Research On Combined Optimization Of Traffic Control And Dynamic Network Equilibrium Based On Game Theory

With the rapid development of national economy, traffic congestion is becoming more and more serious, especially in the big city. Traffic guidance and traffic signal control are an important means of traffic management and traffic control respectively. However, they are separated in most studies, which reduce its effectiveness. Therefore, simultaneously considering the traffic guidance and traffic signal control, this paper investigates the combinatorial optimization problem with respect to traffic control and dynamic network equilibrium, which can make full use of the existing traffic network and thus effectively reduce traffic congestion.Firstly, this paper establishes the dynamic user optimal model based on CTM and urban traffic signal control optimization model, and designs an effective algorithm respectively. Based on this, this paper establishes a combined bi-level model with regard to traffic control and dynamic network equilibrium based on game theory. The purpose of the lower level is realize network equilibrium, with dynamic network loading model based on CTM, which can reflect dynamic characteristics of traffic flow. In equilibrium, all used path costs are equal and minimized between each OD pair. Furthermore, the equilibrium model is transformed into a variational inequality problem, and thus the projection algorithm is used to solve the problem. The Higher level is traffic signal optimization model for minimizing total system travel cost, in which the constraint conditions include intersection green light times and phases, for minimizes total system travel cost. Genetic algorithm solution is used to solve the higher level problem. Finally, the projection algorithm and genetic algorithm are integrated to solve the bi-level model, and numerical examples are provided to verify its effectiveness.