Abstract
Humans operating motor vehicles are often required to engage in decision-making while under substantial cognitive loads imposed by the driving environment itself. Experiencing elevated emotions can influence driver decision-making in a way that increases the risk to the safety of the driver and system performance. Emotion regulation techniques (ERTs) can be used to improve driving safety and performance; however, these techniques can only be effective in an operational driving context if they impose minimal additional cognitive loading on the driver, thus avoiding issues with distraction and the increased workload that could further impact decision making, driving performance, and safety. Additionally, due to motivational factors influencing individual drivers, ERTs that can be activated with greater subtlety (less obvious to the driver) may be more effective than those that are perceived as more obvious and potentially condescending. To determine effective methods that ultimately improve driving safety, two classes of ERTs will be evaluated in this study: those that are classified as “overt”, such as explicitly prompting drivers to perform a cognitive reappraisal of the situation, and those classified as “covert”, such as introducing subtle cues that influence physiological systems, such as synchronizing breathing patterns in a manner that is effective in regulating emotions. Given that affective states can be manipulated with little or no conscious engagement, covert ERTs that minimize cognitive demand, and perhaps even work subconsciously, may be well suited for supporting drivers in an active driving context. The findings of this work can provide design guidance for future driver systems design.
Project Highlights
- Coming Soon
Final Report
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EWD & T2 Products
Coming Soon
Presentations/Publications
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Final Dataset
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Research Investigators (PI*)
Thomas Ferris (TTI/TAMU-Student)*
Sahinya Susindar (TTI/TAMU-Student)
Harrison Wissel-Littmann (TTI/TAMU-Student)
Project Information
Start Date: 01-06-2021
End Date: 01-09-2022
Status: Active
Grant Number: 69A3551747115
Total Funding: $68,276
Source Organization: Safe-D National UTC
Project Number: TTI-Student-09
Safe-D Theme Areas
Big Data Analytics
Connected Vehicle
Safe-D Application Areas
Driver Factors and Interfaces
Risk Assessment
Vehicle Technology
More Information
RiP URL
UTC Project Information Form
Sponsor Organization
Office of the Assistant Secretary for Research and Technology
University Transportation Centers Program
Department of Transportation
Washington, DC 20590 United States
Performing Organization
Texas A&M University
Texas A&M Transportation Institute
3135 TAMU
College Station, Texas 77843-3135
USA