Dynamic traffic signal control using a self-learning fuzzy-neural intelligent system.

Author(s)
Wu, J. Zhou, W.-W. Miska, E. & Dong, Z.
Year
Abstract

This paper introduces an adaptive and self-learning intelligent traffic signal control system for networks or corridor applications. It is aimed at meeting the requirements of dynamic traffic optimal control. The system is developed based on intelligent fuzzy modeling, fuzzy-neural algorithms and traffic delay minimization algorithms. It consists of two major parts: off-line and on-line. In the off-line part, traffic flow patterns are identified using a fuzzy clustering algorithm. In the on-line part, real time traffic data is acquired through field traffic controllers. (A)

Request publication

3 + 1 =
Solve this simple math problem and enter the result. E.g. for 1+3, enter 4.

Publication

Library number
C 8729 (In: C 8665 e) /10 /73 / IRRD 872610
Source

In: Transportation : total customer satisfaction : proceedings of the 1995 Transportation Association of Canada TAC annual conference, Victoria, British Columbia, October 22-25, 1995, Volume 5, p. B25-B43, 13 ref.

Our collection

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