A hierarchical neural network approach to intelligent traffic control

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.<
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