An intelligent vehicle tracking method.

Author(s)
Kim, I. & Soh, Y.
Year
Abstract

This paper presents a fuzzy alpha-beta (a-b) filter as an intelligent vehicle tracking method. This filter is compared with other methods such as a-b filter and Kalman filter. Each method is briefly reviewed with its own properties. Simulation shows that a fuzzy a-b filter is as accurate as the Kalman filter in tracking vehicles. Considering computational cost, a fuzzy a-b filter has advantage over the Kalman filter because its basic structure is built on the a-b filter. Intelligence comes into play to modify the fixed-coefficients, a and b, to the current difference between measurement and prediction. The cause of failures in vehicle tracking are described and reconstruction of missing data is demonstrated using a fuzzy a-b filter.

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Publication

Library number
C 22948 (In: C 22454 CD-ROM) /10 /73 / ITRD E114735
Source

In: From vision to reality : proceedings of the 7th World Congress on Intelligent Transportation Systems ITS, Turin, Italy, 6-9 November 2000, 9 p., 6 ref.

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This publication is one of our other publications, and part of our extensive collection of road safety literature, that also includes the SWOV publications.