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Air Route Network Node Optimization Based On Traffic Flow Feature

Posted on:2017-04-02Degree:MasterType:Thesis
Country:ChinaCandidate:Q Y LiFull Text:PDF
GTID:2322330503495629Subject:Transportation planning and management
Abstract/Summary:PDF Full Text Request
The vigorous development of civil aviation transportation industry has been strongly promoted the prosperity of social economy. It also exposed the structure defect of Air Route Node(ARN for short) which made each segment overwhelmed, caused the airspace congestion, flight delays and impacted air traffic safety. In order to solve the aforementioned problems, the layout of ARN was adjusted.Combining with the background and research status of ARN planning, this paper analyzed the environment of the ARN optimization, concluded the substance of modeling, and then boiled the ARN optimization down to the layout of Air Route Network Node(ARNN for short) in "Fragmented" airspace. Based on an economical and safe ARN, the total cost has been taken here as the objective function, and an ARN optimization model has been developed to circumvent the conditions of airspace restriction, ARN traffic capacity, and nonlinear coefficients. By introducing cellular automata, a square grid cellular space, Moore neighbors, and a fixed boundary, a set of rules for solving the ARN optimization model has been designed. The airport with the largest traffic in each of the nine flight information regions in mainland China was selected as the OD(Origin-Destination) demand. Based on current flight patterns, the model constructs 35 air routes and successfully avoids 144 PRDs(prohibited, restricted, and dangerous areas). Compared with the current air route network structure, the number of nodes is decreased by 48.84%, the total length of flight segments and air routes is decreased by 22.64% and 1.14% respectively, static nonlinear coefficients is decreased by 1.49% with changes in the total length of the air route network, and the total cost of the air route network is decreased by 6.22%. Node degree, the capacity of the node, dynamic nonlinear coefficient and utilization ratio are improved accordingly, verifying feasibility of model and algorithm. Using Java language depending on ArcGIS Engine secondary development, realize ARNN layout optimization simulation.
Keywords/Search Tags:ARN Optimization, Capacity, "Fragmented" airspace, ARNN, Cellular Automata
PDF Full Text Request
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