KALMAN FILTERING ESTIMATION OF TRAFFIC COUNTS FOR TWO NETWORK LINKS IN TANDEM

Previous studies have used the extended Kalman filter (EKF) to obtain improved vehicular density estimates, by coupling counts from detectors with independent density estimates, subject to uncorrelated errors. This study extends the EKF formulation to estimate vehicle counts for two roadway sections in tandem. By considering the fact that the counting error for vehicles leaving a given section is the same as the error for the vehicles entering the very next section, the resulting count estimates are improved over those obtained by treating the two sections as isolated. Using real data, the methodology is confirmed by comparing the analytical derivations of the error estimated when treating two tandem sections together with those obtained by treating the sections as isolated ones. The methodology could potentially be used to estimate the vehicle numbers for multi-section freeways under various flow conditions on a real time basis, thus facilitating effective traffic management of the network.

Language

  • English

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Filing Info

  • Accession Number: 00961816
  • Record Type: Publication
  • Files: TRIS, ATRI
  • Created Date: Aug 12 2003 12:00AM