A Multi-sensor System for Traffic Analysis at Smart Intersections

We present a multi-sensor system for vehicle and pedestrian traffic analysis and visualization at intersections to discover trajectory patterns and anomalous traffic behavior. Augmenting these data with signal and phasing information, we show how clustering in the context of signal information may help us to detect anomalies with respect to vehicles violating signals. We demonstrate our workflow on two intersections with very different traffic composition. The system may be leveraged by a number of other applications, including conflict detection in object movements, turn movement counts, incident detection and management, and demand profiling, for better traffic management through the adjustment of signal timing.