Patent ID: 8755991
Filing Date: 2014-06-17
Classification: G01C,G08G

Abstract:
1. A method for predicting traffic on a transportation network, said transportation network comprised of links, said links constituting a relationship vector, said method comprising: a) providing data points related to real time traffic conditions on each link, wherein at least one data point is missing for a given link; b) estimating the value of said missing data point from a calibrated model representative of historical data points from all links in the relationship vector, except those from the given link; and c) using said estimated value to predict traffic for at least a portion of said transportation network by deviation from a historical traffic pattern of said network, wherein said estimating said value of said missing data point comprises: running a plurality of models for the given link having a missing data point at a most recent time, wherein a model provides either estimating a value for said missing data point of said given link at a most recent time when all other neighboring links of said relationship vector have data at said most recent time, or estimating a value for said missing data point when one or more other neighboring links of said relationship vector is missing a respective data point at said most recent time, generating from each said run model a respective associated weight matrix for said given link; storing each respective associated weight matrix for said given link; determining an applicable model corresponding to a current real-time traffic network condition of said links of said relationship vector; and choosing an associated estimated weight matrix of said plurality based on said applicable model, said chosen associated estimated weight matrix used by said calibrated model to determine said missing data point value for real-time traffic prediction, wherein at least one of the steps is performed by at least one processor.