Automated Identification of Traffic Detector Malfunctions
To assess the quality of data provided by traffic detectors, and therefore detector health, research is necessary to bridge the gap between existing traffic theory and pattern recognition that can identify poor performance (through comparison of data to expected norms) in an automated fashion. To address this gap, the proposed objective is to develop a reliable and robust method of determining poor performance of a traffic detector based solely on historical data and traffic flow theory. It is proposed that this method will work at isolated signalized intersections, using data only from that intersection’s detectors for evaluation. Additionally, a system design of this method will be developed to assist Oregon Department of Transportation (ODOT) with implementation of the method.
Language
- English
Project
- Status: Active
- Funding: $193000
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Contract Numbers:
SPR 837
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Sponsor Organizations:
Federal Highway Administration
1200 New Jersey Avenue, SE
Washington, DC United States 20590 -
Managing Organizations:
Oregon Department of Transportation
555 13th Street NE
Salem, OR United States 97301 -
Project Managers:
Li, Joe
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Performing Organizations:
Civil and Environmental Engineering
PO box 15600
Flagstaff, Arizona United States 86011 -
Principal Investigators:
Smaglik, Edward
- Start Date: 20200101
- Expected Completion Date: 20211231
- Actual Completion Date: 0
- USDOT Program: Transportation, Planning, Research, and Development
Subject/Index Terms
- TRT Terms: Automation; Data analysis; Data quality; Performance measurement; Traffic flow theory; Vehicle detectors
- Identifier Terms: Oregon Department of Transportation
- Subject Areas: Data and Information Technology; Highways; Operations and Traffic Management;
Filing Info
- Accession Number: 01725109
- Record Type: Research project
- Source Agency: Oregon Department of Transportation
- Contract Numbers: SPR 837
- Files: RIP, STATEDOT
- Created Date: Dec 12 2019 1:36PM