Investigating mental workload caused by NDRTs in highly automated driving with deep learning.

Journal: Traffic injury prevention
PMID:

Abstract

OBJECTIVE: This study aimed to examine the impact of non-driving-related tasks (NDRTs) on drivers in highly automated driving scenarios and sought to develop a deep learning model for classifying mental workload using electroencephalography (EEG) signals.

Authors

  • Xintao Hu
  • Jing Hu
    College of Chemistry, Sichuan University Chengdu 610064 People's Republic of China xmpuscu@scu.edu.cn +86 028 8541 2290.