MPC in urban traffic management

More and more people are concerned about the negative phenomenon resulted by the negative effects of the growing traffic motorization. Traffic congestion is the primary direct impact which became everyday occurrence in the last decade. As world trade is continuously increasing, it is obvious that congestions represent also a growing problem. The capacity of the traffic networks saturates during rush hours. At the same time, the traditional traffic management is getting less effective in sustaining a manageable traffic flow. Therefore, external impacts appear causing new costs for the societies. As a possible solution the predictive control based strategy can be applied. The chapter investigates the applicability of MPC strategy specialized in urban traffic management in order to relieve traffic congestion, to reduce travel time and to improve homogeneous traffic flow. Over the theory the realization of the control method is also presented. Firstly we give a historical summary of adaptive traffic control. The brief results of MPC and its related methods in urban traffic control are presented. Then we introduce the modeling possibilities of urban traffic as the appropriate model means an important aspect of the control design. The use of MPC requires a state space theory approach. Therefore the so called Store-and-forward model is chosen which can be directly translated to state space. We analyze the model in details showing the real meaning of system matrices. The constraints of urban traffic system is also discussed which heavily influence modeling and control. The next section presents the simulation environment which is used to demonstrate the developed control methods. Thereinafter we present the main results of MPC in traffic application. The idea to apply MPC in urban traffic network is induced by the fact that the distance is relatively short between several intersections with traffic lights. Hence it is advisable to coordinate the operation of the intersection controller devices. Several intersections are near to each other in smaller or bigger networks, primarily in cities, the coordination is especially emphasized. The development of new control strategies is a real demand of nowadays. One of the possible solutions is the practical application of MPC. The aim of the control is to increase capacity. To test and validate our control strategy we apply it to a real-word transportation network where the actual system is not efficient enough to manage the traffic in rush hours. The simulation results show the effectiveness of the control design. After the presentation of the practical urban traffic MPC the distributive solution of MPC has to be discussed. As the computational demand depends on the size of the network an efficient calculation method is 11