Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

Driver distraction from a control theory perspective.

Thomas B Sheridan1

  • 1Volpe National Transportation Systems Center, Cambridge, Massachusetts, USA. sheridan@mit.edu

Human Factors
|February 16, 2005
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

A Distracted Scientist: The Life and Contributions of John Senders.

Human factors·2020
Same author

A review of recent research in social robotics.

Current opinion in psychology·2020
Same author

Individual Differences in Attributes of Trust in Automation: Measurement and Application to System Design.

Frontiers in psychology·2019
Same author

Extending Three Existing Models to Analysis of Trust in Automation: Signal Detection, Statistical Parameter Estimation, and Model-Based Control.

Human factors·2019
Same author

The Intricacies of User Adjustments of Alerting Thresholds.

Human factors·2017
Same author

A Closed-Loop Model of Operator Visual Attention, Situation Awareness, and Performance Across Automation Mode Transitions.

Human factors·2016
Same journal

System-Wide Trust (SWT) Versus Component-Specific Trust (CST) in Multi-Agent Human-Agent Teams: Individual Variability in Trust Bias.

Human factors·2026
Same journal

Driver Adaptation to Partially Automated Driving in Urban Environments: Effects of Repeated Exposure and System Capabilities on Drivers' Trust, Monitoring, and Response.

Human factors·2026
Same journal

Modeling Human Expertise in a Sanding Task.

Human factors·2026
Same journal

Towards Safe and Comfortable Vehicle Control Transitions: A Systematic Review of Takeover Time, Time Budget, and Takeover Outcomes.

Human factors·2026
Same journal

What's in a Name? Implications of AI Roles and Mind Perception for Human-AI Teams.

Human factors·2026
Same journal

Safety Climate and Safety Behavior and Outcomes: A Comprehensive Systematic Review in Healthcare From the Perspective of Staff and Patients.

Human factors·2026
See all related articles

Driver distraction from interactive devices is a safety concern. A control theory framework defines distraction as disturbances to the driver

Area of Science:

  • Human-Computer Interaction
  • Transportation Safety
  • Control Theory Applications

Background:

  • Driver distraction from in-vehicle technologies is a significant safety issue.
  • Current understanding and definitions of driver distraction are limited.
  • The proliferation of interactive devices in vehicles exacerbates distraction risks.

Purpose of the Study:

  • To develop a comprehensive framework for understanding driver distraction.
  • To define the loci and causes of distraction within a control theory model.
  • To propose a structured approach for researching driver distraction.

Main Methods:

  • Application of control theory principles to model the driver-vehicle system.
  • Representation of distraction as disturbances within the driver's control loop.

Related Experiment Videos

  • Modeling attention switching as sampled-data control.
  • Integration of mental modeling and anticipation into the framework.

    • Main Results:

    • A novel framework defining driver distraction using control theory.
    • Identification of specific functional elements disturbed by distraction.
    • Modeling of attention switching and its impact on driving.
    • The framework suggests avenues for future research and experimentation.

    Conclusions:

    • The proposed control theory framework offers a refined understanding of driver distraction.
    • This model can improve the prediction of driving performance.
    • Research findings can inform vehicle and highway design for enhanced safety.