Inrix Inc.

Inrix, Inx.

Jesse S Hersch

Oliver B Downs

Craig H Chapman

Robert Cahn

Kush G Parikh

Christopher Laurence Scofield

Alec Barker

Mitchel A Burns, Jr

Scott R Love

Te-Ming Huang

Wayne Stoppler

Valerie Raybold Yakich

Robert C Cahn

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).

Filtering road traffic data from multiple data sources

Techniques are described for determining and using information regarding expected road traffic flow conditions information for vehicles traveling on roads. The expected road traffic flow conditions for a particular portion of a road may be generated by combining historical representative information about road traffic flow conditions for that road portion with current information about actual traffic flow on or near that road portion. The combination may, for example, provide benefits for estimating expected traffic flow conditions information for roads with structural flow obstructions that cause reduced traffic flow at certain road locations and times&#x2014;for example, the expected traffic flow conditions information may be based at least in part on fitting or otherwise adapting partial actual traffic flow information about a vehicle's actual travel path to a historical travel profile for a road that includes representative traffic flow information for various combinations of road locations and time periods.

Predicting expected road traffic conditions based on historical and current data

Detecting unrepresentative road traffic condition data

Techniques are described for automatically analyzing historical information about road traffic flow in order to generate representative information regarding current or future road traffic flow, and for using such generated representative traffic flow information. Representative traffic flow information may be generated for a variety of types of useful measures of traffic flow, such as for average speed at each of multiple road locations during each of multiple time periods. Generated representative traffic flow information may be used in various ways to assist in travel and for other purposes, such as to determine likely travel times and plan optimal routes. The historical traffic data used to generate the representative traffic flow information may include data readings from physical sensors that are near or embedded in the roads, and/or data samples from vehicles and other mobile data sources traveling on the roads.

Representative road traffic flow information based on historical data

Detecting anomalous road traffic conditions

Determining road traffic conditions using multiple data samples

Determining road traffic conditions using data from multiple data sources

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Bellevue, WA, United States of America

Jesse S Hersch