Real-Time Anomaly Detection System for Signalized Intersections

About the project

Automated Traffic Signal Performance Metrices (ATSPMs) rely on high-resolution controller data to support signal operations and maintenance. While existing ATSPM Watchdog tools can identify certain detector malfunctions, they typically rely on static thresholds set across the entire system, limiting their ability to detect issues promptly and adapt to site-specific traffic patterns. This project develops and evaluates a statistical, spatiotemporal anomaly detection framework that leverages historical detector behavior and agreement among neighboring detectors to improve alert timeliness and accuracy. The research will characterize practitioner needs, define normal detector behavior, develop and test statistical detection and classification methods, and quantify benefits relative to static thresholds. Results will inform a roadmap for potential real-time implementation within VDOT systems.

Project team

Principal investigators

Co-Principal investigators

Project manager

Project monitor

Members