Modeling Air Traffic Situation Complexity with a Dynamic Weighted Network Approach
In order to address the flight delays and risks associated with the forecasted increase in air traffic, there is a need to increase the capacity of air traffic management systems. This should be based on objective measurements of traffic situation complexity. In current air traffic complexity resear...
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| Format: | Article |
| Language: | English |
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Wiley
2018-01-01
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| Series: | Journal of Advanced Transportation |
| Online Access: | http://dx.doi.org/10.1155/2018/5254289 |
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| author | Hongyong Wang Ziqi Song Ruiying Wen |
| author_facet | Hongyong Wang Ziqi Song Ruiying Wen |
| author_sort | Hongyong Wang |
| collection | DOAJ |
| description | In order to address the flight delays and risks associated with the forecasted increase in air traffic, there is a need to increase the capacity of air traffic management systems. This should be based on objective measurements of traffic situation complexity. In current air traffic complexity research, no simple means is available to integrate airspace and traffic flow characteristics. In this paper, we propose a new approach for the measurement of air traffic situation complexity. This approach considers the effects of both airspace and traffic flow and objectively quantifies air traffic situation complexity. Considering the aircraft, waypoints, and airways as nodes, and the complexity relationships among these nodes as edges, a dynamic weighted network is constructed. Air traffic situation complexity is defined as the sum of the weights of all edges in the network, and the relationships of complexity with some commonly used indices are statistically analyzed. The results indicate that the new complexity index is more accurate than traffic count and reflects the number of trajectory changes as well as the high-risk situations. Additionally, analysis of potential applications reveals that this new index contributes to achieving complexity-based management, which represents an efficient method for increasing airspace system capacity. |
| format | Article |
| id | doaj-art-dd86e3c3396b440cbfa2eb7556124079 |
| institution | OA Journals |
| issn | 0197-6729 2042-3195 |
| language | English |
| publishDate | 2018-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Advanced Transportation |
| spelling | doaj-art-dd86e3c3396b440cbfa2eb75561240792025-08-20T02:21:33ZengWileyJournal of Advanced Transportation0197-67292042-31952018-01-01201810.1155/2018/52542895254289Modeling Air Traffic Situation Complexity with a Dynamic Weighted Network ApproachHongyong Wang0Ziqi Song1Ruiying Wen2Tianjin Key Laboratory for Air Traffic Operation Planning and Safety Technology, Civil Aviation University of China, Tianjin 300300, ChinaDepartment of Civil and Environmental Engineering, Utah State University, Logan, UT 84322, USATianjin Key Laboratory for Air Traffic Operation Planning and Safety Technology, Civil Aviation University of China, Tianjin 300300, ChinaIn order to address the flight delays and risks associated with the forecasted increase in air traffic, there is a need to increase the capacity of air traffic management systems. This should be based on objective measurements of traffic situation complexity. In current air traffic complexity research, no simple means is available to integrate airspace and traffic flow characteristics. In this paper, we propose a new approach for the measurement of air traffic situation complexity. This approach considers the effects of both airspace and traffic flow and objectively quantifies air traffic situation complexity. Considering the aircraft, waypoints, and airways as nodes, and the complexity relationships among these nodes as edges, a dynamic weighted network is constructed. Air traffic situation complexity is defined as the sum of the weights of all edges in the network, and the relationships of complexity with some commonly used indices are statistically analyzed. The results indicate that the new complexity index is more accurate than traffic count and reflects the number of trajectory changes as well as the high-risk situations. Additionally, analysis of potential applications reveals that this new index contributes to achieving complexity-based management, which represents an efficient method for increasing airspace system capacity.http://dx.doi.org/10.1155/2018/5254289 |
| spellingShingle | Hongyong Wang Ziqi Song Ruiying Wen Modeling Air Traffic Situation Complexity with a Dynamic Weighted Network Approach Journal of Advanced Transportation |
| title | Modeling Air Traffic Situation Complexity with a Dynamic Weighted Network Approach |
| title_full | Modeling Air Traffic Situation Complexity with a Dynamic Weighted Network Approach |
| title_fullStr | Modeling Air Traffic Situation Complexity with a Dynamic Weighted Network Approach |
| title_full_unstemmed | Modeling Air Traffic Situation Complexity with a Dynamic Weighted Network Approach |
| title_short | Modeling Air Traffic Situation Complexity with a Dynamic Weighted Network Approach |
| title_sort | modeling air traffic situation complexity with a dynamic weighted network approach |
| url | http://dx.doi.org/10.1155/2018/5254289 |
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