Driving behavior recognition using EEG data from a simulated car-following experiment-Reference-Cited by-同舟云学术

Driving behavior recognition using EEG data from a simulated car-following experiment

Published:2018-07 Issue: Volume:116 Page:30-40
ISSN:0001-4575
Container-title:Accident Analysis & Prevention
language:en
Short-container-title:Accident Analysis & Prevention

Author:

Yang Liu,Ma Rui,Zhang H. Michael,Guan Wei,Jiang Shixiong

Funder

National Natural Science Foundation of China

Fundamental Research Funds for the Central Universities

Publisher

Elsevier BV

Subject

Public Health, Environmental and Occupational Health,Safety, Risk, Reliability and Quality,Human Factors and Ergonomics

Reference44 articles.

1. Learning from Data;Abu-Mostafa,2012

2. Deep in thought while driving: an EEG study on drivers’ cognitive distraction;Almahasneh;Transp. Res. Part F: Traffic Psychol. Behav.,2014

3. Probabilistic driving style determination by means of a situation based analysis of the vehicle data;Bar;14th IEEE Conference on Intelligent Transportation Systems,2011

4. ADJUST: An Automatic EEG Artifact Detector Based on the Joint Use of Spatial and Temporal features;Buiatti,2011

5. Driving behaviour modelling system based on graph construction;Chen;Transp. Res. Part C: Emerg. Technol.,2013

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