Detecting unrepresentative road traffic condition data

摘要

Techniques are described for assessing road traffic conditions in various ways based on obtained traffic-related data, such as data samples from vehicles and other mobile data sources traveling on the roads and/or from one or more other sources (such as physical sensors near to or embedded in the roads). The road traffic conditions assessment based on obtained 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 from the data samples. In some situations, the inferences include repeatedly determining current traffic flow characteristics and/or predicted future traffic flow characteristics for road segments of interest during time periods of interest, such as to determine average traffic speed, traffic volume and/or occupancy, and include weighting various data samples in various ways (e.g., based on a latency of the data samples and/or a source of the data samples).

主权项

1. A computer-implemented method comprising:
receiving, by one or more configured computing systems, multiple data samples that reflect travel characteristics of multiple vehicles traveling on a road; automatically analyzing, by the one or more configured computing systems, the multiple data samples to determine one or more data samples of the multiple data samples that are unrepresentative of actual vehicle travel on the road; and providing, by the one or more configured computing systems, an indication of data samples from the multiple data samples other than the determined one or more data samples, to enable use of the indicated data samples in facilitating vehicle travel.