LEVERAGING MULTISOURCE DATA FOR TRAFFIC DATA QUALITY CONTROL
PI: Jidong J. Yang
Co-PI(s): Stephan Durham, Sonny Kim, and Mi Geum Chorzepa
Institution(s): University of Georgia
Abstract
Maintaining High-quality traffic data serves as the foundation for core transportation planning/engineering activities and decisionmaking. The current state of the practice in traffic data quality control features rule-based data checking and validation processes, where the rules are subjective and insensitive to variation inherited with traffic data. This research study aims to leverage the multisource data available at GDOT to improve the quality control process for traffic data. Cross-validating inductive loop-based traffic count data with independent sources (e.g., from the exiting video detection data as part of the 511 system) provides a practical and robust approach for quality control of traffic data in support of various planning/engineering practices and decision-making at GDOT.
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