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Analysis of ERP on Drivers in Traffic Accidents by Sudden Vehicle

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Advances in Neuroergonomics and Cognitive Engineering (AHFE 2020)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1201))

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Abstract

The event-related potential (ERP technology) and the psychological software E-prime 2.0 is used to present the simulated scenario, and the NeuroOne EEG event-related potential system is used to obtain the electrical signal acquisition. The stimulus material is composed of 30 car accident videos in the driver’s position to realize the brain of a person in a state of emergency. A series of processing are carried on the original signals to obtain ERP signals. After superimposing and averaging, the incubation period, amplitude, and brain area distribution of human EEG signals such as P300 and N400 in an emergency state are obtained. These characteristics show that human body motion and audiovisual hearing have the greatest effect when emergencies occur or when receiving stimuli. And it can provide analysis and recommendations for personnel ERP in emergency situations.

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Author information

Authors and Affiliations

  1. Department of Safety Engineering, China University of Labor Relations, Beijing, 100048, China

    Guilei Sun, Guangxia Hu & Yanhua Meng

  2. Institute of Safety and Occupational Hygiene, China University of Labor Relations, Beijing, 100048, China

    Guilei Sun & Yanhua Meng

Authors
  1. Guilei Sun
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  2. Guangxia Hu
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  3. Yanhua Meng
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Corresponding authors

Correspondence to Guilei Sun or Guangxia Hu .

Editor information

Editors and Affiliations

  1. Drexel University, Philadelphia, PA, USA

    Hasan Ayaz

  2. National University of Sciences and Tech (NUST), School of Mech and Manufacturing Eng (SMME), Islamabad, Pakistan

    Umer Asgher

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Sun, G., Hu, G., Meng, Y. (2021). Analysis of ERP on Drivers in Traffic Accidents by Sudden Vehicle. In: Ayaz, H., Asgher, U. (eds) Advances in Neuroergonomics and Cognitive Engineering. AHFE 2020. Advances in Intelligent Systems and Computing, vol 1201. Springer, Cham. https://doi.org/10.1007/978-3-030-51041-1_18

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