Nothing Special   »   [go: up one dir, main page]

skip to main content
10.1145/2971485.2971551acmotherconferencesArticle/Chapter ViewAbstractPublication PagesnordichiConference Proceedingsconference-collections
short-paper

To See or Not to See: The Effect of Object Recognition on Users' Trust in "Automated Vehicles"

Published: 23 October 2016 Publication History

Abstract

While automated vehicle technology progresses, potentially leading to a safer, more efficient traffic environment, many challenges remain within the area of human factors, such as user trust in Automated Driving (AD) vehicle systems. The authors previously focused on creating a guiding framework for implementing trust-related factors into the Human-Machine-Interaction (HMI) interface in automated vehicles. This paper presents the result of a first attempt to use the framework in the design process. Three concepts with different levels of system transparency were created to provide Object Recognition (OR) feedback, and subsequently user-tested in a level 3 (NHTSA) Wizard of Oz vehicle. Results indicate that presenting feedback through OR can increase the level of trust in the system, and that users prefer moderation -- neither too much nor too little feedback. The paper also demonstrates the framework's usefulness in guiding HMI designers in the trust-based development process with the help of a well-defined design-space.

References

[1]
Ajzen, I., and Fishbein, M. Understanding attitudes and predicting social behavior. Upper Saddle River, NJ: Prentice Hall, 1980.
[2]
Ekman, F., Johansson, M. and Sochor, J. Creating Appropriate Trust for Autonomous Vehicle Systems - A Framework for HMI Design. In Proc. 95th Annual Meeting of The Transportation Research Board. Washington D.C., (2016).
[3]
Helldin, T., Falkman, G., Riveiro, M. and Davidsson, S. Presenting system uncertainty in automotive UIs for supporting trust calibration in autonomous driving. In Proc. of the 5th International Conference on Automotive User Interfaces and Interactive Vehicular Applications (AutomotiveUI,13), Eindhoven, Netherlands, (2013).
[4]
Hoff, KA. and Bashir, M. Trust in Automation: integrating Empirical Evidence on Factors That Influence Trust. Human Factors: The Journal of the Human Factors and Ergonomics Society 50, 3 (2015), 407--434.
[5]
Lee, J.D. and See, KA. Trust in Automation: Designing for Appropriate Reliance. Human Factors 46, 1 (2004), 50--80.
[6]
Marinik, A., Bishop, R., Fitchett, V., Morgan, J.F., Trimble, T.E. and Blanco, M. Human Factors Evaluation of Level 2 And Level 3 Automated Driving Concepts: Concepts of Operation. Washington, DC: U.S Department of Transportation, National Highway Traffic Safety Administration. 2014.
[7]
Mcknight, H.D. and Chervany, N.L. What is Trust? A Conceptual Analysis and an Interdisciplinary Model. In Proc. AMCIS 2000 Paper 382, (2000), 1--8.
[8]
Muir, B.M. Trust between humans and machines, and the design of decision aids. International Journal Man-Machine Studies 27 (1987), 527--539.
[9]
Muir, B.M. Trust in automation: Part I. Theoretical issues in the study of trust and human intervention in automated systems. Ergonomics 37, 11 (1994), 1905--1922.
[10]
Muir, B.M. and Moray, N. Trust in automation. Part II. Experimental studis of trust and human intervention in a process control simulation. Ergonomics 39, 3 (1996), 429--460.
[11]
National Highway Traffic Safety Administration. U.S. Department of Transportation Releases Policy on Automated Vehicle Development, 2013. http://www.nhtsa.gov/About+NHTSA/Press+Releases/U.S.+Department+of+Transportation+Releases+Policy+on+Automated+Vehicle+Development
[12]
Parasuraman, R., Sheridan, T.B. and Wickens, C.D. Situation Awareness, Mental Workload, and Trust in Automation: Viable, Empirically Supported Cognitive Engineering Constructs. Journal of Cognitive Engineering and Decision Making 2, 2 (2008), 140--160.
[13]
Saffarian, M., De Winter, J. and Happee, R. Automated Driving: Human-factors issues and design solutions. Proceedings of the Human Factors and Ergonomics Society Annual Meeting 56, 1 (2012), 2296--2300
[14]
Stanton, N.A. and Young, M.S. A proposed psychological model of driving automation. Theoretical Issues in Ergonomical Sceince 1, 4 (2000), 315--331.
[15]
Toffetti, A., Wilschut, E.S., Martens, M.H., Schieben, A., Rambaldini, A., Merat, N. and Flemisch, F. CityMobil - Human Factor Issues Regarding Highly Automated Vehicles on eLane. Transportation Research Record: Journal of the Transportation Research Board 2110 (2009), 1--8.
[16]
Verberne, F., Ham, J. and Midden, C. Trust in Smart Systems: Sharing Driving Goals and Giving Information to Increase Trustworthiness and Acceptability of Smart Systems in Cars. Human Factors Oct., 54, 5 (2012), 799--810.

Cited By

View all
  • (2024)Towards a Conceptual Model of Users’ Expectations of an Autonomous In-Vehicle Multimodal ExperienceHuman Behavior and Emerging Technologies10.1155/2024/74185972024(1-14)Online publication date: 14-Mar-2024
  • (2024)TimelyTale: A Multimodal Dataset Approach to Assessing Passengers' Explanation Demands in Highly Automated VehiclesProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/36785448:3(1-60)Online publication date: 9-Sep-2024
  • (2024)A Review on the Development of the In-Vehicle Human-Machine Interfaces in Driving Automation: A Design PerspectiveProceedings of the 16th International Conference on Automotive User Interfaces and Interactive Vehicular Applications10.1145/3640792.3675718(160-174)Online publication date: 22-Sep-2024
  • Show More Cited By

Index Terms

  1. To See or Not to See: The Effect of Object Recognition on Users' Trust in "Automated Vehicles"

    Recommendations

    Comments

    Please enable JavaScript to view thecomments powered by Disqus.

    Information & Contributors

    Information

    Published In

    cover image ACM Other conferences
    NordiCHI '16: Proceedings of the 9th Nordic Conference on Human-Computer Interaction
    October 2016
    1045 pages
    ISBN:9781450347631
    DOI:10.1145/2971485
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

    In-Cooperation

    Publisher

    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 23 October 2016

    Permissions

    Request permissions for this article.

    Check for updates

    Author Tags

    1. Human-machine interaction(HMI)
    2. automated vehicles/systems
    3. framework
    4. object recognition
    5. trust
    6. user
    7. validation test

    Qualifiers

    • Short-paper
    • Research
    • Refereed limited

    Conference

    NordiCHI '16

    Acceptance Rates

    NordiCHI '16 Paper Acceptance Rate 58 of 231 submissions, 25%;
    Overall Acceptance Rate 379 of 1,572 submissions, 24%

    Contributors

    Other Metrics

    Bibliometrics & Citations

    Bibliometrics

    Article Metrics

    • Downloads (Last 12 months)33
    • Downloads (Last 6 weeks)3
    Reflects downloads up to 26 Nov 2024

    Other Metrics

    Citations

    Cited By

    View all
    • (2024)Towards a Conceptual Model of Users’ Expectations of an Autonomous In-Vehicle Multimodal ExperienceHuman Behavior and Emerging Technologies10.1155/2024/74185972024(1-14)Online publication date: 14-Mar-2024
    • (2024)TimelyTale: A Multimodal Dataset Approach to Assessing Passengers' Explanation Demands in Highly Automated VehiclesProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/36785448:3(1-60)Online publication date: 9-Sep-2024
    • (2024)A Review on the Development of the In-Vehicle Human-Machine Interfaces in Driving Automation: A Design PerspectiveProceedings of the 16th International Conference on Automotive User Interfaces and Interactive Vehicular Applications10.1145/3640792.3675718(160-174)Online publication date: 22-Sep-2024
    • (2023)Understanding trust calibration in automated driving: the effect of time, personality, and system warning designErgonomics10.1080/00140139.2023.219190766:12(2165-2181)Online publication date: 29-Mar-2023
    • (2023)Is my AV crashing? An online photo-based experiment assessing whether shared intended pathway can help AV drivers anticipate silent failuresErgonomics10.1080/00140139.2023.217655166:12(1984-1998)Online publication date: 11-Feb-2023
    • (2023)Interdependence theory in humans’ interaction with automated vehiclesInternational Journal of Human-Computer Studies10.1016/j.ijhcs.2023.103102179:COnline publication date: 1-Nov-2023
    • (2021)ExplAIn Yourself! Transparency for Positive UX in Autonomous DrivingProceedings of the 2021 CHI Conference on Human Factors in Computing Systems10.1145/3411764.3446647(1-12)Online publication date: 6-May-2021
    • (2021)Increasing the User Experience in Autonomous Driving through different Feedback ModalitiesProceedings of the 26th International Conference on Intelligent User Interfaces10.1145/3397481.3450687(7-10)Online publication date: 14-Apr-2021
    • (2020)Collaboration Around an Interactive Tabletop Map: Comparing Voice Interactions and a Tangible Shape-changing ControllerProceedings of the 19th International Conference on Mobile and Ubiquitous Multimedia10.1145/3428361.3428395(132-142)Online publication date: 22-Nov-2020
    • (2019)The More You Know: Trust Dynamics and Calibration in Highly Automated Driving and the Effects of Take-Overs, System Malfunction, and System TransparencyHuman Factors: The Journal of the Human Factors and Ergonomics Society10.1177/001872081985368662:5(718-736)Online publication date: 24-Jun-2019
    • Show More Cited By

    View Options

    Login options

    View options

    PDF

    View or Download as a PDF file.

    PDF

    eReader

    View online with eReader.

    eReader

    Media

    Figures

    Other

    Tables

    Share

    Share

    Share this Publication link

    Share on social media