research-article

Workshop on The Mobile Office

Authors:

Lewis L. Chuang,

Stella F. Donker,

Christian P. JanssenAuthors Info & Claims

AutomotiveUI '18: Adjunct Proceedings of the 10th International Conference on Automotive User Interfaces and Interactive Vehicular Applications

Pages 10 - 16

https://doi.org/10.1145/3239092.3239094

Published: 23 September 2018 Publication 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.

[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.

Digital 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.

[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.

[5]

Tom M. Gasser & Daniel Westhof. 2012. BASt-study: Definitions of Automation and Legal Issues in Germany (Tech. Rep.). Federal Highway Research Institute (BASt).

[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.

Digital 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.

[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.

Digital 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.

[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.

[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.

Digital 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.

[13]

SAE International. 2014. J3016: Taxonomy and Definitions for Terms Related to On-Road Motor Vehicle Automated Driving Systems.

[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.

Digital 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.

Digital 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.

Digital Library

[17]

Christopher D. Wickens. (1980). The structure of attentional resources. In R. Nickerson (Ed.), Attention and performance VIII (pp. 239--257). Hillsdale, NJ: Erlbaum

[18]

Christopher D. Wickens. (2002). Multiple resources and performance prediction. Theoretical Issues in Ergonomics Science, 3(2), 159--177.

[19]

Christopher D. Wickens. (2008). Multiple Resources and Mental Workload. Human Factors, 50(3), 449--455.

[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.

Cited By

Pan LYu CHe ZShi Y(2023)A Human-Computer Collaborative Editing Tool for Conceptual DiagramsProceedings of the 2023 CHI Conference on Human Factors in Computing Systems10.1145/3544548.3580676(1-29)Online publication date: 19-Apr-2023
https://dl.acm.org/doi/10.1145/3544548.3580676
Schartmüller CRiener A(2022)Multimodal Error Correction for Speech-to-Text in a Mobile Office Automated Vehicle: Results From a Remote StudyProceedings of the 27th International Conference on Intelligent User Interfaces10.1145/3490099.3511131(496-505)Online publication date: 22-Mar-2022
https://dl.acm.org/doi/10.1145/3490099.3511131
Weigl KSteinhauser MRiener A(2022)Gender and age differences in the anticipated acceptance of automated vehicles: insights from a questionnaire study and potential for applicationGender, Technology and Development10.1080/09718524.2022.213789327:1(88-108)Online publication date: 19-Dec-2022
https://doi.org/10.1080/09718524.2022.2137893
Show More Cited By

Index Terms

Workshop on The Mobile Office
1. Human-centered computing
  1. Human computer interaction (HCI)
    1. HCI design and evaluation methods
      1. Usability testing
      2. User models

Recommendations

Are automated vehicles safer than manually driven cars?
Abstract
Are automated vehicles really safer than manually driven vehicles? If so, how would we know? Answering this question has spurred a contentious debate. Unfortunately, several issues make answering this question difficult for the foreseeable future. ...
Feeling-of-Safety Slider: Measuring Pedestrian Willingness to Cross Roads in Field Interactions with Vehicles
CHI EA '19: Extended Abstracts of the 2019 CHI Conference on Human Factors in Computing Systems

Can interactions between automated vehicles and pedestrians be evaluated in a quantifiable and standardized way? In order to answer this, we designed an input device in the form of a continuous slider that enables pedestrians to indicate their ...
Exploring the concept of the (future) mobile office
AutomotiveUI '19: Proceedings of the 11th International Conference on Automotive User Interfaces and Interactive Vehicular Applications: Adjunct Proceedings

This video shows a concept of a future mobile office in a semi-automated vehicle that uses augmented reality. People perform non-driving tasks in current, non-automated vehicles even though that is unsafe. Moreover, even for passengers there is limited ...

Comments

Information & Contributors

Information

Published In

cover image ACM Conferences

AutomotiveUI '18: Adjunct Proceedings of the 10th International Conference on Automotive User Interfaces and Interactive Vehicular Applications

September 2018

282 pages

ISBN:9781450359474

DOI:10.1145/3239092

Copyright © 2018 Owner/Author.

This work is licensed under a Creative Commons Attribution International 4.0 License.

Sponsors

SIGCHI: ACM Special Interest Group on Computer-Human Interaction

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 23 September 2018

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article
Research
Refereed limited

Funding Sources

Conference

AutomotiveUI '18

Sponsor:

SIGCHI

AutomotiveUI '18: 10th International Conference on Automotive User Interfaces and Interactive Vehicular Applications

September 23 - 25, 2018

ON, Toronto, Canada

Acceptance Rates

Overall Acceptance Rate 248 of 566 submissions, 44%

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

17
Total Citations
View Citations
197
Total Downloads

Downloads (Last 12 months)11
Downloads (Last 6 weeks)0

Reflects downloads up to 25 Dec 2024

Other Metrics

View Author Metrics

Citations

Cited By

Pan LYu CHe ZShi Y(2023)A Human-Computer Collaborative Editing Tool for Conceptual DiagramsProceedings of the 2023 CHI Conference on Human Factors in Computing Systems10.1145/3544548.3580676(1-29)Online publication date: 19-Apr-2023
https://dl.acm.org/doi/10.1145/3544548.3580676
Schartmüller CRiener A(2022)Multimodal Error Correction for Speech-to-Text in a Mobile Office Automated Vehicle: Results From a Remote StudyProceedings of the 27th International Conference on Intelligent User Interfaces10.1145/3490099.3511131(496-505)Online publication date: 22-Mar-2022
https://dl.acm.org/doi/10.1145/3490099.3511131
Weigl KSteinhauser MRiener A(2022)Gender and age differences in the anticipated acceptance of automated vehicles: insights from a questionnaire study and potential for applicationGender, Technology and Development10.1080/09718524.2022.213789327:1(88-108)Online publication date: 19-Dec-2022
https://doi.org/10.1080/09718524.2022.2137893
Weigl KSchartmüller CRiener A(2022)Development of the Questionnaire on Non-Driving Related Tasks (QNDRT) in automated driving: revealing age and gender differencesBehaviour & Information Technology10.1080/0144929X.2022.207347342:9(1374-1388)Online publication date: 14-May-2022
https://doi.org/10.1080/0144929X.2022.2073473
Teodorovicz TKun ASadun RShaer O(2022)Multitasking while drivingInternational Journal of Human-Computer Studies10.1016/j.ijhcs.2022.102789162:COnline publication date: 16-May-2022
https://dl.acm.org/doi/10.1016/j.ijhcs.2022.102789
Schartmüller CWeigl KLöcken AWintersberger PSteinhauser MRiener A(2021)Displays for Productive Non-Driving Related Tasks: Visual Behavior and Its Impact in Conditionally Automated DrivingMultimodal Technologies and Interaction10.3390/mti50400215:4(21)Online publication date: 18-Apr-2021
https://doi.org/10.3390/mti5040021
Kuen JSchartmüller CWintersberger P(2021)The TOR Agent:Optimizing Driver Take-Over with Reinforcement Learning13th International Conference on Automotive User Interfaces and Interactive Vehicular Applications10.1145/3473682.3480262(47-52)Online publication date: 9-Sep-2021
https://dl.acm.org/doi/10.1145/3473682.3480262
Fröhlich PSchartmüller CWintersberger PRiener AKun ABrewster SShaer OBaldauf M(2021)AutoWork 2021: Workshop on the Future of Work and Well-Being with Automated Vehicles13th International Conference on Automotive User Interfaces and Interactive Vehicular Applications10.1145/3473682.3477437(164-166)Online publication date: 9-Sep-2021
https://dl.acm.org/doi/10.1145/3473682.3477437
Dai KTan ZDuan Q(2021)Design of the Resumption and Prompt Interface for Online Meetings Under Automatic DrivingAdvances in Usability, User Experience, Wearable and Assistive Technology10.1007/978-3-030-80091-8_82(692-699)Online publication date: 8-Jul-2021
https://doi.org/10.1007/978-3-030-80091-8_82
Schartmüller CWintersberger PRiener AKun ABrewster SShaer O(2020)AutoWork 2020: Second Workshop on the Future of Work and Well-Being in Automated Vehicles12th International Conference on Automotive User Interfaces and Interactive Vehicular Applications10.1145/3409251.3411738(113-116)Online publication date: 21-Sep-2020
https://dl.acm.org/doi/10.1145/3409251.3411738
Show More Cited By

View Options

Login options

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

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Media

Figures

Other

Tables

View Table of Contents