View in EDS HTML Full Text PDF Full Text

Multitasking While Driving: How Drivers Self-Regulate Their Interaction with In-Vehicle Touchscreens in Automated Driving.

Saved in:
Bibliographic Details
Title: Multitasking While Driving: How Drivers Self-Regulate Their Interaction with In-Vehicle Touchscreens in Automated Driving.
Authors: Ebel, Patrick1 (AUTHOR), Lingenfelder, Christoph2 (AUTHOR), Vogelsang, Andreas1 (AUTHOR)
Source: International Journal of Human-Computer Interaction. Oct2023, Vol. 39 Issue 16, p3162-3179. 18p. 1 Color Photograph, 1 Diagram, 7 Charts, 8 Graphs.
Subjects: Automobile driving, In-vehicle computing, Motor vehicle driving, Driver assistance systems, Touch screens, Multilevel models, Systems development
Abstract: Driver assistance systems are designed to increase comfort and safety by automating parts of the driving task. At the same time, modern in-vehicle information systems with large touchscreens provide the driver with numerous options for entertainment, information, or communication, and are a potential source of distraction. However, little is known about how driving automation affects how drivers interact with the center stack touchscreen, i.e., how drivers self-regulate their behavior in response to different levels of driving automation. To investigate this, we apply multilevel models to a real-world driving dataset consisting of 31,378 sequences. Our results show significant differences in drivers' interaction and glance behavior in response to different levels of driving automation, vehicle speed, and road curvature. During automated driving, drivers perform more interactions per touchscreen sequence and increase the time spent looking at the center stack touchscreen. Specifically, at higher levels of driving automation (level 2), the mean glance duration toward the center stack touchscreen increases by 36% and the mean number of interactions per sequence increases by 17% compared to manual driving. Furthermore, partially automated driving has a strong impact on the use of more complex UI elements (e.g., maps) and touch gestures (e.g., multitouch). We also show that the effect of driving automation on drivers' self-regulation is greater than that of vehicle speed and road curvature. The derived knowledge can inform the design and evaluation of touch-based infotainment systems and the development of context-aware driver monitoring systems. [ABSTRACT FROM AUTHOR]
Copyright of International Journal of Human-Computer Interaction is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
Full text is not displayed to guests.
FullText Links:
  – Type: pdflink
Text:
  Availability: 1
Header DbId: egs
DbLabel: Engineering Source
An: 171338891
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Multitasking While Driving: How Drivers Self-Regulate Their Interaction with In-Vehicle Touchscreens in Automated Driving.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Ebel%2C+Patrick%22">Ebel, Patrick</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Lingenfelder%2C+Christoph%22">Lingenfelder, Christoph</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Vogelsang%2C+Andreas%22">Vogelsang, Andreas</searchLink><relatesTo>1</relatesTo> (AUTHOR)
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="JN" term="%22International+Journal+of+Human-Computer+Interaction%22">International Journal of Human-Computer Interaction</searchLink>. Oct2023, Vol. 39 Issue 16, p3162-3179. 18p. 1 Color Photograph, 1 Diagram, 7 Charts, 8 Graphs.
– Name: Subject
  Label: Subjects
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Automobile+driving%22">Automobile driving</searchLink><br /><searchLink fieldCode="DE" term="%22In-vehicle+computing%22">In-vehicle computing</searchLink><br /><searchLink fieldCode="DE" term="%22Motor+vehicle+driving%22">Motor vehicle driving</searchLink><br /><searchLink fieldCode="DE" term="%22Driver+assistance+systems%22">Driver assistance systems</searchLink><br /><searchLink fieldCode="DE" term="%22Touch+screens%22">Touch screens</searchLink><br /><searchLink fieldCode="DE" term="%22Multilevel+models%22">Multilevel models</searchLink><br /><searchLink fieldCode="DE" term="%22Systems+development%22">Systems development</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Driver assistance systems are designed to increase comfort and safety by automating parts of the driving task. At the same time, modern in-vehicle information systems with large touchscreens provide the driver with numerous options for entertainment, information, or communication, and are a potential source of distraction. However, little is known about how driving automation affects how drivers interact with the center stack touchscreen, i.e., how drivers self-regulate their behavior in response to different levels of driving automation. To investigate this, we apply multilevel models to a real-world driving dataset consisting of 31,378 sequences. Our results show significant differences in drivers' interaction and glance behavior in response to different levels of driving automation, vehicle speed, and road curvature. During automated driving, drivers perform more interactions per touchscreen sequence and increase the time spent looking at the center stack touchscreen. Specifically, at higher levels of driving automation (level 2), the mean glance duration toward the center stack touchscreen increases by 36% and the mean number of interactions per sequence increases by 17% compared to manual driving. Furthermore, partially automated driving has a strong impact on the use of more complex UI elements (e.g., maps) and touch gestures (e.g., multitouch). We also show that the effect of driving automation on drivers' self-regulation is greater than that of vehicle speed and road curvature. The derived knowledge can inform the design and evaluation of touch-based infotainment systems and the development of context-aware driver monitoring systems. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of International Journal of Human-Computer Interaction is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=171338891
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1080/10447318.2023.2215634
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 18
        StartPage: 3162
    Subjects:
      – SubjectFull: Automobile driving
        Type: general
      – SubjectFull: In-vehicle computing
        Type: general
      – SubjectFull: Motor vehicle driving
        Type: general
      – SubjectFull: Driver assistance systems
        Type: general
      – SubjectFull: Touch screens
        Type: general
      – SubjectFull: Multilevel models
        Type: general
      – SubjectFull: Systems development
        Type: general
    Titles:
      – TitleFull: Multitasking While Driving: How Drivers Self-Regulate Their Interaction with In-Vehicle Touchscreens in Automated Driving.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Ebel, Patrick
      – PersonEntity:
          Name:
            NameFull: Lingenfelder, Christoph
      – PersonEntity:
          Name:
            NameFull: Vogelsang, Andreas
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 10
              Text: Oct2023
              Type: published
              Y: 2023
          Identifiers:
            – Type: issn-print
              Value: 10447318
          Numbering:
            – Type: volume
              Value: 39
            – Type: issue
              Value: 16
          Titles:
            – TitleFull: International Journal of Human-Computer Interaction
              Type: main
ResultId 1