Title :
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
fDate :
27 Jun-2 Jul 1994
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;
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
DOI :
10.1109/ICNN.1994.374775
