Measure for Traffic Anomaly Detection on the Urban Roads Using Speed Transition Matrices

Road traffic anomaly detection is an essential research topic within the Intelligent Transport System (ITS) context. Urban road anomaly detection systems are a crucial part of the ITS regarding the trip planning, road security, and congestion estimation applications. In this paper, the method for traffic anomaly detection using Speed Transition Matrices (STM) is presented. The paper’s main goal is to present the novel method for measuring the distance between two STM, as standard distance measures are inapplicable for the anomaly detection and road traffic analysis interpretation The method is based on the Euclidean distance measure between STM’s Center of Mass (COM), and the average STM that represents normal traffic conditions. The Global Navigation Satellite System (GNSS) data on the roadnetwork of City of Zagreb were used as a case study, as it is, the capital and the largest city in Croatia, suitable for the application of the proposed methodology. The anomaly detection method resulted in 73 anomalous points which are presented on the digital map. The proposed method is compared to the other distance metrics used in the literature, and advantages over each of the metrics are highlighted.