Intelligenttransportation system has been a major research area
during the past decade [9]. Now sensors have been an increasingly
important method in the intelligent transportation system design
[10]. An algorithm for the implementation of short-term prediction
of traffic with real-time updating based on spectral analysis is
described in [11]. The prediction is based on the characterization
of the flow based on modal functions associated with a covariance
matrix constructed from historical flow data. The number of these
modal functions used for prediction depends on the local traffic
characteristics. Although the method works well for the examples
in this paper using the lower frequency modes, it can be adapted
to include modes of higher frequency, as traffic conditions dictate.