Introduction to the theory of neural computation
Introduction to the theory of neural computation
Applications of Automatic Control Concepts to Traffic Flow Modeling and Control
Applications of Automatic Control Concepts to Traffic Flow Modeling and Control
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We present a neural method – based on the Hopfield net – for the modellingand control of over-saturated signalized intersections. The problem is to look, in real-time, for lights signal setting which minimize a given trafficcriterion such as waiting time. The use of the Hopfield model is straightforward justified by its optimization capabilities,especially its fast time computing (by its own dynamic), which is of a great interest inreal-time problems like the traffic control one. The original Hopfield algorithm is modified to take into account proper constraints ofthe traffic problem. This approach is illustrated by numerical examples oftraffic conditions generated by a simulator. We extend the method to urbannets of several interconnected intersections.