Induction Of Evolutionary Algorithms And Artificial Immune Game Based On The Path

With the increasing of mechanization level and the promoting of urbanization in our country, traffic congestion problems have become increasingly prominent in cities, especially in the core areas of them, which puts difficulty into the urban traffic management, and also makes the driver’s travel delays increase and travel efficiency reduce. Within the actual traffic network of the urban, traffic managers and drivers constitute the protagonist of the game, which, in the meanwhile, is also between the system optimal and users optimal. From the view of system optimal, the traffic managers release route guidance information, to guide the drivers-in-way to select the paths dynamically, to distribute the traffic flow and keep roads load balanced; while the driver, from the point of the user optimal, makes the optimal path from the starting point to the destination, to reduce the individual travel cost. In addition, traffic congestion of traffic network within a certain region, is that the speed of accumulation of traffic flow of peripheral network exceeds the dissipation rate inside, and, in other words, it is vehicles in transit continues to increase but no effective path to lead to congestion increasingly, and whose principle is similar to immune response in the biological immune system. In order to solve the problems above, this paper proposes the optimization algorithm of path induction based on evolutionary game theory and artificial immune.First of all, this paper takes the urban road network as the research object and improving the accommodating degree of road network and the efficiency of traffic route guidance information as the goal, through the game analysis of two aspects between urban traffic managers and drivers and the research of route choice behavior of the drivers, and constructs a simple evolutionary game model functioned by traffic path guidance information.Secondly, on the basis of the theory of artificial immune system, this paper will take the traffic network of the core area of urban traffic network as the body of the artificial immune system, the periphery invading driver-groups or driver-groups in the body as antigen, and the path guidance information released by traffic managers and the drivers-in-way as antibodies or immune cells, then analyze traffic immune mechanism under " the binary participation, the tripartite game", and put forward the optimization algorithm of path guidance based on the evolutionary game theory and artificial immune. Finally, compiled with C language we shall implement the algorithm program designed by this paper, and through the secondary development tools of GISDK embed into the applications of simulation software Transmodeler, so as to realize the functions of simulation software expansion; and applied into the traffic network of the core area of Baoshan city, simulations are conducted to verify the algorithm, whose results demonstrate the validity and feasibility of this algorithm.