EDA Driving Data and Survey Responses
2023-04-05
Loading...
Persistent link to this item
Statistics
View StatisticsCollection period
2022-08-30
2023-03-04
2023-03-04
Date completed
2023-03-04
Date updated
Time period coverage
Geographic coverage
Source information
Journal Title
Journal ISSN
Volume Title
Title
EDA Driving Data and Survey Responses
Published Date
2023-04-05
Authors
Author Contact
Seecharan, Turuna
tseechar@d.umn.edu
tseechar@d.umn.edu
Type
Dataset
Human Subjects Data
Survey Data-Qualitative
Other Dataset
Human Subjects Data
Survey Data-Qualitative
Other Dataset
Abstract
To find the relation between drivers’ stress levels and driving performance, two types of data were collected: drivers’ stress data, as known as Electrodermal Activity (EDA) Data, and vehicles’ engine data. The purpose of this study is to investigate how drivers’ driving performance changes in higher-stressed situations.
Description
Twenty participants aged between 18-30 participated in this study. To collect stress data, participants wore an E4 empatica wristband while driving, and a telematics device collected engine data. Acceleration, braking, right turn, and left turn data were collected as engine data. Raw EDA data and EDA features were used to observe the change in driving performance. In this study, higher engine data was observed with higher stress data, which means that with the change in stress level, drivers’ driving performance changes.
Referenced by
Tila, T.Z., Seecharan, T.S. (2023). Using Wearable Sensors to Form a Relationship Between Driver Stress and Aggressive Driving Habits. In 16th WCEAM Proceedings. WCEAM 2022. Lecture Notes in Mechanical Engineering. Springer, Cham. https://doi.org/10.1007/978-3-031-25448-2_32
Tila, T.Z., Seecharan, T.S. Analysis of driver stress on aggressive driving habits using wearable sensors. (Under Review).
Tila, T.Z., Seecharan, T.S. Analysis of driver stress on aggressive driving habits using wearable sensors. (Under Review).
Related to
Replaces
item.page.isreplacedby
Publisher
Collections
Funding information
item.page.sponsorshipfunderid
item.page.sponsorshipfundingagency
item.page.sponsorshipgrant
Previously Published Citation
Other identifiers
Suggested citation
Seecharan, Turuna; Tila, Tahrim Zaman. (2023). EDA Driving Data and Survey Responses. Retrieved from the Data Repository for the University of Minnesota (DRUM), https://doi.org/10.13020/9dre-8p52.
View/Download File
File View/Open
Description
Size
Engine Dataset.xlsx
Engine Data
(493.72 KB)
Survey Responses.xlsx
Survey Responses
(14.66 KB)
EDA Features.xlsx
Electrodermal Activity Features Data
(21.29 KB)
EDA Dataset (2).xlsx
Electrodermal Activity Raw Data
(27.79 MB)
Readme_Tila_2023-2.txt
Readme File
(8.55 KB)
Duplicate files in CSV.zip
Duplicate datasets in csv format for preservation
(6.05 MB)
Content distributed via the University Digital Conservancy may be subject to additional license and use restrictions applied by the depositor. By using these files, users agree to the Terms of Use. Materials in the UDC may contain content that is disturbing and/or harmful. For more information, please see our statement on harmful content in digital repositories.