Anomaly Detection for Traffic Management Purposes at Urban Intersections Using Infrastructure-Generated Vehicle-to-X Messages

Reliable detection of problematic system states in traffic management poses a significant challenge. Failures in detection can result in the inability to intervene in a timely manner, while excessive detection may lead to operator fatigue, causing critical information to be ignored amidst an overload of irrelevant messages. Light-controlled intersections represent both safety and efficiency-critical locations within urban traffic networks. Anomalies in these traffic system units can manifest at various levels: technically/physically within the control systems (actuators, sensors, communication technology), at the traffic data level (reliability and completeness of collected traffic data), and in traffic observation (unusual traffic flows, unusual objects). Anomaly detection occurs across these different levels using various methods (technical and algorithmic). Vehicle-to-Everything (V2X) communication provides an additional data source for monitoring the correct and efficient operation of traffic signal systems. This paper presents strategies for leveraging the diverse messages from V2X communication to identify unusual system states across these levels. We demonstrate our approaches at an urban intersection within the Digital Testbed Dresden.