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Author:

Zhao, Xiao-Hua (Zhao, Xiao-Hua.) (Scholars:赵晓华) | Xu, Wen-Xiang (Xu, Wen-Xiang.) | Yao, Ying (Yao, Ying.) | Rong, Jian (Rong, Jian.) (Scholars:荣建)

Indexed by:

EI Scopus

Abstract:

Driving distraction is a task affected by an increasing number of Driving Assistance Systems, which have been a main reason of traffic accident. Understanding the nature of driver distraction and to find a way to analysis the driver distraction we can reduce the traffic accident. This chapter applied the electrocardiography (ECG) for identifying driving situation. ECG data such as heart rate variability (HRV), QRS wave were used to represent driving distraction, the method of sample entropy used to indicate the difference between normal driving and driving distraction. The data have interviewed 34 subjects during two weeks based on driving simulation experiment. The result showed that sample entropy of ECG data on distracted driving is higher than that on normal driving. Especially, the driver who send message during driving has the biggest difference in sample entropy. Driver’s QRS waveform showing a greater degree of confusion on the distracted driving. © Springer Nature Singapore Pte Ltd. 2019.

Keyword:

Accidents Intelligent vehicle highway systems Entropy Electrocardiography Intelligent systems Behavioral research

Author Community:

  • [ 1 ] [Zhao, Xiao-Hua]College of Metropolitan Transportation, Beijing University of Technology, Beijing; 100124, China
  • [ 2 ] [Xu, Wen-Xiang]College of Metropolitan Transportation, Beijing University of Technology, Beijing; 100124, China
  • [ 3 ] [Yao, Ying]College of Metropolitan Transportation, Beijing University of Technology, Beijing; 100124, China
  • [ 4 ] [Rong, Jian]College of Metropolitan Transportation, Beijing University of Technology, Beijing; 100124, China

Reprint Author's Address:

  • 赵晓华

    [zhao, xiao-hua]college of metropolitan transportation, beijing university of technology, beijing; 100124, china

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Source :

ISSN: 1876-1100

Year: 2019

Volume: 503

Page: 263-271

Language: English

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count: 1

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 11

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