Surface Street Traffic Estimation

In this paper, we propose a simple yet effective method of identifying traffic conditions on surface streets given location traces collected from on-road vehicles-this requires only GPS location data, plus infrequent low-bandwidth cellular updates. Unlike other systems, which simply display vehicle speeds on the road, our system characterizes unique traffic patterns on each road segment and identifies unusual traffic states on a segment-by-segment basis. We developed and evaluated the system by applying it to two sets of location traces. Evaluation results show that higher than 90% accuracy in characterization can be achieved after ten or more traversals are collected on a given road segment. We also show that traffic patterns on a road are very consistent over time, provided that the underlying road conditions do not change. This allows us to use a longer history in identifying traffic conditions with higher accuracy.