Research On The Public Traffic Network Hierarchical Optimization Of Xi’an Ancient City Area Based On Accessibility

As the ancient Chang’an District, Xi’an ancient city area is the core area of modern Xi’an, centrally reflects the characteristic of Xi’an and the features of the ancient capital. The development of the ancient city area is inseparable from rational urban traffic planning. To establish a suitable and complete public transport system of ancient city area is one of the most important measures to coordinate relations between the protection and development, and to promote sustainable and healthy development of the ancient city area.Xi’an ancient city area is the enclosed area of Ming Dynasty city wall of the city centre. This paper takes conventional public transit as the research object, analyzes the public transit problem due to the progress of urbanization and the excessive concentration of urban functions, puts forward the necessity of the public traffic network hierarchical optimization of ancient city area. The author collects the information of 208 bus lines and 1406 bus stations, builds the complex public traffic network model of Xi’an by Matlab method, uses Floyd algorithm from the stop complex network model and the changing complex network model of public traffic network to solve the topological distance between any two stations and to calculate every station’s shortest path index. The author selects accessibility as the grading hierarchy standard for bus stations, introduces betweenness into accessibility measurement, and calculates the betweenness index of every bus station from the stop complex network model and the changing complex network model by using Ucinet, builds the modified model of accessibility topological measurement, then calculates every bus station’s Accessibility Index(AI) of Xi’an, takes station accessibility from Beiyuanmen, Sanxuejie, Qixianzhuang historic district as the example to study the bus station accessibility of ancient city area. Dividing the bus stations of ancient city area into three categories after analyzing their AI by using SPSS, and then classify public traffic network into three layers based on the present public transit situation, analysis the features of each layer. Setting different optimized goals to every layer according to their different optimization features, build different models, and get the optimized route collection by applying ant colony algorithm and VC platform. Adjusting the bus lines of ancient city area, get optimizing ancient city area main route, sub trunk, feeder route. Finally, take transfer numbers as the evaluation of public transport networks, compare the difference between before and after the optimizing adjustment, to prove that average transfer number decreases after public transportation network optimization, operational efficiency and service levels of the transit system get upgraded.The study is supported by the Midwest Historic City Protection and Reconstruction of Historic District Space Transportation Planning Theory and Methods Research Fund(National Natural Science Foundation, NO.51278396).