Safety enhancement by detecting driver impairment through analysis of real-time volatilities
The overall goal of the project is to focus on understanding early detection of driver impairment using streaming biometric information coupled with data on vehicle performance and surrounding contexts. During Phase 1 of the project, the team focused on developing a framework for driver impairment detection through analysis of driver biometric information along with vehicle and road infrastructure factors, with streaming data. This project will contribute by implementing the framework and the model developed in Phase 1 to detect impaired driving and any abnormality in the driver, vehicle, and roadway/environment system performance. The model can be used by transportation stakeholders to reduce the probability of crashes. The motivation behind our research is to enhance safety by monitoring driver actions and detecting impairment. To accomplish this task, the project team will conduct experiments in a simulated environment where they will request the participants to emulate specific distracted driving behaviors, e.g., texting, reading, looking at scenery, drowsiness, and drinking. The project team will take a multimodal approach to data collection, monitoring, and analysis. Specifically, the data will include driver biometric signals, vehicle dynamics and telemetry, and external environmental conditions, e.g., traffic flow, simulated weather, day/night conditions. The outcomes of this project will include embedding leading indicators of impairment in Advanced Driver Assistance System (ADAS) that can greatly enhance safety, given the substantial interest from major automotive and information technology companies, especially for applications in fleet vehicles.
- Record URL:
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Supplemental Notes:
- CSCRS2021R44
Language
- English
Project
- Status: Active
- Funding: $TBD
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Contract Numbers:
69A3551747113
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Sponsor Organizations:
Office of the Assistant Secretary for Research and Technology
University Transportation Centers Program
Department of Transportation
Washington, DC United States 20590 -
Managing Organizations:
Collaborative Sciences Center for Road Safety
University of North Carolina, Chapel Hill
Chapel Hill, NC United States 27514 -
Project Managers:
Sandt, Laura
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Performing Organizations:
University of Tennessee, Knoxville
Knoxville, TN United StatesUniversity of North Carolina at Chapel Hill
UNC-CH New East Building
Campus Box #3140
Chapel Hill, North Carolina United States 27599-3140 -
Principal Investigators:
Khattak, Asad
Chakraborty, Subhadeep
Clamann, Michael
- Start Date: 20210501
- Expected Completion Date: 20220831
- Actual Completion Date: 0
- USDOT Program: University Transportation Centers Program
Subject/Index Terms
- TRT Terms: Biometrics; Detection and identification systems; Distraction; Driver monitoring; Driver support systems; Environment; Impaired drivers; Mathematical models; Simulation; Telemetry; Traffic safety; Vehicle performance
- Subject Areas: Data and Information Technology; Highways; Safety and Human Factors;
Filing Info
- Accession Number: 01771371
- Record Type: Research project
- Source Agency: Collaborative Sciences Center for Road Safety
- Contract Numbers: 69A3551747113
- Files: UTC, RIP
- Created Date: May 7 2021 10:24AM