Abstract

A new method of data integration to detect congestion in signalized urban networks is presented. The method uses imprecise knowledge within the framework of fuzzy operator logic and the modified Dempster-Shafer rule of combination. The results of the method evaluation indicate that the amount of congestion information produced by the algorithm increases several times after the intelligent processing is applied to sparse data. The developed algorithm can be also used to reduce amount of source data required.

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