Freeway ramp metering using artificial neural networks

This paper proposes a nonlinear approach for designing local traffic-responsive ramp controls using artificial neural networks. The problem is formulated as a nonlinear feedback control problem, where the system model is the well known hydrodynamic model developed by Lighthill and Whitham, and Richards, the model's flow–density relationship is nonlinear, and the feedback nonlinear controllers are composed of one of a number of feed-forward neural networks. These neural network controllers are of integral (I) or proportional-plus-integral (PI) type, and can be tuned on-line to achieve prescribed performance. Initial simulation results show that such an approach is promising.