Anomaly detection in transportation networks using machine learning techniques

摘要: We develop a method to detect atypical traffic jams in the City of Boston. Our motivation is these which are often caused by some event (e.g., accident, lane closure, etc.) and enable intervene before congestion spreads adjacent roads negatively affected. Using jam dataset provided Boston, we present novel detection system for anomalous identification. demonstrate its effectiveness using it identify that cannot be explained typical patterns.