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Title:

Evaluating Driving Safety of Road Alignment Conditions by Predicted Driver’s Psychophysiological Workload Using Vehicle Maneuvering Data

Accession Number:

01890157

Record Type:

Component

Availability:

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Order URL: http://worldcat.org/issn/03611981

Abstract:

Evaluating driving safety according to road alignment conditions is a fundamental for safe road design and traffic operations to prevent traffic crashes. A significant intrinsic factor affecting driving safety is the driver’s psychophysiological workload generated in response to various external environmental changes during road driving. Electroencephalogram (EEG) is a well-known measure to evaluate the driver workload resulting from the response to the internal and external stimuli experienced while driving vehicles. However, the use of EEG in research of the transportation engineering domain requires not only high-cost experiments but also great efforts in data analysis. To address these issues, this study developed a promising method to predict the psychophysiological workload affecting driving safety using vehicle maneuvering data. A total of 30 drivers participated in driving simulation experiments using a high-fidelity motion-based driving simulator to obtain both psychophysiological workload data and vehicle maneuvering data to be used for developing the methodology. The proposed methodology consists of two parts: the prediction of the level of psychophysiological workload using a K-nearest neighbor (KNN) algorithm and the derivation of the alertness risk index (ARI) based on the spatiotemporal aggregation of the prediction results. Additionally, evaluating driving safety by different road conditions is conducted based on the proposed methodology.

Supplemental Notes:

Jiyong Jang https://orcid.org/0000-0003-4225-8475© National Academy of Sciences: Transportation Research Board 2023.

Language:

English

Authors:

Jang, Jiyong

ORCID 0000-0003-4225-8475

Jung, Aram

ORCID 0000-0003-4525-9828

Oh, Cheol

ORCID 0000-0002-1431-9480

Park, Jaehong
Yun, Dukgeun

ORCID 0000-0002-1204-7282

Publication Date:

2023

Serial:

Transportation Research Record: Journal of the Transportation Research Board

Publisher: Sage Publications, Incorporated
ISSN: 0361-1981
EISSN: 2169-4052
Serial URL: http://journals.sagepub.com/home/trr

Media Type:

Web

Features:

References (45)

Subject Areas:

Highways; Operations and Traffic Management; Safety and Human Factors

Files:

TRIS, TRB, ATRI

Created Date:

Aug 15 2023 3:01PM