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Title:

Recognition of Driving Fatigue Based on Support Vector Machine

Accession Number:

01763623

Record Type:

Component

Abstract:

This paper use support vector machine (SVM) to identify the fatigue of train drivers in rail transit. The authors designed a driving of urban rail transit train on the main line simulating experiment through the traffic simulation driving system. Select train drivers in good health condition as experimental subjects and collect pulse signals by Photoplethysmograph. Due to the single driving environment of rail transit train drivers, the authors proposed a fatigue classification standard based on the pupil area, recorded the eye-movement related data of the train drivers during the experiment by eye tracker equipment and identified the feasibility of the standard, the accuracy rate reached 86.36% by using SVM .

Supplemental Notes:

This paper was sponsored by TRB committee AR070 Standing Committee on Rail Safety.

Report/Paper Numbers:

TRBAM-21-01033

Language:

English

Corporate Authors:

Transportation Research Board

Authors:

Zhu, Hai-yan
Luo, Jin
Gao, Ting
Liu, Zhi-gang

Pagination:

13p

Publication Date:

2021

Conference:

Transportation Research Board 100th Annual Meeting

Location: Washington DC, United States
Date: 2021-1-5 to 2021-1-29
Sponsors: Transportation Research Board; Transportation Research Board

Media Type:

Digital/other

Features:

Figures; Photos; References; Tables

Subject Areas:

Public Transportation; Railroads; Safety and Human Factors

Source Data:

Transportation Research Board Annual Meeting 2021 Paper #TRBAM-21-01033

Files:

TRIS, TRB, ATRI

Created Date:

Dec 23 2020 11:07AM