http://iet.metastore.ingenta.com
1887

Simulating the effect of cognitive load on braking responses in lead vehicle braking scenarios

Simulating the effect of cognitive load on braking responses in lead vehicle braking scenarios

For access to this article, please select a purchase option:

Buy article PDF
£12.50
(plus tax if applicable)
Buy Knowledge Pack
10 articles for £75.00
(plus taxes if applicable)

IET members benefit from discounts to all IET publications and free access to E&T Magazine. If you are an IET member, log in to your account and the discounts will automatically be applied.

Learn more about IET membership 

Recommend Title Publication to library

You must fill out fields marked with: *

Librarian details
Name:*
Email:*
Your details
Name:*
Email:*
Department:*
Why are you recommending this title?
Select reason:
 
 
 
 
 
IET Intelligent Transport Systems — Recommend this title to your library

Thank you

Your recommendation has been sent to your librarian.

The recently proposed cognitive control hypothesis suggests that the performance of cognitively loading but non-visual tasks such as cell phone conversation selectively impairs driving tasks that rely on top-down cognitive control while leaving automatised driving tasks unaffected. This idea is strongly supported by the existing experimental literature and the authors have previously outlined a conceptual model to account for the key underlying mechanisms. The present paper presents a mechanistically explicit account of the cognitive control hypothesis in terms of a computational simulation model. More specifically, it is shown how this model offers a straightforward explanation for why the effect of cognitive load on brake response time reported in the experimental lead vehicle (LV) braking studies depends strongly on scenario kinematics, more specifically the initial time headway. It is demonstrated that this relatively simple model can be fitted to empirical data obtained from an existing meta-analysis on existing LV braking studies.

References

    1. 1)
      • 1. Engström, J.: ‘Understanding attention selection in driving: from limited capacity to adaptive behaviour’. PhD thesis, Chalmers University, Sweden, 2011.
    2. 2)
      • 2. Engström, J., Markkula, G., Victor, T., et al: ‘Effects of cognitive load on driving performance: the cognitive control hypothesis’, Hum. Factors, 2017, 59, (5), pp. 734764.
    3. 3)
      • 3. Bruyas, M.P., Dumont, L.: ‘Sensitivity of detection response task (DRT) to the driving demand and task difficulty’. Proc. Seventh Int. Driving Symp. on Human Factors in Driver Assessment, Training, and Vehicle Design, Lake George, NY, 2013, pp. 6470.
    4. 4)
      • 4. Harbluk, J.L., Burns, P.C., Hernandez, S., et al: ‘Detection response tasks: using remote, headmounted and tactile signals to assess cognitive demand while driving’. Proc. Seventh Int. Driving Symp. on Human Factors in Driver Assessment, Training, and Vehicle Design, Lake George, NY, 2013, pp. 7884.
    5. 5)
      • 5. Engström, J., Larsson, P., Larsson, C.: ‘Comparison of static and driving simulator venues for the tactile detection response task’. Proc. Seventh Int. Driving Symp. on Human Factors in Driver Assessment, Training, and Vehicle Design, Lake George, NY, 2013..
    6. 6)
      • 6. ISO: ‘Road vehicles – transport information and control systems – detection response task (DRT) for assessing attentional effects of cognitive load in driving. International Standard, ISO 17488’, 2015.
    7. 7)
      • 7. Merat, N., Jamson, A.H.: ‘The effect of stimulus modality on signal detection: implications for assessing the safety of in-vehicle technology’, Hum. Factors, 2008, 50, (1), pp. 145158.
    8. 8)
      • 8. Patten, C., Kircher, A., Östlund, J., et al: ‘Using mobile telephones: cognitive workload and attention resource allocation’, Accident Anal. Prev., 2003, 36, (3), pp. 341350.
    9. 9)
      • 9. Alm, H., Nilsson, L.: ‘The effects of a mobile telephone task on driver behaviour in a car following situation’, Accident Anal. Prev., 1995, 27, pp. 707715.
    10. 10)
      • 10. Bergen, B., Medeiros-Ward, N., Wheeler, K., et al: ‘The crosstalk hypothesis: language interferes with driving because of modality-specific mental simulation’, J. Exp. Psychol. Gen., 2014, 142, pp. 119130.
    11. 11)
      • 11. Brookhuis, K.A., de Vries, G., Waard, D.: ‘The effects of mobile telephoning on driving performance’, Accident Anal. Prev., 1991, 23, (4), pp. 309316.
    12. 12)
      • 12. Engström, J., Ljung Aust, M., Viström, M.: ‘Effects of working memory load and repeated scenario exposure on emergency braking performance’, Hum. Factors, 2010, 52, (5), pp. 551559.
    13. 13)
      • 13. Lee, J.D., Caven, B., Haake, S., et al: ‘Speech-based interaction with in-vehicle computers: The effect of speech-based e-mail on drivers’ attention to the roadway’, Hum. Factors, 2001, 43, pp. 631640.
    14. 14)
      • 14. Levy, J., Pashler, H., Boer, E.: ‘Central interference in driving - is there any stopping the psychological refractory period?Psychol. Sci., 2006, 17, (3), pp. 228235.
    15. 15)
      • 15. Salvucci, D.D., Beltowska, J.: ‘Effects of memory rehearsal on driver performance: experiment and theoretical account’, Hum. Factors, 2008, 50, pp. 834844.
    16. 16)
      • 16. Strayer, D.L., Drews, F.A., Johnston, W.A.: ‘Cell phone induced failures of visual attention during simulated driving’, J. Exp. Psychol., Appl., 2003, 9, pp. 2352.
    17. 17)
      • 17. Strayer, D.L., Drews, F.A.: ‘Profiles in driver distraction: effects of cell phone conversations on younger and older drivers’, Hum. Factors, 2004, 46, pp. 640649.
    18. 18)
      • 18. Strayer, D.L., Drews, F.A., Crouch, D.J.: ‘A comparison of the cell phone driver and the drunk driver’, Hum. Factors, 2006, 48, (2), pp. 381391.
    19. 19)
      • 19. Sonnleitner, A., Treder, M.S., Simon, M., et al: ‘EEG alpha spindles and prolonged brake reaction times during auditory distraction in an on-road driving study’, Accident Anal. Prev., 2014, 62, pp. 110118.
    20. 20)
      • 20. Muttart, J.W., Fisher, D.L., Knodler, M., et al: ‘Driving without a clue: evaluation of driver simulator performance during hands-free cell phone operation in a work zone’, Transp. Res. Rec., J. Transp. Res. Board, 2007, 2018, pp. 914.
    21. 21)
      • 21. Baumann, M.R.K., Petzoldt, T., Hogema, J., et al: ‘The effect of cognitive tasks on predicting events in traffic’. Proc. European Conf. on Human Centred Design for Intelligent Transport Systems, Lyon, France, 2008, pp. 311.
    22. 22)
      • 22. Mantzke, O., Keinath, A.: ‘Relating the detection response task to critical events-consequences of high cognitive workload to brake reaction times’, Procedia Manuf., 2015, 3, pp. 23812386.
    23. 23)
      • 23. Shiffrin, R.M., Schneider, W.: ‘Controlled and automatic human information processing: II. Perceptual learning, automatic attending, and a general theory. Psychol. Rev., 1977, 84, pp. 127190.
    24. 24)
      • 24. Franconeri, S.L., Simons, D.J.: ‘Moving and looming stimuli capture attention’, Percept. Psychophys., 2003, 65, (7), pp. 9991010.
    25. 25)
      • 25. Náñez, J.: ‘Perception of impending collision in 3-to 6-week-old human infants’, Infant Behav. Dev., 1988, 11, (4), pp. 447463.
    26. 26)
      • 26. Schiff, W., Caviness, J.A., Gibson, J.J.: ‘‘Persistent fear responses in rhesus monkeys to the optical stimulus of ‘looming’’, Science, 1962, 136, (3520), pp. 982983.
    27. 27)
      • 27. Markkula, G., Engström, J., Lodin, J., et al: ‘A farewell to brake reaction times? Kinematics-dependent brake response in naturalistic rear-end emergencies’, Accident Anal. Prev., 2016, 95, pp. 209226.
    28. 28)
      • 28. Medeiros-Ward, N., Cooper, J.M., Strayer, D.L.: ‘Hierarchical control and driving’, J. Exp. Psychol. Gen., 2014, 143, (3), pp. 953958.
    29. 29)
      • 29. Lewis-Evans, B., de Waard, D., Brookhuis, K.A.: ‘Speed maintenance under cognitive load – implications for theories of driver behaviour’, Accident Anal. Prev., 2011, 43, pp. 14971507.
    30. 30)
      • 30. Recarte, M.A., Nuñes, L.M.: ‘Mental load and loss of control over speed in real driving. Towards a theory of attentional speed control’, Transp. Res., 2002, 5, pp. 111122.
    31. 31)
      • 31. Cooper, P.J., Zheng, Y., Richard, C., et al: ‘The impact of hands-free message reception/response on driving task performance’, Accident Anal. Prev., 2003, 35, pp. 2335.
    32. 32)
      • 32. Engström, J., Victor, T., Markkula., : ‘Attention selection and multitasking in everyday driving: A conceptual model’, in Regan, M. A, Victor, T.W., Lee, J.D. (Eds.) Driver distraction and inattention: advances in research and countermeasures (Farnham: Ashgate, 2013), pp. 2754.
    33. 33)
      • 33. Botvinick, M.M., Cohen, J.D.: ‘The computational and neural basis of cognitive control: charted territory and new frontiers’, Cogn. Sci., 2014, 38, pp. 12491285.
    34. 34)
      • 34. Cohen, J.D., Dunbar, K., McClelland, J.L.: ‘On the control of automatic processes: a parallel distributed processing account of the Stroop effect’, Psychol. Rev., 1990, 97, pp. 332361.
    35. 35)
      • 35. Feng, S.F., Schwemmer, M., Gershman, S.J., et al: ‘Multitasking vs. multiplexing: toward a normative account of limitations in the simultaneous execution of control-demanding behaviors’, Cogn. Affect. Behav. Neurosci., 2014, 14, pp. 129146.
    36. 36)
      • 36. Miller, E.K., Cohen, J.D.: ‘An integrative theory of prefrontal cortex function’, Annu. Rev. Neurosci., 2001, 24, pp. 167202.
    37. 37)
      • 37. Schumacher, E.H., Seymour, T.L., Glass, J.M., et al: ‘Virtually perfect time sharing in dual-task performance: uncorking the central cognitive bottleneck’, Psychol. Sci., 2001, 12, pp. 101108.
    38. 38)
      • 38. Engström, J., Markkula, G., Merat, N.: ‘Modeling the effect of cognitive load on driver reactions to a braking lead vehicle: a computational account of the cognitive control hypothesis’. Paper presented at the 5th Int. Conf. of Driver Distraction and Inattention, Paris, France, 2017.
    39. 39)
      • 39. Engström, J.: ‘Scenario criticality determines the effects of working memory load on brake response time’. Proc. European Conf. on Human Centred Design for Intelligent Transport Systems, Lyon, France, 2010, pp. 2536.
    40. 40)
      • 40. Markkula, G.Modeling driver control behavior in both routine and near-accident driving’, Proc. Hum. Factors Ergon. Soc. Annu. Meet., 2014, 58, (1), pp. 879883.
    41. 41)
      • 41. Markkula, G., Boer, E.R., Romano, R., et al: Sustained sensorimotor control as intermittent decisions about prediction errors: Computational framework and application to ground vehicle steering. Biological Cybernetics (in press).
    42. 42)
      • 42. Ratcliff, R., Tuerlinckx, F.: ‘Estimating parameters of the diffusion model: approaches to dealing with contaminant reaction times and parameter variability’, Psychon. Bull. Rev., 2002, 9, (3), pp. 438481.
    43. 43)
      • 43. Ratcliff, R., Strayer, D.L.: ‘Modeling simple driving tasks with a one-boundary diffusion model’, Psychon. Bull. Rev., 2014, 21, (3), pp. 577589.
    44. 44)
      • 44. Cooper, J.M., Strayer, D.L.: ‘Effects of simulator practice and real-world experience on cell-phone related driver distraction’, Hum. Factors, 2008, 50, pp. 893902.
    45. 45)
      • 45. Tillman, G., Strayer, D.L., Eidels, A., et al: ‘Modeling cognitive load effects of conversation between a passenger and driver’, Attention Percep. Psychophys., 2017, 79, (6), pp. 17951803Open Science Framework.
    46. 46)
      • 46. Markkula, E., Engström, J.: ‘Simulating effects of arousal on lane keeping: Are drowsiness and cognitive load opposite ends of a single spectrum?Paper presented at the10th Int. Conf. on Managing Fatigue, San Diego, CA, 2017.
http://iet.metastore.ingenta.com/content/journals/10.1049/iet-its.2017.0233
Loading

Related content

content/journals/10.1049/iet-its.2017.0233
pub_keyword,iet_inspecKeyword,pub_concept
6
6
Loading
This is a required field
Please enter a valid email address