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Route Guidance Modality for Elder Driver Navigation

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Pervasive Computing (Pervasive 2012)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 7319))

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Abstract

Differences in perceptual and cognitive abilities between the young and elderly have implications for in-car tasks. As a primary example, although in-car navigation systems enhance situational awareness, this comes at the cost of increasing visual distraction and cognitive load. To address these shortcomings, this paper explores the efficacy of multi-modal cues for providing route guidance information. We present the results of a study evaluating the impact of multi-modal feedback on driving performance and cognitive load. We found that the full combination of visual, auditory, and haptic feedback was generally most useful to reduce way-finding errors. However, our study highlighted a number of differences between elder and younger drivers for their safer navigation. Adding more modalities strained the already high workload of elder drivers. In contrast, adding haptic feedback to traditional audio and visual feedback led to more attentive driving by younger drivers. Therefore, for elder drivers, navigation systems need to be personalized to enhance the benefit of auditory feedback without increasing the number of sensory feedbacks. For younger drivers, it is necessary to incorporate new non-visual feedback to minimize distractions caused by visual feedback. We demonstrate these results through task performance-based measures, subjective workload measures and through objective workload measures that use psychophysiological responses of participants to predict a driver’s cognitive load in near real-time.

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Author information

Authors and Affiliations

  1. Human-Computer Interaction Institute, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, 15213, USA

    SeungJun Kim, Jin-Hyuk Hong, Jodi Forlizzi & Anind K. Dey

  2. AT & T Research, Labs, Florham Park, NJ, 07932, USA

    Kevin A. Li

Authors
  1. SeungJun Kim
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  2. Jin-Hyuk Hong
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  3. Kevin A. Li
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  4. Jodi Forlizzi
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  5. Anind K. Dey
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Editor information

Editors and Affiliations

  1. School of Information Technologies, University of Sydney, Australia

    Judy Kay

  2. DFKI GmbH, Embedded Intelligence, Trippstadter Straße 122, 67663, Kaiserslautern, Germany

    Paul Lukowicz

  3. Faculty of Environment and Information Studies, Keio University, 5322, Endo, 252-8520, Fujisawa City, Kanagawa, Japan

    Hideyuki Tokuda

  4. School of Computing Science, Newcastle University, UK

    Patrick Olivier

  5. DFKI GmbH, Stuhlsatzenhausweg 3, 66123, Saarbrücken, Germany

    Antonio Krüger

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© 2012 Springer-Verlag Berlin Heidelberg

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Kim, S., Hong, JH., Li, K.A., Forlizzi, J., Dey, A.K. (2012). Route Guidance Modality for Elder Driver Navigation. In: Kay, J., Lukowicz, P., Tokuda, H., Olivier, P., Krüger, A. (eds) Pervasive Computing. Pervasive 2012. Lecture Notes in Computer Science, vol 7319. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31205-2_12

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  • DOI: https://doi.org/10.1007/978-3-642-31205-2_12

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-31204-5

  • Online ISBN: 978-3-642-31205-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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