A hierarchical neural network approach to intelligent traffic control

Author

Park, Sung Joo ; Yang, Jin Seol

Author_Institution

Dept. of Manage. Sci., Korea Adv. Inst. of Sci. & Technol., Taejon, South Korea

Volume

5

fYear

1994

fDate

27 Jun-2 Jul 1994

Firstpage

3358

Abstract

The goal of this work is to develop a hierarchical neural network (HNN) architecture for providing intelligent control of complex urban traffic networks which are usually nonlinear and hard to model mathematically. Two types of neural networks, such as a global planning network and local control networks, are employed for traffic modeling and control. The experimental results indicate that the control scheme has strong adaptive properties and it can be built with little knowledge about the signal operations

Keywords

intelligent control; neural nets; planning (artificial intelligence); road traffic; traffic control; traffic engineering computing; complex urban traffic networks; global planning network; hierarchical neural network; intelligent traffic control; local control networks; traffic modeling; Backpropagation; Communication system traffic control; Intelligent control; Intelligent networks; Mathematical model; Multi-layer neural network; Neural networks; Process control; Traffic control; Vehicle dynamics;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Networks, 1994. IEEE World Congress on Computational Intelligence., 1994 IEEE International Conference on

Conference_Location

Orlando, FL

Print_ISBN

0-7803-1901-X

Type

conf

DOI

10.1109/ICNN.1994.374775

Filename

374775