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Electroencephalography Shows Effects of Age in Response to Oddball Auditory Signals: Implications for Semi-autonomous Vehicle Alerting Systems for Older Drivers

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HCI in Mobility, Transport, and Automotive Systems (HCII 2021)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 12791))

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Abstract

This research considers the efficacy of auditory alert systems in semi-autonomous vehicles (SAVs) from the perspective of the neurological processing of multi-modal information. While SAVs are growing in popularity, there is much to be discovered concerning driver safety. Understanding how the brain integrates multi-modal information is essential to determining the efficacy of auditory alerting systems in SAVs and whether or not they suffice as a method for conveying information to drivers. Investigating how younger and older groups process various types of auditory information while engaged in visuospatial tasks of different workload levels is a crucial step to take to optimize safety in SAVs. We report on how auditory processing of deviant and standard tones was impacted by age at decision-making areas of the brain using electroencephalography (EEG). EEG and behavioural data from 10 participants, five older (57–78) and five younger (18–26) were analyzed. Participants completed four rounds of a match-to-sample visuospatial task while paired tones (using an oddball protocol) were delivered through headphones. Regardless of age, deviant tones resulted in greater P200 components, which highlights the importance of auditory alert systems implementing novel alert sounds for emergencies, such as handover tasks. Results also showed that neural responses to salient auditory tones in the second position were attenuated in older adults in difficult conditions of a visuospatial task. Thus, the effects of age and visuospatial workload level on auditory processing are critical to consider, given that features related to SAVs, such as alerting systems, are still being developed.

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References

  1. Knoefel, F., Wallace, B., Goubran, R., Sabra, I., Marshall, S.: Semi-autonomous vehicles as a cognitive assistive device for older adults. Geriatr. 4, 63 (2019)

    Article  Google Scholar 

  2. Morando, A., Gershon, P., Mehler, B., Reimer, B.: Driver-initiated Tesla autopilot disengagements in naturalistic driving. In: 12th International Conference on Automotive User Interfaces and Interactive Vehicular Applications (2020)

    Google Scholar 

  3. Jamson, A., Merat, N., Carsten, O., Lai, F.: Behavioural changes in drivers experiencing highly-automated vehicle control in varying traffic conditions. Transp. Res. Part C Emerg. Technologies. 30, 116–125 (2013)

    Article  Google Scholar 

  4. Jin, L., Guo, B., Jiang, Y., Wang, F., Xie, X., Gao, M.: Study on the impact degrees of several driving behaviors when driving while performing secondary tasks. IEEE Access 6, 65772–65782 (2018)

    Article  Google Scholar 

  5. 3016A: Taxonomy and Definitions for Terms Related to Driving Automation Systems for On-Road Motor Vehicles - SAE International. https://www.sae.org/standards/content/j3016_201609/

  6. Banks, V., Eriksson, A., O’Donoghue, J., Stanton, N.: Is partially automated driving a bad idea? Observations from an on-road study. Appl. Ergon. 68, 138–145 (2018)

    Article  Google Scholar 

  7. McCall, R., et al.: A taxonomy of autonomous vehicle handover situations. Transp. Res. Part A Policy Pract. 124, 507–522 (2019)

    Article  Google Scholar 

  8. Lv, C., et al.: Analysis of autopilot disengagements occurring during autonomous vehicle testing. IEEE/CAA J. Automatica Sinica 5, 58–68 (2018)

    Article  Google Scholar 

  9. Carsten, O., Lai, F., Barnard, Y., Jamson, A., Merat, N.: Control task substitution in semiautomated driving. Hum. Factors J. Hum. Factors Ergon. Soc. 54, 747–761 (2012)

    Article  Google Scholar 

  10. Disengagement Reports - California DMV. https://www.dmv.ca.gov/portal/vehicle-industry-services/autonomous-vehicles/disengagement-reports/

  11. Wogalter, M., Conzola, V., Smith-Jackson, T.: Research-based guidelines for warning design and evaluation. Appl. Ergon. 33, 219–230 (2002)

    Article  Google Scholar 

  12. Nees, M., Helbein, B., Porter, A.: Speech auditory alerts promote memory for alerted events in a video-simulated self-driving car ride. Hum. Factors J. Hum. Factors Ergon. Soc. 58, 416–426 (2016)

    Article  Google Scholar 

  13. Harrison, M.: Interior noise: assessment and control. Veh. Refin., 145–233 (2004)

    Google Scholar 

  14. Au, K.: Advances in Knitting Technology. Elsevier (2011)

    Google Scholar 

  15. Lin, C., et al.: Assessing effectiveness of various auditory warning signals in maintaining drivers’ attention in virtual reality-based driving environments. Percept. Mot. Skills 108, 825–835 (2009)

    Article  Google Scholar 

  16. Wiese, E., Lee, J.: Auditory alerts for in-vehicle information systems: the effects of temporal conflict and sound parameters on driver attitudes and performance. Ergonomics 47, 965–986 (2004)

    Article  Google Scholar 

  17. Nagaraj, N., Kennett, S., Levisee, M., Atcherson, S.: Overview of central auditory processing deficits in older adults. Semin. Hear. 36, 150–161 (2015)

    Article  Google Scholar 

  18. Marshall, D., Chrysler, S., Smith, K.: Older drivers’ acceptance of in-vehicle systems and the effect it has on safety. https://trid.trb.org/view/1331080

  19. Baldwin, C., May, J., Parasuraman, R.: Auditory forward collision warnings reduce crashes associated with task-induced fatigue in young and older drivers. Int. J. Hum. Factors Ergon. 3, 107 (2014)

    Article  Google Scholar 

  20. Norman, D., Bobrow, D.: On data-limited and resource-limited processes. Cogn. Psychol. 7, 44–64 (1975)

    Article  Google Scholar 

  21. Ullsperger, P., Freude, G., Erdmann, U.: Auditory probe sensitivity to mental workload changes – an event-related potential study. Int. J. Psychophysiol. 40, 201–209 (2001)

    Article  Google Scholar 

  22. Pavarini, S., et al.: On the use of the P300 as a tool for cognitive processing assessment in healthy aging: A review. Dement. Neuropsychol. 12(1), 1–11 (2018)

    Article  Google Scholar 

  23. Boutros, N., Korzyukov, O., Jansen, B., Feingold, A., Bell, M.: Sensory gating deficits during the mid-latency phase of information processing in medicated schizophrenia patients. Psychiatry Res. 126, 203–215 (2004)

    Article  Google Scholar 

  24. Gmehlin, D., Kreisel, S., Bachmann, S., Weisbrod, M., Thomas, C.: Age effects on preattentive and early attentive auditory processing of redundant stimuli: is sensory gating affected by physiological aging? J. Gerontol. A Biol. Sci. Med. Sci. 66A, 1043–1053 (2011)

    Article  Google Scholar 

  25. Delorme, A., Makeig, S.: EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis. J. Neurosci. Meth. 134(1), 9–21 (2004). https://doi.org/10.1016/j.jneumeth.2003.10.009

    Article  Google Scholar 

  26. HydroCel Geodesic Sensor Net. https://www.egi.com/images/stories/manuals/Printed%20IFUs%20with%20New%20Notified%20Body/HC_GSN_channel_map_128_8403486-54_20181207.pdf

  27. Turabian, M., Van Benthem, K., Herdman, C.M.: Impairments in early auditory detection coincide with substandard visual-spatial task performance in older age: an ERP study. In: Stephanidis, C., Antona, M., Ntoa, S. (eds.) HCII 2020. CCIS, vol. 1294, pp. 110–118. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-60703-6_14

    Chapter  Google Scholar 

  28. Hoffmann, U., Vesin, J., Ebrahimi, T., Diserens, K.: An efficient P300-based brain–computer interface for disabled subjects. J. Neurosci. Meth. 167, 115–125 (2008)

    Article  Google Scholar 

  29. van der Heiden, R., Iqbal, S., Janssen, C.: Priming drivers before handover in semi-autonomous cars. In: Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems (2017)

    Google Scholar 

  30. Reuter-Lorenz, P., Cappell, K.: Neurocognitive aging and the compensation hypothesis. Curr. Dir. Psychol. Sci. 17, 177–182 (2008)

    Article  Google Scholar 

  31. Jones, L., Hills, P., Dick, K., Jones, S., Bright, P.: Cognitive mechanisms associated with auditory sensory gating. Brain Cogn. 102, 33–45 (2016)

    Article  Google Scholar 

  32. Zabelina, D., O’Leary, D., Pornpattananangkul, N., Nusslock, R., Beeman, M.: Creativity and sensory gating indexed by the P50: selective versus leaky sensory gating in divergent thinkers and creative achievers. Neuropsychologia 69, 77–84 (2015)

    Article  Google Scholar 

  33. Javitt, D., Freedman, R.: Sensory processing dysfunction in the personal experience and neuronal machinery of Schizophrenia. Am. J. Psychiatry 172, 17–31 (2015)

    Article  Google Scholar 

  34. Nees, M., Walker, B.: Auditory displays for in-vehicle technologies. Rev. Hum. Factors Ergon. 7, 58–99 (2011)

    Article  Google Scholar 

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Authors and Affiliations

  1. Carleton University, Ottawa, ON, K1S 5B6, Canada

    Melanie Turabian, Kathleen Van Benthem & Chris M. Herdman

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  1. Melanie Turabian
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  2. Kathleen Van Benthem
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  3. Chris M. Herdman
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Correspondence to Melanie Turabian .

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Editors and Affiliations

  1. Technische Universität Ilmenau, Ilmenau, Germany

    Heidi Krömker

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Turabian, M., Van Benthem, K., Herdman, C.M. (2021). Electroencephalography Shows Effects of Age in Response to Oddball Auditory Signals: Implications for Semi-autonomous Vehicle Alerting Systems for Older Drivers. In: Krömker, H. (eds) HCI in Mobility, Transport, and Automotive Systems. HCII 2021. Lecture Notes in Computer Science(), vol 12791. Springer, Cham. https://doi.org/10.1007/978-3-030-78358-7_38

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  • DOI: https://doi.org/10.1007/978-3-030-78358-7_38

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  • Publisher Name: Springer, Cham

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  • Online ISBN: 978-3-030-78358-7

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