Application of Kalman Filtering to the Surveillance and Control of Traffic Systems

Michael W. Szeto and Denos C. Gazis
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Michael W. Szeto: Massachusetts Institute of Technology, Cambridge, Massachusetts
Denos C. Gazis: IBM Watson Research Center, Yorktown Heights, New York

Transportation Science, 1972, vol. 6, issue 4, 419-439

Abstract: The methodology of the discrete-time, extended Kalman filter is applied for the estimation of densities and the control of critical traffic links. The methodology is tested using traffic data obtained at the Lincoln tunnel of New York City. Two algorithms are tested, one involving density estimation alone and one combining density estimation with a formalism for the determination of optimal control. The results indicate that the first algorithm gives very good density estimates. The second algorithm yields a less accurate density estimate, but has the advantage over the first that it is amenable to an analytical optimization investigation.

Date: 1972
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Persistent link: https://EconPapers.repec.org/RePEc:inm:ortrsc:v:6:y:1972:i:4:p:419-439

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