13th Asia Pacific Transportation Development Conference
Study on Fatigue of Urban Railway Transportation Drivers Based on Eye Movement Characteristics and Electrocardiogram
Publication: Resilience and Sustainable Transportation Systems
ABSTRACT
It is of great significance to identify the driver's fatigue state in actual operation to improve the safety of urban railway transportation and prevent the occurrence of various safety accidents caused by driver's fatigue. Based on the train driving simulation experiment of urban railway transportation, electrocardiogram (ECG) signals and eye movement characteristics of subjects were obtained, and the collected data were analyzed. By analyzing the data, the fatigue degree of the subjects is judged, and the fatigue period is distinguished according to the time period of fatigue occurrence, and the indicators that can be used to construct support vector machine are selected in the obtained data. Finally, according to the theory of support vector machine, using MATLAB and libsvm software, select the appropriate kernel function, train the fatigue identification model of non-linear support vector machines (SVM), and verify the accuracy of the model with experimental data.
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Information & Authors
Information
Published In
Resilience and Sustainable Transportation Systems
Pages: 329 - 336
Editors: Fengxiang Qiao, Ph.D., Texas Southern University, Yong Bai, Ph.D., Marquette University, Pei-Sung Lin, Ph.D., University of South Florida, Steven I Jy Chien, Ph.D., New Jersey Institute of Technology, Yongping Zhang, Ph.D., California State Polytechnic University, and Lin Zhu, Ph.D., Shanghai University of Engineering Science
ISBN (Online): 978-0-7844-8290-2
Copyright
© 2020 American Society of Civil Engineers.
History
Published online: Jun 29, 2020
Published in print: Jun 29, 2020
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