Freeway ramp metering using artificial neural networks

Abstract

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 (1955), and Richards (1956), the model's flow-density relationship is nonlinear, and the feedback nonlinear controllers are composed of one or 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.