Comparative Analysis of Domestic Airline Network Risks in Typical Time Periods

Yan Pei Li and Hang Li ()
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Yan Pei Li: Civil aviation university of china, School of Safety Science and Engineering
Hang Li: Civil aviation university of china, School of Safety Science and Engineering

A chapter in Proceedings of the 10th Annual Meeting of Risk Analysis Council of China Association for Disaster Prevention (RAC 2022), 2023, pp 254-261 from Springer

Abstract: Abstract With the rapid development of China's civil aviation industry, the scale and complexity of the air transportation network are increasing, and the spatial and temporal heterogeneity of the network structure is becoming more and more prominent. It is of great significance to study the route network structure of a specific time scale for the fine management of civil aviation transportation and the improvement of risk prevention and control level. Based on the complex network theory, the weighted route network is constructed by collecting the route data of China's civil aviation in summer and autumn season, winter and spring season, Spring Festival and National Day respectively, considering the flight volume. The degree distribution, average shortest path, clustering coefficient index at the whole network level, degree centrality and betweenness centrality index at the node level are used to make a comparative analysis of the route network structure in the typical period. The simulation results show that China's airline network shows the characteristics of "dense in southeast and sparse in northwest", and the cumulative distribution shows the characteristics of "long tail", no matter in the season or in important holidays. At the same time, the key airports of the airline network are slightly different in summer and autumn season, winter and spring season, Spring Festival and National Day. According to the network characteristics of specific time periods, it is necessary to improve the risk prevention and control ability of the corresponding key airports in response to disasters and improve the safe operation level of the whole system.

Keywords: weighted route network; typical time period; degree centrality; Betweenness centrality (search for similar items in EconPapers)
Date: 2023
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DOI: 10.2991/978-94-6463-194-4_36

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