Abstract: Techniques are described for assessing road traffic conditions in various ways based on obtained traffic-related data, such as data samples from road traffic sensors (e.g., physical sensors that are near or embedded in the roads) and/or from vehicles and other mobile data sources traveling on the roads. The assessment of road traffic conditions based on obtained sensor data readings and/or other data samples may include various filtering and/or conditioning of the data samples, and various inferences and probabilistic determinations of traffic-related characteristics of interest. Assessing obtained data may further include determining traffic conditions (e.g., traffic flow and/or average traffic speed) for various portions of a road network in a particular geographic area, based at least in part on obtained data samples.

Abstract: Techniques are described for automatically detecting anomalous road traffic conditions and for providing information about the detected anomalies, such as for use in facilitating travel on roads of interest. Anomalous road traffic conditions may be identified using target traffic conditions for a particular road segment at a particular selected time, such as target traffic conditions that reflect actual traffic conditions for a current or past selected time, and/or target traffic conditions that reflect predicted future traffic conditions for a future selected time. Target traffic conditions may be compared to distinct expected road traffic conditions for a road segment at a selected time, with the expected conditions reflecting road traffic conditions that are typical or normal for the road segment at the selected time. Anomalous conditions may be identified based on sufficiently large differences from the expected conditions, and information about the anomalous conditions may be provided in various ways.