WS21: Driver Vigilance Estimation for Vehicle Active Safety

Workshop Code: 16qc3

Time: 8:30-12:00 & 13:30-17:00


  • Bao-Liang Lu
    Affiliation: Shanghai Jiao Tong University, China

  • Chin-Teng Lin
    Affiliation: University of Technology Sydney, Australia

Scope and Goals

Vigilance decrement or attention lapse has long been recognized as the critical factor responsible for thousands of deaths and injuries each year in the public traffic community. Driving tasks, particularly truck driving and high-speed trains, require sustained high vigilance. However, efficient techniques for quantifying driver vigilance levels are still lacking, which leads to the inability to provide active feedback for active safety systems. Although considerable progress has been achieved in various areas over the past decades, accurately estimating driver vigilance in real-world driving environments is still difficult. The main reason for this difficulty is that vigilance states are intrinsic mental states that involve temporal evolution rather than a time point. It is difficult to evaluate mental states without using an intrusive stimulus or behavior probe. Moreover, real-world applications require continuous vigilance estimation with high temporal resolution. Vigilance decrement is typically accompanied by both external behaviors, such as head nodding, yawning, and eye closure, and internal physiological changes. Various approaches based on these cues have been developed. Among these various modalities, physiological signals have been found to be relevant for different vigilance levels. However, how to identify reliable and valid biomarkers remains a challenge within the research community. The aim of this workshop is to give a forum for researchers to present the state-of-the art of neural mechanism, modelling, devices, and systems for driver vigilance estimation and to exchange ideas and issues.


  • 9:00-09:10
    Organizer’s introduction

  • 9:10-10:10
    Keynote: Brain Computer Interface (BCI) for Driving Cognition
    Chin-Teng Lin, University of Technology Sydney, Australia

  • 10:10-10:30
    Coffee break

  • 10:30-11:00
    Invited talk: Prediction of Driver’s Eye Fixation Distribution with Visual Attention Model
    Yongjie Li, University of Electronic Science and Technology of China, China

  • 11:00-11:30
    Invited talk: Driver Distraction Detection Using Multiple Kernel Learning
    Yan Yang, Northwestern Polytechnical University, China

  • 11:30-12:00
    Invited talk: Noncontact Stress Monitoring and Sleep Analysis using Millimeter Wave Radar
    Jin Zhang, Southern University of Science and Technology, China

  • 12:00-13:30
    Lunch break

  • 13:30-14:00
    Invited talk: EEG-based spatio-temporal interaction analysis for driver fatigue assessment
    Fengyu Cong, Dalian University of Technology, China

  • 14:00-14:30
    Invited talk: Assessment of driving fatigue based on brain connectivity
    Wanzong Kong, Hangzhou Dianzi University, China

  • 14:30-15:00
    Coffee break

  • 15:00-16:00
    Keynote: Multimodal Vigilance and Sleep Quality Estimation Using Transfer Learning
    Bao-Liang Lu, Shanghai Jiao Tong University, China

  • 16:00-16:30
    Summary and discussion round with all speakers