skip to main content
10.1145/3239092.3239094acmconferencesArticle/Chapter ViewAbstractPublication PagesautomotiveuiConference Proceedingsconference-collections
research-article

Workshop on The Mobile Office

Published:23 September 2018Publication History

ABSTRACT

This workshop discusses the balance between safety and productivity as automated vehicles turn into 'mobile offices': spaces where non-driving activities are performed during one's daily commute. Technological developments reduce the active role of the human driver that might, nonetheless, require occasional intervention. To what extent are drivers allowed to dedicate resources to non-driving work-related activities? To address this critical question, the workshop brings together a diverse community of researchers and practitioners that are interested in questions as follows: what non-driving activities are likely to be performed on one's way to work and back; what is a useful taxonomy of these tasks; how can various tasks be studied in experimental settings; and, what are the criteria to assess human performance in automated vehicles. To foster further dialogue, the outcome of the workshop will be an online blog where attendees can contribute their own thoughts: https://medium.com/the-mobile-office.

References

  1. Paul Atchley, & Mark Chan. 2011. Potential Benefits and Costs of Concurrent Task Engagement to Maintain Vigilance: A Driving Simulator Investigation. Human Factors, 53(1), 3--12.Google ScholarGoogle ScholarCross RefCross Ref
  2. Chuang, L. L., Glatz, C., & Krupenia, S. 2017. Using EEG to understand why behavior to auditory in-vehicle notifications differs across test environments. In Proceedings of the 9th International Conference on Automotive User Interfaces and Interactive Vehicular Applications, 123--133. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. Thomas A. Dingus, Feng Guo, Suzie Lee, Jonathan F. Antin, Miguel Perez, Mindy Buchanan-King, & Jonathan Hankey. 2016. Driver crash risk factors and prevalence evaluation using naturalistic driving data. Proceedings of the National Academy of Sciences, 201513271.Google ScholarGoogle ScholarCross RefCross Ref
  4. Anna Feldhütter, Christian Gold, Sonja Schneider, & Klaus Bengler. 2017. How the duration of automated driving influences take-over performance and gaze behavior, Advances in Ergonomic Design of Systems, Products and Processes. Springer, Berlin, Heidelberg, 2017. 309--318.Google ScholarGoogle Scholar
  5. Tom M. Gasser & Daniel Westhof. 2012. BASt-study: Definitions of Automation and Legal Issues in Germany (Tech. Rep.). Federal Highway Research Institute (BASt).Google ScholarGoogle Scholar
  6. Glatz, C., Krupenia, S. S., Bülthoff, H. H., & Chuang, L. L. (2018, April). Use the Right Sound for the Right Job: Verbal Commands and Auditory Icons for a Task-Management System Favor Different Information Processes in the Brain. In Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems, 472, 1--13. Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. Christian P. Janssen, Linda Ng Boyle, Andrew L. Kun, Wendy Ju, & Lewis Chuang. accepted 2018. A Hidden Markov Framework to Capture Human-Machine Interaction in Automated Vehicles. International Journal of Human Computer Interaction.Google ScholarGoogle Scholar
  8. Christian P. Janssen, Sandy J. Gould, Simon Y.W. Li, Duncan P. Brumby, & Anna L. Cox. 2015. Integrating knowledge of multitasking and Interruptions across different Perspectives and research methods. International Journal of Human-Computer Studies, 79, 1--5. Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. Christian P. Janssen, Shamsi T. Iqbal, Andrew L. Kun, Stella F. Donker. Submitted. Interrupted by my car? Implications of interruption and interleaving research for automated vehicles. Submitted for publication.Google ScholarGoogle Scholar
  10. Sheila G. Klauer, Feng Guo, Bruce G. Simons-Morton, Marie C. Ouimet, Suzanne E. Lee, & Thomas A. Dingus. 2014. Distracted Driving and Risk of Road Crashes among Novice and Experienced Drivers. New England Journal of Medicine, 370(1), 54--59.Google ScholarGoogle ScholarCross RefCross Ref
  11. Andrew L. Kun, Susanne Boll, & Albrecht Schmidt. 2016. Shifting gears: User interfaces in the age of autonomous driving. IEEE Pervasive Computing, 15(1), 32--38. Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. Natasha Merat, A. Hamish Jamson, Frank C. H. Lai, & Oliver Carsten, (2012). Highly automated driving, secondary task performance, and driver state. Human Factors, 54(5), 762--771.Google ScholarGoogle ScholarCross RefCross Ref
  13. SAE International. 2014. J3016: Taxonomy and Definitions for Terms Related to On-Road Motor Vehicle Automated Driving Systems.Google ScholarGoogle Scholar
  14. Shadan Sadeghian Borojeni, Lewis L. Chuang, Wilko Heuten, & Susanne C.J. Boll (2016) Assisting drivers with ambient take-over requests in highly automated driving. In Proceedings of the 8th International Conference on Automotive User Interfaces and Interactive Vehicular Applications, 237--244. Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. Shadan Sadeghian Borojeni, Susanne C.J. Boll, Wilko Heuten, Heinrich H. Bülthoff HH, & Lewis Chuang (2018) Feel the Movement: Real Motion Influences Responses to Take-over Requests in Highly Automated Vehicles, CHI Conference on Human Factors in Computing Systems (CHI '18), ACM Press, New York, NY, USA, 246, 1--13. Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. Remo M.A. van der Heiden, Shamsi T. Iqbal, and Christian P. Janssen. 2017. Priming Drivers before Handover in Semi-Autonomous Cars. In Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems (CHI '17). ACM, New York, NY, USA, 392--404. Google ScholarGoogle ScholarDigital LibraryDigital Library
  17. Christopher D. Wickens. (1980). The structure of attentional resources. In R. Nickerson (Ed.), Attention and performance VIII (pp. 239--257). Hillsdale, NJ: ErlbaumGoogle ScholarGoogle Scholar
  18. Christopher D. Wickens. (2002). Multiple resources and performance prediction. Theoretical Issues in Ergonomics Science, 3(2), 159--177.Google ScholarGoogle ScholarCross RefCross Ref
  19. Christopher D. Wickens. (2008). Multiple Resources and Mental Workload. Human Factors, 50(3), 449--455.Google ScholarGoogle ScholarCross RefCross Ref
  20. Joost de Winter, Riender Happee, Marieke H. Martens, & Neville A. Stanton. 2014. Effects of adaptive cruise control and highly automated driving on workload and situation awareness: A review of the empirical evidence. Transportation Research Part F: Traffic Psychology and Behaviour, 27, 196--217.Google ScholarGoogle ScholarCross RefCross Ref

Index Terms

  1. Workshop on The Mobile Office

      Recommendations

      Comments

      Login options

      Check if you have access through your login credentials or your institution to get full access on this article.

      Sign in

      PDF Format

      View or Download as a PDF file.

      PDF

      eReader

      View online with eReader.

      eReader