Wearable neurotechnology for inferring the driver's attention for assistive driving

Inferring a driver's attentive state and visual focus will be critical in future transport systems. This project will develop wearable technology and AI algorithms to infer the location and the degree of a driver's visual attention based on Electroencephalography (EEG) electrodes placed on the driver's head while they driving (real-world and simulated VR environments). This attentional signal can be used, in conjunction with vehicular sensors, for automated decisions at critical moments.

• Record URL:
  https://ppms.cit.cmu.edu/projects/detail/323

Language

• English

Project

• Status: Completed
• Funding: $100000
• Contract Numbers:

  69A3551747111

• Sponsor Organizations:

  Carnegie Mellon University

  Mobility21 National USDOT UTC for Mobility of Goods and People
  Pittsburgh, PA  United States  15213

  Office of the Assistant Secretary for Research and Technology

  University Transportation Center Program
  ,    
• Managing Organizations:

  Carnegie Mellon University

  Mobility21 National USDOT UTC for Mobility of Goods and People
  Pittsburgh, PA  United States  15213
• Project Managers:

  Kline, Robin

• Performing Organizations:

  Carnegie Mellon University

  ,    
• Principal Investigators:

  Grover, Pulkit

• Start Date: 20200701
• Expected Completion Date: 20210630
• Actual Completion Date: 20210928
• USDOT Program: University Transportation Centers

Subject/Index Terms

• TRT Terms: Algorithms; Artificial intelligence; Attention; Driver support systems; Drivers; Electroencephalography; Sensors; Technological innovations
• Subject Areas: Data and Information Technology; Highways; Safety and Human Factors;

Filing Info

• Accession Number: 01738976
• Record Type: Research project
• Source Agency: National University Transportation Center for Improving Mobility (Mobility21)
• Contract Numbers: 69A3551747111
• Files: UTC, RIP
• Created Date: May 11 2020 10:25AM