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Multiple-object tracking while driving: the multiple-vehicle tracking task

Attention, Perception, & Psychophysics volume 76, pages 2326–2345 (2014)Cite this article

Abstract

Many contend that driving an automobile involves multiple-object tracking. At this point, no one has tested this idea, and it is unclear how multiple-object tracking would coordinate with the other activities involved in driving. To address some of the initial and most basic questions about multiple-object tracking while driving, we modified the tracking task for use in a driving simulator, creating the multiple-vehicle tracking task. In Experiment 1, we employed a dual-task methodology to determine whether there was interference between tracking and driving. Findings suggest that although it is possible to track multiple vehicles while driving, driving reduces tracking performance, and tracking compromises headway and lane position maintenance while driving. Modified change-detection paradigms were used to assess whether there were change localization advantages for tracked targets in multiple-vehicle tracking. When changes occurred during a blanking interval, drivers were more accurate (Experiment 2a) and ~250 ms faster (Experiment 2b) at locating the vehicle that changed when it was a target rather than a distractor in tracking. In a more realistic driving task where drivers had to brake in response to the sudden onset of brake lights in one of the lead vehicles, drivers were more accurate at localizing the vehicle that braked if it was a tracking target, although there was no advantage in terms of braking response time. Overall, results suggest that multiple-object tracking is possible while driving and perhaps even advantageous in some situations, but further research is required to determine whether multiple-object tracking is actually used in day-to-day driving.

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References

  • Bahrami, B. (2003). Object property encoding and change blindness in multiple object tracking. Visual Cognition, 10(8), 949–963.

    Article  Google Scholar 

  • Ball, K., Edwards, J. D., & Ross, L. A. (2007). The impact of speed of processing training on cognitive and everyday functions. The Journals of Gerontology. Series B, Psychological Sciences and Social Sciences, 62(1), 19–31.

    PubMed  Article  Google Scholar 

  • Bowers, A. R., Anastasio, R. J., Sheldon, S. S., O’Connor, M. G., Hollis, A. M., Howe, P. D., & Horowitz, T. D. (2013). Can we improve clinical prediction of at-risk older drivers? Accident Analysis and Prevention, 59(1), 537–547.

    PubMed Central  PubMed  Article  Google Scholar 

  • Chang, S., Lin, C., Hsu, C., Fung, C., & Hwang, J. (2009). The effect of a collision warning system on the driving performance of young drivers at intersections. Transportation Research Part F, 12, 371–380.

    Article  Google Scholar 

  • Chen, H., Cao, L., & Logan, D. B. (2011). Investigation into the effect of an intersection crash warning system on driving performance in a simulator. Traffic Injury Prevention, 12, 529–537.

    PubMed  Article  Google Scholar 

  • Chen, W., Howe, P. D., & Holcombe, A. O. (2013). Resource demands of object tracking and differential allocation of the resource. Attention, Perception, & Psychophysics, 75(4), 710–725.

    Article  Google Scholar 

  • Clabaux, N., Brenac, T., & Perrin, C. (2012). Motorcyclists’ speed and the “looked-but-failed-to-see” accidents. Accident Analysis and Prevention, 49, 73–77.

    PubMed  Article  Google Scholar 

  • Cohen, M., Pinto, Y., Howe, P., & Horowitz, T. (2011). The what-where tradeoff in multiple-identity tracking. Attention, Perception, & Psychophysics, 73(5), 1422–1434.

    Article  Google Scholar 

  • Cole, G. G., Kentridge, R. W., Gellatly, A. R. H., & Heywood, C. A. (2003). Detectability of onsets versus offsets in the change detection paradigm. Journal of Vision, 3, 22–31.

    PubMed  Article  Google Scholar 

  • Culham, J. C., Cavanagh, P., & Kanwisher, N. G. (2001). Attention response functions: Characterizing brain areas using fMRI activation during parametric variation in attentional load. Neuron, 32(4), 737–745.

    PubMed  Article  Google Scholar 

  • Dotzauer, M., Caljouw, S. R., de Waard, D., & Brouwer, W. H. (2013). Intersection assistance: A safe solution for older drivers? Accident Analysis and Prevention, 59, 522–528.

    PubMed  Article  Google Scholar 

  • Drew, T., Horowitz, T. S., & Vogel, E. K. (2013). Swapping versus dropping? Electrophysiological measures of difficulty in multiple-object tracking. Cognition, 126(2), 213–223.

    PubMed Central  PubMed  Article  Google Scholar 

  • Dukic, T., & Broberg, T. (2012). Older drivers’ visual search behaviour at intersections. Transportation Research Part F, 15, 462–470.

    Article  Google Scholar 

  • Eck, R. W., & Winn, G. (2002). Older-driver perception of problems at unsignalized intersections and divided highways. Transportation Research Record, 1818, 70–77.

    Article  Google Scholar 

  • Faul, F., Erdfelder, E., Lang, A., & Buchner, A. (2007). G*Power3: A flexible statistical power analysis program for the social, behavioural, and biomedical sciences. Behaviour Research Methods, 39(2), 175–191.

    Article  Google Scholar 

  • Fehd, H. M., & Seiffert, A. E. (2010). Looking at the centre of the targets helps multiple-object tracking. Journal of Vision, 10(4), 19.1. doi:10.1167/10.4.19. 13.

    Article  Google Scholar 

  • Fencsik, D. E., Klieger, S. B., & Horowitz, T. S. (2007). The role of location and motion information in the tracking and recovery of moving objects. Perception & Psychophysics, 69(4), 567–577.

    Article  Google Scholar 

  • Feria, C. S. (2008). The distribution of attention within objects in multiple-object scenes: Prioritization by spatial probabilities and a center bias. Perception & Psychophysics, 70(7), 1185–1196.

    Article  Google Scholar 

  • Franconeri, S. L., Lin, J. Y., Pylyshyn, Z. W., Fisher, B., & Enns, J. T. (2008). Evidence a speed limit in multiple-object tracking. Psychonomic Bulletin and Review, 15(4), 802–808.

    PubMed  Article  Google Scholar 

  • Hardiess, G., Hansmann-Roth, S., & Mallot, H. A. (2013). Gaze movements and spatial working memory in collision avoidance: A traffic intersection task. Frontiers in Behavioural Neuroscience, 7(62), 1–13. doi:10.3389/fnbeh.2013.00062

    Google Scholar 

  • Hauer, E. (1988). The safety of older persons at intersections: Special Report 218. Transportation in an Aging Society, 2, pp. 194–252. National Research Council, Washington, D.C.

  • Henderson, S., Gagnon, S., Collin, C., Tabone, R., & Stinchcombe, A. (2013). Near peripheral motion contrast threshold predicts older drivers’ simulator performance. Accident Analysis and Prevention, 50, 103–109.

    PubMed  Article  Google Scholar 

  • Higgins, K. E., Wood, J., & Tait, A. (1998). Vision and driving: Selective effect of optical blur on different driving tasks. Human Factors, 40(2), 224–232.

    PubMed  Article  Google Scholar 

  • Horowitz, T. S., Birnkrant, R. S., Fencsik, D. E., Tran, L., & Wolfe, J. M. (2006). How do we track invisible objects? Psychonomic Bulletin & Review, 13(3), 516–523.

    Article  Google Scholar 

  • Horowitz, T. S., Klieger, S. B., Fencsik, D. E., Yang, K. K., Alvarez, G. A., & Wolfe, J. M. (2007). Tracking unique objects. Perception & Psychophysics, 69(2), 172–184.

    Article  Google Scholar 

  • Howe, P. D., Horowitz, T. S., Morocz, I. A., Wolfe, J., & Livingstone, M. S. (2009). Using fMRI to distinguish components of the multiple object tracking task. Journal of Vision, 9(4), 10.1–11. doi:10.1167/9.4.10

    PubMed Central  Article  Google Scholar 

  • Hulleman, J. (2005). The mathematics of multiple object tracking: From proportions correct to number of objects tracked. Vision Research, 45(17), 2298–2309.

    PubMed  Article  Google Scholar 

  • Isler, R., Parsonson, B., & Hansson, G. (1997). Age related effects of restricted head movements on the Useful Field of View of drivers. Accident Analysis and Prevention, 29(6), 793–801.

    PubMed  Article  Google Scholar 

  • Jovicich, J., Peters, R. J., Koch, C., Braun, J., Chang, L., & Ernst, T. (2001). Brain areas specific for attentional load in a motion-tracking task. Journal of Cognitive Neuroscience, 13(8), 1048–1058.

    PubMed  Article  Google Scholar 

  • Kennedy, R. S., Fowlkes, J. E., Berbaum, K. S., & Lilienthal, M. G. (1992). Use of a motion sickness history questionnaire for prediction of simulator sickness. Aviation, Space, & Environmental Medicine, 63(7), 588–593.

    Google Scholar 

  • Kunar, M., Carter, R., Cohen, M., & Horowitz, T. S. (2008). Telephone conversation impairs sustained visual attention via a central bottleneck. Psychonomic Bulletin and Review, 15(6), 1135–1140.

    PubMed Central  PubMed  Article  Google Scholar 

  • Ludwig, C. J. H., Ranson, A., & Gilchrist, I. D. (2008). Oculomotor capture by transient events: A comparison of abrupt onsets, offsets, motion, and flicker. Journal of Vision, 8(14), 11.1–16. doi:10.1167/8.14.11

    Article  Google Scholar 

  • Makovski, T., & Jiang, Y. V. (2009). The role of visual working memory in attentive tracking of unique objects. Journal of Experimental Psychology: Human Perception and Performance, 35(6), 1687–1697.

    PubMed Central  PubMed  Google Scholar 

  • Maltz, M., & Shinar, D. (1999). Eye movements of younger and older drivers. Human Factors, 41(1), 15–25.

    PubMed  Article  Google Scholar 

  • McGwin, G., & Brown, D. B. (1999). Characteristics of traffic crashes among young, middle aged, and older drivers. Accident Analysis and Prevention, 31(3), 181–198.

    PubMed  Article  Google Scholar 

  • Moussa, G., Radwan, E., & Hussain, K. (2012). Augmented reality vehicle system: Left-turn maneuver study. Transportation Research Part C, 21, 1–16.

    Article  Google Scholar 

  • Oksama, L., & Hyönä, J. (2004). Is multiple object tracking carried out automatically by an early vision mechanism independent of higher order cognition? An individual differences approach. Visual Cognition, 11(5), 631–671.

    Article  Google Scholar 

  • Oksama, L., & Hyönä, J. (2008). Dynamic binding of identity and location information: A serial model of multiple identity tracking. Cognitive Psychology, 56, 237–283.

    PubMed  Article  Google Scholar 

  • Owens, D. A., & Tyrrell, R. A. (1999). Effects of luminance, blur, and age on nighttime visual guidance: A test of the visual degradation hypothesis. Journal of Experimental Psychology: Applied, 5(2), 115–128.

    Google Scholar 

  • Owsley, C., & McGwin, G. (2010). Vision and driving. Vision Research, 50(23), 2348–2361.

    PubMed Central  PubMed  Article  Google Scholar 

  • Posner, M. I. (1980). Orienting of attention. Quarterly Journal of Psychology, 32, 3–25.

    Article  Google Scholar 

  • Preusser, D. F., Williams, A. F., Ferguson, S. A., Ulmer, R. G., & Weinstein, H. B. (1998). Fatal crash risk for older drivers at intersections. Accident Analysis and Prevention, 30(2), 151–159.

    PubMed  Article  Google Scholar 

  • Pylyshyn, Z. W. (1989). The role of location indexes in spatial perception: A sketch of the FINST spatial-index model. Cognition, 32(1), 65–97.

    PubMed  Article  Google Scholar 

  • Pylyshyn, Z. W. (2004). Some puzzling findings in multiple-object tracking: I. Tracking without keeping track of object identities. Visual Cognition, 11(7), 801–822.

    Article  Google Scholar 

  • Pylyshyn, Z. W. (2009). Perception, Representation, and the World: The FINST That Binds. In D. Dedrick & L. M. Trick (Eds.), Computation, cognition, and pylyshyn (pp. 3–48). Cambridge, MA: MIT Press.

    Google Scholar 

  • Pylyshyn, Z. W., Haladjian, H. H., King, C. E., & Reilly, J. E. (2008). Selective nontarget inhibition in multiple object tracking. Visual Cognition, 16(8), 1011–1021.

    Article  Google Scholar 

  • Pylyshyn, Z. W., & Storm, R. W. (1988). Tracking multiple independent targets: Evidence for a parallel tracking mechanism. Spatial Vision, 3(3), 179–198.

    PubMed  Article  Google Scholar 

  • Reed Jones, J. G., Trick, L. M., & Matthews, M. (2008). Testing assumptions implicit in the use of the 15-second rule as an early predictor of whether an in-vehicle device produces unacceptable distraction. Accident Analysis and Prevention, 40(2), 628–634.

    PubMed  Article  Google Scholar 

  • Rensink, R. A. (2002). Change detection. Annual Review of Psychology, 53(1), 245–277.

    PubMed  Article  Google Scholar 

  • Riecke, B. E. (2010). Compelling Self-Motion Through Virtual Environments Without Actual Self-Motion – Using Self-Motion Illusions ('Vection') to Improve VR User Experience, Virtual Reality, Prof. Jae-Jin Kim (Ed.), ISBN: 978-953-307-518-1, InTech, Available from: http://www.intechopen.com/books/virtual-reality/compellingself-motion-through-virtual-environments-without-actual-self-motion-using-self-motion-ill

  • 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, 16, 104–116.

    Article  Google Scholar 

  • Scholl, B. J. (2009). What have we learned about attention from multiple-object tracking (and vice versa)? In D. Dedrick & L. Trick (Eds.), Computation, cognition, and pylyshyn (pp. 49–77). Cambridge, MA, US: MIT Press.

    Google Scholar 

  • Scholl, B. J., Pylyshyn, Z. W., & Franconeri, S. L. (1999). When are featural and spatiotemporal properties encoded as a result of attentional allocation? Investigative Ophthalmology and Visual Science, 40(4), 797–797.

    Google Scholar 

  • Sears, C. R., & Pylyshyn, Z. W. (2000). Multiple-object tracking and attentional processing. Canadian Journal of Experimental Psychology, 54(1), 1–14.

    PubMed  Article  Google Scholar 

  • Simons, D. J. (1996). In sight, out of mind: when object representations fail. Psychological Science, 7(5), 301–305.

    Article  Google Scholar 

  • Skyving, M., Berg, H. Y., & Laflamme, L. (2009). A pattern analysis of traffic crashes fatal to older drivers. Accident Analysis and Prevention, 41, 253–258.

    PubMed  Article  Google Scholar 

  • Smiley, A., Reid, L., & Fraser, M. (1980). Changes in driver steering control with learning. Human Factors, 22(4), 401–415.

    Google Scholar 

  • Spence, I., & Feng, J. (2010). Video games and spatial cognition. Review of General Psychology, 14(2), 92–104.

    Article  Google Scholar 

  • Spotorno, S., Tatler, B. W., & Faure, S. (2013). Semantic consistency versus perceptual salience in visual scenes: Findings from change detection. Acta Psychologica, 142, 168–176.

    PubMed  Article  Google Scholar 

  • Staplin, L., Gish, K. W., & Wagner, E. K. (2003). MaryPODS revisited: Updated crash analysis and implications for screening program implementation. Journal of Safety Research, 34(4), 389–397.

    PubMed  Article  Google Scholar 

  • Störmer, V. S., Winther, G. N., Li, S., & Andersen, S. K. (2013). Sustained multifocal attentional enhancement of stimulus processing in early visual areas predicts tracking performance. Journal of Neuroscience, 33(12), 5346–5351.

    PubMed  Article  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(1), 23–32.

    PubMed  Google Scholar 

  • 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 and Prevention, 30(4), 401–407.

    PubMed  Article  Google Scholar 

  • Summala, H., Nieminen, T., & Punto, M. (1996). Maintaining lane position with peripheral vision during in-vehicle tasks. Human Factors, 38(3), 442–451.

    Article  Google Scholar 

  • Thomas, L. E., & Seiffert, A. E. (2010). Self-motion impairs multiple-object tracking. Cognition, 117(1), 80–86.

    PubMed  Article  Google Scholar 

  • Treat, J. R., Tumbas, N. S., McDonald, S. T., Shinar, D., Hume, R. D., Mayer, R. E., Stansifer, R. L., & Castellan, N. J. (1979). Tri-level study on the causes of traffic accidents: Final Report, Volumes I and II. U.S. DOT HS-805-086, (NTIS PB 80-121064).

  • Trick, L. M., Brandigampola, S., & Enns, J. T. (2012). How fleeting emotions affect hazard perception and steering while driving: The impact of image arousal and valence. Accident Analysis and Prevention, 45, 222–229.

    PubMed  Article  Google Scholar 

  • Trick, L. M., Enns, J. T., Mills, J., & Vavrik, J. (2004). Paying attention behind the wheel: A framework for studying the role of selective attention in driving. Theoretical Issues in Ergonomic Science, 5(5), 385–424.

    Article  Google Scholar 

  • Trick, L. M., Guindon, J., & Vallis, L. (2006). Sequential tapping interferes selectively with multiple-object tracking: Do finger-tapping and tracking share a common resource? Quarterly Journal of Experimental Psychology, 59(7), 1188–1195.

    Article  Google Scholar 

  • Trick, L., Hollinsworth, H., & Brodeur, D. (2009). Multiple-object tracking across the lifespan: Do different factors contribute to diminished performance in different age groups? In Don Dedrick and Lana Trick (Eds.) Computation, Cognition, and Pylyshyn. (pp. 79-99). MIT press.

  • Trick, L. M., Jaspers-Fayer, F., & Sethi, N. (2005). Multiple-object tracking in children: The “Catch the Spies” task. Cognitive Development, 20(3), 373–387.

    Article  Google Scholar 

  • Trick, L. M., Mutreja, R., & Hunt, K. (2012). Spatial and visuo-spatial working memory tests predict performance in classic multiple-object tracking in young adults but measures of the executive do not. Attention, Perception and Psychophysics, 74(2), 300–311.

    PubMed  Article  Google Scholar 

  • Trick, L. M., Perl, T., & Sethi, N. (2005). Age-related differences in multiple-object tracking. Journal of Gerontology: Series B: Psychological Sciences and Social Sciences, 60B(2), 102–105.

    Article  Google Scholar 

  • Trick, L. M., Toxopeus, R., & Wilson, D. (2010). The effects of visibility conditions, traffic density, and navigational challenge on speed compensation and driving performance in drivers of different ages. Accident Analysis and Prevention, 42, 1661–1671.

    PubMed  Article  Google Scholar 

  • Velichkovsky, B. M., Dornhoefer, S. M., Kopf, M., Helmert, J., & Joos, M. (2002). Change detection and occlusion modes in road-traffic scenarios. Transportation Research Part F: Traffic Psychology and Behaviour. Special Issue: Eye Movements, Visual Attention and Driving Behaviour, 5(2), 99–109.

    Article  Google Scholar 

  • Vlakveld, W., Romoser, M. R. E., Mehranian, H., Diete, F., Pollatsek, A., & Fisher, D. L. (2011). Do crashes and near crashes enhance novice drivers’ visual search for latent hazards? Transportation Research Record, 2265, 153–160.

    PubMed Central  PubMed  Article  Google Scholar 

  • White, C. B., & Caird, J. K. (2010). The blind date: The effects of change blindness, passenger conversation and gender on looked-but-failed-to-see (LBFTS) errors. Accident Analysis and Prevention, 42(6), 1822–1830.

    PubMed  Article  Google Scholar 

  • Wickens, C. D. (1984). Processing resources in attention. In R. Parasuraman & R. Davies (Eds.), Varieties of Attention (pp. 63–101). New York: Academic Press.

    Google Scholar 

  • Wickens, C. D. (2002). Multiple resources and performance prediction. Theoretical Issues in Ergonomics Science, 3(2), 159–177.

    Article  Google Scholar 

  • Yantis, S., & Jonides, J. (1984). Abrupt visual onsets and selective attention: Evidence from visual search. Journal of Experimental Psychology: Human Perception and Performance, 10(5), 601–621.

    PubMed  Google Scholar 

  • Zhang, H., Xuan, Y., Fu, X., & Pylyshyn, Z. W. (2010). Do objects in working memory compete with objects in perception? Visual Cognition, 18(4), 617–640.

    Article  Google Scholar 

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Acknowledgments

This research was funded through grants to the second author from Auto21: Network Centres of Excellence, the Natural Sciences and Engineering Research Council of Canada, the Canadian Foundation for Innovation, and the Ontario Innovation Trust. We would like to thank Ryan Toxopeus for his help in maintaining the driving simulator and proofreading earlier versions of the manuscript.

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  1. Computational Infomatics: Intelligent Sensing and Systems Lab, Commonwealth Scientific and Industrial Research Organization, Castray Esplanade, Hobart, Tasmania, 7001, Australia

    Martin J. Lochner

  2. Department of Psychology, University of Guelph, Guelph, Ontario, Canada, N1G 2 W1

    Lana M. Trick

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  1. Martin J. Lochner
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  2. Lana M. Trick
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Correspondence to Lana M. Trick.

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Lochner, M.J., Trick, L.M. Multiple-object tracking while driving: the multiple-vehicle tracking task. Atten Percept Psychophys 76, 2326–2345 (2014). https://doi.org/10.3758/s13414-014-0694-3

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  • DOI: https://doi.org/10.3758/s13414-014-0694-3

Keywords

  • Object-based attention
  • Perception and action
  • Dual-task performance
  • Driving
  • Multiple-object tracking