Urban Traffic Flow Prediction and Assignment with Dynamic Programming

In view of the uncertainty of the complex urban traffic system,this paper presents a traffic flow prediction and assignment method with dynamic programming.The model is developed by considering the capacity limitation in each section of the road network.In this model,the newly-added restraint condition is transferred by introducing punishment function,and the fine characters of traditional assignment model are maintained.Then,the algorithm is documented,in which Frank-Wolfe algorithm is combined with the punishment function.The control strategy consists of prediction control,feedback correction,and rolling optimization.Finally,a numerical example is used to illustrate the availability of the proposed method which provides reference for traffic flow prediction and assignment.