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EDA Driving Data and Survey Responses

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Collection period

2022-08-30
2023-03-04

Date completed

2023-03-04

Date updated

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Journal Title

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Title

EDA Driving Data and Survey Responses

Published Date

2023-04-05

Author Contact

Seecharan, Turuna
tseechar@d.umn.edu

Type

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).

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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.

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