Research On Layout Of City Traffic Congestion Processing Notes

With the rapid development of economy, urban expanding constantly and function improving, more residents have been attracted to city and most city population have exceeded ten million. The growing number of city population has brought tremendous pressure for urban transport infrastructure. Especially the increasing number of private cars has brought new challenges for the normal operation of urban traffic in recent years. Traffic congestion has gradually become a huge problem for the development of city.Xi’an is the transportation hub of western China, the starting point of the Silk Road City, has developed rapidly recent years, the increasing population and the growth number of motor vehicles have increased traffic pressure continuously. In order to solve the problems effectively, Xi ’an has do great effort developing urban public transport, promoting road infrastructure construction, strengthening urban traffic operation management. The measures have made some achievements, but still failed to solve the problem of traffic congestion fundamentally. Therefore, this article put forward to build urban congestion processing nodes. When someplace of the city occur congestion, processing person can arrive the congestion in quick and control the traffic, in order to restore the traffic in a short time.This paper introduces the relevant theories and the impact of traffic congestion first. Then analysis the traffic congestion of Xi’an through geographical position and the unique network structure of Xi’an, research into 95 nodes prone to traffic congestion and accordingly pick up 31 processing nodes. Based on the research of models about the facility location problem, added the relevant knowledge of urban traffic planning, traffic flow theory, traffic demand forecasting to establish location model for xi ’an traffic congestion processing nodes. Through analyzing and research on modern heuristic algorithm, using MATLAB software based on Genetic Algorithm to solve the model. Finally we can get 23 locations of processing nodes of Xi ’an traffic congestion and mainly responsible on specific congestion nodes.