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:
Language
- English
Project
- Status: Active
- Funding: $100000
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Contract Numbers:
69A3551747111
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Sponsor Organizations:
Carnegie Mellon University
Mobility21 National USDOT UTC for Mobility of Goods and People
Pittsburgh, PA United States 15213Office of the Assistant Secretary for Research and Technology
University Transportation Center Program
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Managing Organizations:
Carnegie Mellon University
Mobility21 National USDOT UTC for Mobility of Goods and People
Pittsburgh, PA United States 15213 -
Project Managers:
Kline, Robin
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Performing Organizations:
Carnegie Mellon University
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Principal Investigators:
Grover, Pulkit
- Start Date: 20200701
- Expected Completion Date: 20210630
- Actual Completion Date: 0
- 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