Deep-Learning-Based Prediction of High-Risk Taxi Drivers Using Wellness Data.

Journal: International journal of environmental research and public health
Published Date: Dec 18, 2020

Abstract

BACKGROUND: Factors related to the wellness of taxi drivers are important for identifying high-risk drivers based on human factors. The purpose of this study is to predict high-risk taxi drivers based on a deep learning method by identifying the wellness of a driver, which reflects the personal characteristics of the driver.

Authors

  • Seolyoung Lee
    Research Institute of Engineering Technology, Hanyang University Erica Campus, Ansan 15588, Korea.
  • Jae Hun Kim
    Research Institute of Engineering Technology, Hanyang University Erica Campus, Ansan 15588, Korea.
  • Jiwon Park
    Department of Transportation and Logistics Engineering, Hanyang University Erica Campus, Ansan 15588, Korea.
  • Cheol Oh
    Department of Transportation and Logistics Engineering, Hanyang University Erica Campus, Ansan 15588, Korea.
  • Gunwoo Lee
    Medical Imaging R&D Group, Health & Medical Equipment Business, Samsung Electronics Co., Ltd., Seoul, Republic of Korea.

Keywords

External Resources

Popular Topics
Recent Journals