Dynamic time series prediction of future traffic conditions

Details Dynamic time series prediction of future traffic conditions Dynamic time series prediction of future traffic conditions

2006-03-03

2010-10-12

Tran, Khoi (Department: 3664)

Data processing: vehicles, navigation, and relative location

Vehicle control, guidance, operation, or indication

Traffic analysis or control of surface vehicle

C701S119000, C340S995130

Reexamination Certificate

active

07813870

ABSTRACT:
Techniques are described for generating predictions of future traffic conditions at multiple future times, such as by using probabilistic techniques to assess various input data while repeatedly producing future time series predictions for each of numerous road segments (e.g., in a real-time manner based on changing current conditions for a network of roads in a given geographic area). In some situations, one or more predictive Bayesian models and corresponding decision trees are automatically created for use in generating the future traffic condition predictions for each geographic area of interest, such as based on observed historical traffic conditions for those geographic areas. Predicted future traffic condition information may then be used in a variety of ways to assist in travel and for other purposes, such as to plan optimal routes through a network of roads based on predictions about traffic conditions for the roads at multiple future times.

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