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Title:

Assessment of Urban Railway Transit Driver Workload and Fatigue under Real Working Conditions

Accession Number:

01711262

Record Type:

Component

Availability:

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

Abstract:

This paper describes an experiment conducted to establish a workload model by employing physiological methods to measure driver workload and fatigue under real working conditions. Experienced healthy metro drivers were selected as subjects; they performed normal schedules during which simultaneous electrocardiogram (ECG) recording was used to assess their levels of fatigue. Then, subjective workload assessment and reaction time tests were conducted during each break interval to monitor the drivers’ physiological and psychological performance. Based on task analysis, driving workload models with time weight parameters of four types of tasks were established and the workload real-time changes during different shifts were evaluated. The results demonstrate that workload tends to increase over time and it is significantly higher during manual driving mode than autonomous mode (p = 0.015 < 0.05). Driving fatigue occurs earlier in the night shift than in the day shift according to ECG spectrum analysis results. Although the results of reaction time tests show no significance (p = 0.917 > 0.05), the increase in the number of reaction errors after fatigue driving indicates a reduction in drivers’ cognitive ability. Regression analysis shows a significant regression relationship with a mutual incentive effect between workload and fatigue in three shifts (R2 > 0.4). These will be used as a future reference for fatigue research and to help develop reasonable schedules to ensure operational safety.

Supplemental Notes:

The Task Force on Transit Safety and Security (AP018T) peer-reviewed this paper (19-02838). © National Academy of Sciences: Transportation Research Board 2019.

Report/Paper Numbers:

19-02838

Language:

English

Authors:

Huang, Yuan-chun
Li, Lan-peng
Liu, Zhi-gang
Zhu, Hai-yan
Zhu, Lin

Pagination:

pp 891-900

Publication Date:

2019-11

Serial:

Transportation Research Record: Journal of the Transportation Research Board

Volume: 2673
Issue Number: 11
Publisher: Sage Publications, Incorporated
ISSN: 0361-1981
EISSN: 2169-4052
Serial URL: http://journals.sagepub.com/home/trr

Media Type:

Digital/other

Features:

Figures; References (59) ; Tables

Subject Areas:

Operations and Traffic Management; Railroads; Safety and Human Factors

Files:

TRIS, TRB, ATRI

Created Date:

Feb 1 2019 1:38PM