than novice drivers to benefit from driving simulations with a wide field of view? Transportation Research Part F: Traffic Psychology and Behaviour, 27, 124–132.

    Article  Google Scholar 

  • Alexander, G. J., & Lunefeld, H. (1986). Driver expectancy in highway design and traffic operations (Report No. FHWA-TO-86–1). Washington, DC: U.S. Department of Transportation.

    Google Scholar 

  • Alliance of Automobile Manufacturers Driver Focus-Telematics Working Group. (2003). Statement of principles, criteria and verification procedures on driver interactions with advanced in-vehicle information and communication systems. Retrieved from http://www.autoalliance.org.

  • Authié, C. N., & Mestre, D. R. (2012). Path curvature discrimination: Dependence on gaze direction and optical flow speed. PLoS ONE, 7(2), 1–12.

    Article  Google Scholar 

  • Ball, K. K., Beard, B. L., Roenker, D. L., Miller, R. L., & Griggs, D. S. (1988). Age and visual search: Expanding the useful field of view. Journal of the Optical Society of America A, 5, 2210–2219.

    Article  Google Scholar 

  • Bao, S., & Boyle, L. N. (2009). Age-related differences in visual scanning at median-divided highway intersections in rural areas. Accident Analysis and Prevention, 41, 146–152.

    Article  PubMed  Google Scholar 

  • Baumann, M. R. K., & Krems, J. F. (2007). Situation awareness and driving: A cognitive model. In P. C. Cacciabue (Ed.), Modelling driver behaviour in automotive environments: Critical issues in driver interactions with intelligent transport systems (pp. 253–265). London, United Kingdom: Springer.

    Chapter  Google Scholar 

  • Baumann, M. R. K., & Krems, J. F. (2009). A comprehension based cognitive model of situation awareness. In Lecture Notes in Computer Science (Vol. 5620, pp. 192–201). Berlin, Germany: Springer.

    Google Scholar 

  • Beggiato, M., & Krems, J. F. (2013, November). Sequence analysis of glance patterns to predict lane changes on urban arterial roads. Paper presented at 6. Tagung Fahrerassistenz—Der Weg zum automatischen Fahren, Munich, Germany.

    Google Scholar 

  • Borowsky, A., Shinar, D., & Oron-Gilad, T. (2010). Age, skill, and hazard perception in driving. Accident Analysis and Prevention, 42, 1240–1249.

    Article  PubMed  Google Scholar 

  • Bortz, J., & Döring, N. (2002). Forschungsmethoden und Evaluation (3rd ed.). Berlin, Germany: Springer.

    Book  Google Scholar 

  • Brown, I. (2005). Review of the ‘looked but failed to see’ accident causation factor (Road Safety Research Report No. 60). London, United Kingdom: Department for Transport.

    Google Scholar 

  • Bubb, H., & Wohlfarter, M. (2013). Eye-tracking data analysis and neuroergonomics. In M. Fafrowicz, T. Marek, W. Karwowski, & D. Schmorrow (Eds.), Neuroadaptive systems: Theory and applications (pp. 255–310). Boca Raton, FL: CRC Press.

    Google Scholar 

  • Bundesministerium für Verkehr und digitale Infrastruktur (BMVI). (2014). Verkehr in Zahlen 2014/2015. Hamburg, Germany: DVV Media Group.

    Google Scholar 

  • Caird, J. K., Willness, C. R., Steel, P., & Scialfa, C. (2008). A meta-analysis of the effects of cell phones on driver performance. Accident Analysis and Prevention, 40, 1282–1293.

    Article  PubMed  Google Scholar 

  • Carbonell, J. R. (1966). A queuing model of many-instrument visual sampling. IEEE Transactions on Human Factors in Electronics, HFE-7(4), 157–164.

    Article  Google Scholar 

  • Cardona, G., & Quevedo, N. (2013). Blinking and driving: The influence of saccades and cognitive workload. Current Eye Research, 39, 239–244.

    Article  PubMed  Google Scholar 

  • Castro, C. (2009). Human factors of visual and cognitive performance in driving. Boca Raton, FL: CRC Press.

    Google Scholar 

  • Chapman, P. R., & Underwood, G. (1998). Visual search of driving situations: Danger and experience. Perception, 27, 951–964.

    Article  PubMed  Google Scholar 

  • Chapman, P. R., Underwood, G., & Roberts, K. (2002). Visual search patterns in trained and untrained novice drivers. Transportation Research Part F: Traffic Psychology and Behaviour, 5, 157–167.

    Article  Google Scholar 

  • Chun, J., Lee, I., Park, G., Seo, J., Choi, S., & Han, S. H. (2013). Efficacy of haptic blind spot warnings applied through a steering wheel or a seatbelt. Transportation Research Part F: Traffic Psychology and Behaviour, 21, 231–241.

    Article  Google Scholar 

  • Costa, M., Simone, A., Vignali, V., Lantieri, C., Bucchi, A., & Dondi, G. (2014). Looking behavior for vertical road signs. Transportation Research Part F: Traffic Psychology and Behaviour, 23, 147–155.

    Article  Google Scholar 

  • Crabb, D. P., Smith, N. D., Rauscher, F. G., Chisholm, C. M., Barbur, J. L., Edgar, D. F., & Garwey-Heath, D. F. (2010). Exploring eye movements in patients with glaucoma when viewing a driving scene. PLoS One, 5(3), e9710.

    Google Scholar 

  • Crundall, D., Chapman, P. R., Trawley, S., Collins, L., van Loon, E., Andrews, B., & Underwood, G. (2012). Some hazards are more attractive than others: Drivers of varying experience respond differently to different types of hazard. Accident Analysis & Prevention, 45, 600–609.

    Google Scholar 

  • Crundall, D., van Loon, E., & Underwood, G. (2006). Attraction and distraction of attention with roadside advertisements. Accident Analysis and Prevention, 38, 671–677.

    Article  PubMed  Google Scholar 

  • Crundall, D., & Underwood, G. (2011). Visual attention while driving. In B. E. Porter (Ed.), Handbook of traffic psychology (pp. 137–148). San Diego, CA: Academic Press.

    Chapter  Google Scholar 

  • Crundall, D., Underwood, G., & Chapman, P. R. (1999). Driving experience and the functional field of view. Perception, 28, 1075–1087.

    Article  PubMed  Google Scholar 

  • Deubel, H., & Schneider, W. X. (1996). Saccade target selection and object recognition: Evidence for a common attentional mechanism. Vision Research, 36, 1827–1837.

    Article  PubMed  Google Scholar 

  • Dishart, D. C., & Land, M. F. (1998). The development of the eye movement strategies of learner drivers. In G. Underwood (Ed.), Eye guidance in reading and scene perception. Kidlington, Umited Kingdom: Elsevier Science Ltd.

    Google Scholar 

  • Donges, E. (1978). A two-level model of driver steering behaviour. Human Factors, 20, 691–707.

    Article  Google Scholar 

  • Doshi, A., & Trivedi, M. M. (2009). On the roles of eye gaze and head dynamics in predicting driver’s intent to change lanes. IEEE Transactions on Intelligent Transportation Systems, 10, 452–463.

    Article  Google Scholar 

  • Drews, F. A., & Strayer, D. L. (2009). Cellular phones and driver distraction. In M. A. Regan, J. D. Lee, & K. L. Young (Eds.), Driver distraction (pp. 169–190). Boca Raton, FL: CRC Press.

    Google Scholar 

  • Duchowski, A. (2007). Eye tracking methodology: Theory and practice. London, United Kingdom: Springer.

    Google Scholar 

  • Durso, F. T., Rawson, K. A., & Girotto, S. (2007). Comprehension and situation awareness. In F. T. Durso (Ed.), Handbook of applied cognition (2nd ed., pp. 163–194). Chichester, United Kingdom: Wiley.

    Chapter  Google Scholar 

  • Endsley, M. R. (1995). Measurement of situation awareness in dynamic systems. Human Factors, 37, 65–84.

    Article  Google Scholar 

  • Endsley, M. R., & Garland, D. J. (2000). Situation awareness: Analysis and measurement. Mahwah, NJ: Lawrence Erlbaum Associates.

    Google Scholar 

  • Engström, J., & Hollnagel, E. (2007). A general conceptual framework for modelling behavioural effects of driver support functions. In P. Cacciabue (Ed.), Modelling driver behaviour in automotive environments: Critical issues in driver interactions with intelligent transport systems (pp. 61–84). London, United Kingdom: Springer.

    Chapter  Google Scholar 

  • Evans, L. (1970). Speed estimation from a moving automobile. Ergonomics, 13(2), 219–230.

    Article  Google Scholar 

  • Falkmer, T., & Gregersen, N. P. (2005). A comparison of eye movement behaviour of inexperienced and experienced drivers in real traffic environments. Optometry and Vision Science, 82, 732–739.

    Article  PubMed  Google Scholar 

  • Fisher, D. L., Pollatsek, A., & Horrey, W. J. (2011). Eye behaviors: How driving simulators can expand their role in science and engineering. In D. L. Fisher, M. Rizzo, J. K. Caird, & J. D. Lee (Eds.), Handbook of driving simulation for engineering, medicine, and psychology (pp. 18.1–18.22). Boca Raton, FL: CRC Press.

    Chapter  Google Scholar 

  • Fisher, D. L., Pradhan, A. K., Pollatsek, A., & Knodler, M. A. (2007). Empirical evaluation of hazard anticipation behaviors in the field and on driving simulator using eye tracker. Transportation Research Record: Journal of the Transportation Research Board, 2018, 80–86.

    Article  Google Scholar 

  • Fitts, P. M., Jones, R. E., & Milton, J. L. (1950). Eye movements of aircraft pilots during instrument-landing approaches. Aeronautical Engineering Review, 9(2), 24–29.

    Google Scholar 

  • Gibson, J. J. (1950). Perception and the visual world. Boston, MA: Houghton Mifflin.

    Google Scholar 

  • Greenwald, A. G. (1976). Within-subjects design: To use or not to use? Psychological Bulletin, 83, 314–320.

    Article  Google Scholar 

  • Harbluk, J. L., Noy, Y. I., Trbovich, P. L., & Eizenman, M. (2007). An on-road assessment of cognitive distraction: Impacts on drivers’ visual behaviour and braking performance. Accident Analysis and Prevention, 39, 372–379.

    Article  PubMed  Google Scholar 

  • He, J., Becic, E., Lee, Y., & McCarley, J. S. (2011). Mind wandering behind the wheel: Performance and oculomotor correlates. Human Factors, 53, 13–21.

    Article  PubMed  Google Scholar 

  • Henning, M. (2010). Preparation for lane change manoeuvres: Behavioural indicators and underlying cognitive processes (Doctoral dissertation). Technische Universität Chemnitz, Chemnitz, Germany.

    Google Scholar 

  • Herslund, M., & Jörgensen, N. O. (2003). Looked-but-failed-to-see-errors in traffic. Accident Analysis and Prevention, 35, 885–891.

    Article  PubMed  Google Scholar 

  • Hess, E. H., & Polt, J. M. (1964). Pupil size in relation to mental activity during simple problem-solving. Science, 143, 1190–1192.

    Article  PubMed  Google Scholar 

  • Hills, B. L. (1980). Vision, visibility and perception in driving. Perception, 3, 434–467.

    Google Scholar 

  • Hoffman, J. E., & Subramaniam, B. (1995). The role of visual attention in saccadic eye movements. Perception and Psychophysics, 57, 787–795.

    Article  PubMed  Google Scholar 

  • Hollnagel, E., & Woods, D. D. (2005). Joint cognitive systems: Foundations of cognitive systems engineering. Boca Raton, FL: CRC Press.

    Book  Google Scholar 

  • Holmqvist, K., Nyström, M., Andersson, R., Dewhurst, R., Jarodzka, H., & van de Weijer, J. (2011). Eye tracking: A comprehensive guide to methods and measures. Oxford, United Kingdom: Oxford University Press.

    Google Scholar 

  • Horrey, W. J. (2009). On allocating the eyes: Visual attention and in-vehicle technologies. In C. Castro (Ed.), Human factors of visual and cognitive performance in driving (pp. 151–166). Boca Raton, FL: CRC Press.

    Google Scholar 

  • Hosking, S. G., Liu, C. C., & Bayly, M. (2010). The visual search patterns and hazard responses of experienced and inexperienced motorcycle riders. Accident Analysis and Prevention, 42, 196–202.

    Article  PubMed  Google Scholar 

  • Huestegge, L., Skottke, E., Anders, S., Müsseler, J., & Debus, G. (2010). The development of hazard perception: Dissociation of visual orientation and hazard processing. Transportation Research Part F: Traffic Psychology and Behaviour, 13, 1–8.

    Article  Google Scholar 

  • Irwin, D. E. (2004). Fixation location and fixation duration as indices of cognitive processing. In J. M. Henderson & F. Ferreira (Eds.), The interface of language, vision, and action: Eye movements and the visual world (pp. 105–133). New York, NY: Psychology Press.

    Google Scholar 

  • Jacob, R. J. K., & Karn, K. S. (2003). Eye tracking in human-computer interaction and usability research: Ready to deliver the promises. In J. Hyönä, R. Radach, & H. Deubel (Eds.), The mind’s eye: Cognitive and applied aspects of eye movement research (Vol. 2, pp. 573–605). Amsterdam, Netherlands: Elsevier.

    Chapter  Google Scholar 

  • Just, M. A., & Carpenter, P. A. (1976). Eye fixations and cognitive processes. Cognitive Psychology, 8, 441–480.

    Article  Google Scholar 

  • Kircher, A., Uddman, M., & Sandin, J. (2002). Vehicle control and drowsiness (Report No. VTI meddelande 922A). Linköping, Sweden: Swedish National Road and Transport Research Institute.

    Google Scholar 

  • Kirchner, W. K. (1958). Age differences in short-term retention of rapidly changing information. Journal of Experimental Psychology, 55, 352–358.

    Article  PubMed  Google Scholar 

  • 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 (Report No. DOT HS 810 594). Washington, DC: National Highway Traffic Safety Administration.

    Google Scholar 

  • Klauer, S. G., Perez, M., & McClafferty, J. (2011). Naturalistic driving studies and data coding and analysis techniques. In B. E. Porter (Ed.), Handbook of traffic psychology (pp. 73–85). San Diego, CA: Academic Press.

    Chapter  Google Scholar 

  • Konstantopoulos, P., Chapman, P., & Crundall, D. (2010). Driver’s visual attention as a function of driving experience and visibility: Using a driving simulator to explore drivers’ eye movements in day, night and rain driving. Accident Analysis and Prevention, 42, 827–834.

    Article  PubMed  Google Scholar 

  • Krems, J. F., & Baumann, M. R. K. (2009). Driving and situation awareness: A cognitive model of memory-update processes. In Lecture Notes in Computer Science (Vol. 5619, pp. 986–994). Berlin, Germany: Springer.

    Google Scholar 

  • Krems, J. F., & Petzoldt, T. (2011). Tools and procedures for measuring safety-relevant criteria. In Y. Barnard, R. Risser, & J. F. Krems (Eds.), The safety of intelligent driver support systems (pp. 93–109). Farnham, United Kingdom: Ashgate.

    Google Scholar 

  • Lamble, D., Summala, H., & Hyvärinen, L. (2002). Driving performance of drivers with impaired central visual field acuity. Accident Analysis and Prevention, 34, 711–716.

    Article  PubMed  Google Scholar 

  • Land, M. F. (1992). Predictable eye-head coordination during driving. Nature, 359, 318–320.

    Article  PubMed  Google Scholar 

  • Land, M. F. (2006). Eye movements and the control of actions in everyday life. Progress in Retinal and Eye Research, 25, 296–324.

    Article  PubMed  Google Scholar 

  • Land, M. F. (2007). Fixation strategies during active behaviour: A brief history. In R. P. G. van Gompel, M. H. Fischer, W. S. Murray, & R. L. Hill (Eds.), Eye movements: A window on mind and brain (pp. 75–95). Oxford, United Kingdom: Elsevier.

    Chapter  Google Scholar 

  • Land, M. F., & Horwood, J. (1995). Which parts of the road guide steering? Nature, 377, 339–340.

    Article  PubMed  Google Scholar 

  • Land, M. F., & Lee, D. N. (1994). Where we look when we steer. Nature, 369, 742–744.

    Article  PubMed  Google Scholar 

  • Lappi, O. (2014). Future path and tangent point models in the visual control of locomotion in curve driving. Journal of Vision, 14, 1–22.

    Article  Google Scholar 

  • Lappi, O., Lehtonen, E., Pekkanen, J., & Itkonen, T. (2013). Beyond the tangent point: Gaze targets in naturalistic driving. Journal of Vision, 13(13), 1–18.

    Article  Google Scholar 

  • Lee, J. D. (2008). Fifty years of driving safety research. Human Factors, 50, 521–528.

    Article  PubMed  Google Scholar 

  • Lee, S. E., Olsen, E. C. B., & Wierwille, W. W. (2004). A comprehensive examination of naturalistic lane-changes (Report No. DOT HS 809 702). Washington, DC: National Highway Traffic Safety Administration.

    Google Scholar 

  • Lestina, D. C., & Miller, T. R. (1994). Characteristics of crash-involved younger drivers. In 38th Annual proceedings of the association for the advancement of automotive medicine (pp. 425–437). Des Plaines, IL: Association for the Advancement of Automotive Medicine.

    Google Scholar 

  • Lethaus, F., Harris, R. M., Baumann, M. R. K., Köster, F., & Lemmer, K. (2013). Windows of driver gaze data: How early and how much for robust predictions of driver intent? In M. Tomassini, A. Antonioni, F. Daolio, & P. Buesser (Eds.), Adaptive and natural computing algorithms (pp. 446–455). Berlin, Germany: Springer.

    Chapter  Google Scholar 

  • Lethaus, F., & Rataj, J. (2007). Do eye movements reflect driving manoeuvres? IET Intelligent Transport Systems, 1, 199–204.

    Article  Google Scholar 

  • Lehtonen, E., Lappi, O., Koirikivi, I., & Summala, H. (2014). Effect of driving experience on anticipatory look-ahead fixations in real curve driving. Accident Analysis and Prevention, 70, 195–208.

    Article  PubMed  Google Scholar 

  • 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.

    Article  Google Scholar 

  • Liang, Y., Lee, J. D., & Yekhshatyan, L. (2012). How dangerous is looking away from the road? Algorithms predict crash risk from glance patterns in naturalistic driving. Human Factors, 54, 1104–1116.

    Article  PubMed  Google Scholar 

  • Mack, A. (2003). Inattentional blindness: Looking without seeing. Current Directions in Psychological Science, 12, 180–184.

    Article  Google Scholar 

  • Mack, A., & Rock, I. (1998). Inattentional blindness. Cambridge, MA: MIT Press.

    Book  Google Scholar 

  • Mackworth, N. H. (1965). Visual noise causes tunnel vision. Psychonomic Science, 3, 67–68.

    Article  Google Scholar 

  • Macuga, K. L., Beall, A. C., Kelly, J. W., Smith, R. S., & Loomis, J. M. (2007). Changing lanes: Inertial cues and explicit path information facilitate steering performance when visual feedback is removed. Experimental Brain Research, 178(2), 141–150.

    Google Scholar 

  • Maltz, M., & Shinar, D. (1999). Eye movements of younger and older drivers. Human Factors, 41, 15–25.

    Article  PubMed  Google Scholar 

  • Marquart, G., Cabrall, C., & de Winter, J. (2015). Review of eye-related measures of drivers’ mental workload. Procedia Manufacturing, 3, 2854–2861.

    Article  Google Scholar 

  • Marshall, S. P. (2007). Identifying cognitive state from eye metrics. Aviation, Space and Environmental Medicine, 78, 165–175.

    Google Scholar 

  • Martens, M. H., & Fox, M. (2007). Does road familiarity change eye fixations? A comparison between watching a video and real driving. Transportation Research Part F: Traffic Psychology and Behaviour, 10, 33–47.

    Article  Google Scholar 

  • Mattes, S. (2003). The lane-change-task as a tool for driver distraction evaluation. In H. Strasser, K. Kluth, H. Rausch, & H. Bubb (Eds.), Quality of work and products in enterprises of the future (pp. 57–60). Stuttgart, Germany: Ergonomia.

    Google Scholar 

  • McQueen, R. A., & Knussen, C. (2006). Introduction to research methods and statistics in psychology. Harlow, United Kingdom: Pearson.

    Google Scholar 

  • Mele, M. L., & Federici, S. (2012). Gaze and eye-tracking solutions for psychological research. Cognitive Processing, 13, 261–265.

    Article  Google Scholar 

  • Metz, B., Schömig, N., & Krüger, H. (2011). Attention during visual secondary tasks in driving: Adaptation to the demands of the driving task. Transportation Research Part F: Traffic Psychology and Behaviour, 14, 369–380.

    Article  Google Scholar 

  • Michon, J. A. (1985). A critical review of driver behaviour models: What do we know? What should we do? In L. A. Evans & R. C. Schwieg (Eds.), Human behaviour and traffic safety (pp. 487–525). New York, NY: Plenum Press.

    Google Scholar 

  • Milicic, N. (2010). Sichere und ergonomische Nutzung von Head-Up Displays im Fahrzeug (Doctoral dissertation). Technische Universität München, Munich, Germany.

    Google Scholar 

  • Mourant, R. R., & Rockwell, T. H. (1972). Strategies of visual search by novice and experienced drivers. Human Factors, 14, 325–335.

    Article  PubMed  Google Scholar 

  • Muttard, J. W., Peck, L. R., Guderian, S., Bartlett, W., Ton, L. P., Kauderer, C., et al. (2011). Glancing and stopping behavior of motorcyclists and car drivers at intersections. Transportation Research Record: Journal of the Transportation Research Board, 2265, 81–88.

    Article  Google Scholar 

  • Navarro, J., Mars, F., & Young, M. S. (2011). Lateral control assistance in car driving: Classification, review and future prospects. IET Intelligent Transport Systems, 5, 207–220.

    Article  Google Scholar 

  • Neisser, U. (1976). Cognition and reality. San Francisco, CA: W. H. Freeman.

    Google Scholar 

  • Norman, D. A., & Shallice, T. (1986). Attention to action: Willed and automatic control of behavior. In R. J. Davidson, G. E. Schwartz, & D. Shapiro (Eds.), Consciousness and self-regulation (pp. 1–18). New York, NY: Plenum Press.

    Google Scholar 

  • Olsen, E. C. B., Lee, S. E., & Wierwille, W. W. (2005). Eye glance behaviour during lane changes and straight-ahead driving. Transportation Research Record: Journal of the Transportation Research Board, 1937, 44–50.

    Google Scholar 

  • Petzold, T. (2011). Theoretical and methodological issues in driver distraction (Doctoral dissertation). Technische Universität Chemnitz, Chemnitz, Germany.

    Google Scholar 

  • Petzold, T., Brüggemann, S., & Krems, J. F. (2014). Learning effects in the lane change task (LCT)—Realistic secondary tasks and transfer of learning. Applied Ergonomics, 45, 639–646.

    Article  Google Scholar 

  • Petzoldt, T., Weiß, T., Franke, T., Krems, J. F., & Bannert, M. (2013). Can driver education be improved by computer based training of cognitive skills? Accident Analysis and Prevention, 50, 1185–1192.

    Article  PubMed  Google Scholar 

  • Platten, F. (2013). Analysis of mental workload and operating behaviour in secondary tasks while driving (Doctoral dissertation). Technische Universität Chemnitz, Chemnitz, Germany.

    Google Scholar 

  • Platten, F., Schwalm, M., Hülsmann, J., & Krems, J. F. (2014). Analysis of compensative behaviour in demanding driving situations. Transportation Research Part F: Traffic Psychology and Behaviour, 26, 38–48.

    Article  Google Scholar 

  • Poole, A., & Ball, L. J. (2006). Eye tracking in HCI and usability research. In C. Ghaoui (Ed.), Encyclopedia of human computer interaction (pp. 211–219). Hershey, PA: Idea Group Reference.

    Chapter  Google Scholar 

  • Rauh, N., Franke, T., & Krems, J. F. (2015). Understanding the impact of electric vehicle driving experience on range anxiety. Human Factors, 57, 177–187.

    Article  PubMed  Google Scholar 

  • Rayner, K. (2009). Eye movements and attention in reading, scene perception, and visual search. The Quarterly Journal of Experimental Psychology, 62, 1457–1506.

    Article  PubMed  Google Scholar 

  • Recarte, M. A., & Nunes, L. M. (2000). Effects of verbal and spatial-imagery tasks on eye fixations while driving. Journal of Experimental Psychology: Applied, 6, 31–43.

    PubMed  Google Scholar 

  • Recarte, M. A., & Nunes, L. M. (2003). Mental workload while driving: Effects on visual search, discrimination, and decision making. Journal of Experimental Psychology: Applied, 9, 119–137.

    PubMed  Google Scholar 

  • Recarte, M. A., & Nunes, L. M. (2009). Driver distractions. In C. Castro (Ed.), Human factors of visual and cognitive performance in driving (pp. 75–88). Boca Raton, FL: CRC Press.

    Google Scholar 

  • Reimer, B., Mehler, B., Wang, Y., & Coughlin, J. 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.

    Article  PubMed  Google Scholar 

  • Robertshaw, K. D., & Wilkie, R. M. (2008). Does gaze influence steering around a bend? Journal of Vision, 8(4), 1–13.

    Article  PubMed  Google Scholar 

  • Rockwell, T. H. (1972). Skills, judgment and information acquisition in driving. In T. W. Forbes (Ed.), Human factors in highway traffic safety research (pp. 133–164). New York, NY: Wiley.

    Google Scholar 

  • Romoser, M. R. E., Pollatsek, A., Fisher, D. L., & Williams, C. C. (2013). Comparing the glance patterns of older versus younger experienced drivers: Scanning for hazards while approaching and entering the intersection. Transportation Research Part F: Traffic Psychology and Behaviour, 16, 104–116.

    Article  Google Scholar 

  • Rousseau, R., Tremblay, S., & Breton, R. (2005). Defining and modeling situation awareness: A critical review. In S. Banbury & S. Tremblay (Eds.), A cognitive approach to situation awareness: Theory and application (pp. 3–21). Burlington, United Kingdom: Ashgate.

    Google Scholar 

  • Salvucci, D. D. (2006). Modeling driver behaviour in a cognitive architecture. Human Factors, 48, 362–380.

    Article  PubMed  Google Scholar 

  • Salvucci, D. D., & Gray, R. (2004). A two-point visual control model of steering. Perception, 33, 1233–1248.

    Article  PubMed  Google Scholar 

  • Salvucci, D. D., & Liu, A. (2002). The time course of a lane change: Driver control and eye-movement behaviour. Transportation Research Part F: Traffic Psychology and Behaviour, 5, 123–132.

    Article  Google Scholar 

  • Salvucci, D. D., Liu, A., & Boer, E. R. (2001, August). Control and monitoring during lane changes. Paper presented at the Vision in Vehicles IX, Brisbane, Australia.

    Google Scholar 

  • Schinka, J. A., & Velicer, W. F. (2003). Handbook of psychology, Vol. 2: Research methods in psychology. Hoboken, NJ: Wiley.

    Google Scholar 

  • Schleicher, R., Galley, N., Briest, S., & Galley, L. (2008). Blinks and saccades as indicators of fatigue in sleepiness warnings: Looking tired? Ergonomics, 51, 982–1010.

    Article  PubMed  Google Scholar 

  • Scholz, A., Mehlhorn, M., & Krems, J. F. (2016). Listen up, eye movements play a role in verbal memory retrieval. Psychological Research, 80, 149–158.

    Article  PubMed  Google Scholar 

  • Schwalm, M., Keinath, A., & Zimmer, H. (2008). Pupillometry as a method for measuring mental workload within a simulated driving task. In D. de Waard, F. O. Flemisch, B. Lorenz, H. Oberheid, & K. A. Brookhuis (Eds.), Human factors for assistance and automation (pp. 75–88). Maastricht, Netherlands: Shaker Publishing.

    Google Scholar 

  • Sen, B., Smith, J. D., & Najm, W. G. (2003). Analysis of lane change crashes (Report No. DOT-VNTSC-NHTSA-02-03). Cambridge, MA: U.S. Department of Transportation, Research and Special Programs Administration.

    Google Scholar 

  • Senders, J. W. (1964). The human operator as a monitor and controller of multidegree of freedom systems. IEEE Transaction on Human Factors in Electronics, HFE-5, 2–5.

    Article  Google Scholar 

  • Shepard, M., Findlay, J. M., & Hockey, R. J. (1986). The relationship between eye movements and spatial attention. The Quarterly Journal of Experimental Psychology Section A: Human Experimental Psychology, 38, 475–491.

    Article  Google Scholar 

  • Shinar, D. (2008). Looks are (almost) everything: Where drivers look to get information. Human Factors, 50, 380–384.

    Article  PubMed  Google Scholar 

  • Shinar, D., McDowell, E. D., & Rockwell, T. H. (1977). Eye movements in curve negotiation. Human Factors, 19, 63–71.

    Article  PubMed  Google Scholar 

  • Simons, D. J. (2000). Attentional capture and inattentional blindness. Trends in Cognitive Sciences, 4, 147–155.

    Article  PubMed  Google Scholar 

  • Simons, D. J., & Chabris, C. F. (1999). Gorillas in our midst: Sustained inattentional blindness for dynamic events. Perception, 28, 1059–1074.

    Article  Google Scholar 

  • Simons-Morton, B. G., Guo, F., Klauer, S. G., Ehsani, J. P., & Pradhan, A. K. (2014). Keep your eyes on the road: Young driver crash risk increases according to duration of distraction. Journal of Adolescent Health, 54, S61–S67.

    Article  PubMed  Google Scholar 

  • Sivak, M. (1996). The information that drivers use: Is it indeed 90% visual? Perception, 25, 1081–1089.

    Article  PubMed  Google Scholar 

  • Strayer, D. L., Drews, F. A., & Johnston, W. A. (2003). Cell phone-induced failures of visual attention during simulated driving. Journal of Experimental Psychology: Applied, 9, 23–32.

    PubMed  Google Scholar 

  • Summala, H., Nieminen, T., & Punto, M. (1996). Maintaining lane position with peripheral vision during in-vehicle tasks. Human Factors, 38, 442–451.

    Article  Google Scholar 

  • Sweller, J., Ayres, P., & Kalyuga, S. (2011). Cognitive load theory. New York, NY: Springer.

    Book  Google Scholar 

  • Theeuwes, J., Belopolsky, A., & Olivers, C. N. L. (2009). Interactions between working memory, attention and eye movements. Acta Psychologica, 132, 106–114.

    Article  PubMed  Google Scholar 

  • Tijerina, L., Garrott, W. R., Stoltzfus, D., & Parmer, E. (2005). Eye glance behaviour of van and passenger car drivers during lane change decision phase. Transportation Research Record: Journal of the Transportation Research Board, 1937, 37–43.

    Article  Google Scholar 

  • Treat, J. R. (1980). A study of precrash factors involved in traffic accidents. HSRI Research Review, 10, 1–35.

    Google Scholar 

  • Underwood, G. (Ed.). (1998). Eye guidance in reading and scene perception. Oxford, United Kingdom: Elsevier.

    Google Scholar 

  • Underwood, G. (2007). Visual attention and the transition from novice to advanced driver. Ergonomics, 50, 1235–1249.

    Article  PubMed  Google Scholar 

  • Underwood, G., Chapman, P., Brocklehurst, N., Underwood, J., & Crundall, D. (2003). Visual attention while driving: Sequences of eye fixations made by experienced and novice drivers. Ergonomics, 46, 629–646.

    Article  PubMed  Google Scholar 

  • Underwood, G., Phelps, N., Wright, C., van Loon, E., & Galpin, A. (2005). Eye fixation scanpaths of younger and older drivers in a hazard perception task. Ophthalmic and Physiological Optics, 25, 346–356.

    Article  PubMed  Google Scholar 

  • Victor, T. W., Harbluk, J. L., & Engström, J. A. (2005). Sensitivity of eye-movement measures to in-vehicle task difficulty. Transportation Research Part F: Traffic Psychology and Behaviour, 8, 167–190.

    Article  Google Scholar 

  • Vollrath, M., & Krems, J. F. (2011). Verkehrspsychologie. Ein Lehrbuch für Psychologen, Ingenieure und Informatiker. Stuttgart, Germany: Kohlhammer.

    Google Scholar 

  • Vollrath, M., & Schießl, C. (2004). Belastung und Beanspruchung im Fahrzeug—Anforderungen an Fahrerassistenzsysteme. In VDI (Ed.), Integrierte Sicherheit und Fahrerassistenzsysteme (pp. 343–360). Düsseldorf, Germany: VDI.

    Google Scholar 

  • Wade, N. J., & Tatler, B. W. (2011). Origins and applications of eye movement research. In S. P. Liversedge, I. D. Gilchrist, & S. Everling (Eds.), The Oxford handbook of eye movements (pp. 17–44). Oxford, United Kingdom: Oxford University Press.

    Google Scholar 

  • Wang, Y., Reimer, B., Dobres, J., & Mehler, B. (2014). The sensitivity of different methodologies for characterizing drivers’ gaze concentration under increased cognitive demand. Transportation Research Part F: Traffic Psychology and Behaviour, 26, 227–237.

    Article  Google Scholar 

  • Warren, W. H., Morris, M. W., & Kalish, M. (1988). Perception of translational heading from optical flow. Journal of Experimental Psychology: Human Perception and Performance, 14, 646–660.

    PubMed  Google Scholar 

  • Wickens, C. D. (2002). Multiple resources and performance predictions. Theoretical Issues in Ergonomic Science, 3, 159–177.

    Article  Google Scholar 

  • Wickens, C. D., & McCarley, J. S. (2007). Applied attention theory. CRC Press. https://www.crcpress.com/Applied-Attention-Theory/Wickens-McCarley/p/book/9781420063363.

  • Wickens, C. D., Goh, J., Helleberg, J., Horrey, W., & Talleur, D. A. (2003). Attentional models of multi-task pilot performance using advanced display technology. Human Factors, 45, 360–380.

    Article  PubMed  Google Scholar 

  • Wierwille, W. W. (1993). Visual and manual demands of in-car controls and displays. In J. B. Peacock & W. Karwowski (Eds.), Automotive ergonomics: Human factors in the design and use of the automobile (pp. 299–320). London, United Kingdom: Taylor & Francis.

    Google Scholar 

  • Wikman, A., Nieminen, T., & Summala, H. (1998). Driving experience and time-sharing during in-car tasks on roads of different width. Ergonomics, 41, 358–372.

    Article  Google Scholar 

  • Wikman, A., & Summala, H. (2005). Aging and time-sharing in highway driving. Optometry and Vision Science, 82, 716–723.

    Article  PubMed  Google Scholar 

  • Wilkie, R. M., & Wann, J. P. (2003). Eye-movements aid the control of locomotion. Journal of Vision, 3, 677–684.

    Article  PubMed  Google Scholar 

  • Wittmann, M., Kiss, M., Gugg, P., Steffen, A., Fink, M., Pöppel, E., & Kamiya, H. (2006). Effects of display position of a visual in-vehicle task on simulated driving. Applied Ergonomics, 37, 198–199.

    Google Scholar 

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Acknowledgements

The authors would like to thank Esko Lehtonen and Mark Vollrath for valuable comments on a previous version of this chapter.

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Rosner, A., Franke, T., Platten, F., Attig, C. (2019). Eye Movements in Vehicle Control. In: Klein, C., Ettinger, U. (eds) Eye Movement Research. Studies in Neuroscience, Psychology and Behavioral Economics. Springer, Cham. https://doi.org/10.1007/978-3-030-20085-5_22

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