Abstract
To scientifically evaluate the reliability of air traffic networks, a definition of air traffic network reliability is proposed in this paper. Calculation models of the connectivity reliability, travel-time reliability, and capacity reliability of the air traffic network are constructed based on collected historical data, considering the current status and the predicted future evolution trends. Considering the randomness and fuzziness of factors affecting reliability, a comprehensive evaluation model of air traffic networks based on the uncertainty transformation model is established. Finally, the reliability of the US air traffic network is analyzed based on data published by the Transportation Statistics Bureau of the US Department of Transportation. The results show that the connectivity reliability is 0.4073, the capacity reliability is 0.8300, the travel-time reliability is 0.9180, and the overall reliability evaluated is “relatively reliable”. This indicates that although the US structural reliability is relatively low, the US air traffic management is very efficient, and the overall reliability is strong. The reliability in nonpeak hours is much higher than that in peak hours. The method can identify air traffic network reliability efficiently. The main factors affecting reliability can be found in the calculation process, and are beneficial for air traffic planning and management. The empirical analysis also reflects that the evaluation model based on the uncertainty transformation model can transform the quantitative data of network structure and traffic function into the qualitative language of reliability.
Highlights
Reliability is an important feature of complex systems
Wang S J et al propose an improved triangle whitening weight function and use it to measure the reliability of air traffic controllers [13]
We introduce the uncertainty transformation model into the reliability evaluation method to achieve a balance between quality and quantity
Summary
Reliability is an important feature of complex systems. Many scholars have studied the reliability of different systems [1,2,3,4,5,6,7,8,9], such as composite materials [10], communication systems [11], and power systems [12]. Yuan L P and Zhang X J propose a method of determining the maximum influence value of the controller’s error based on Delphi and Bayesian networks and calculate the human error probability of flight conflict resolution [15]. Kirwan B et al determine human error probabilities by analyzing the results of a real-time simulation involving air traffic controllers (ATCOs) and pilots, with a focus on communication errors [16]. The second task is to comprehensively evaluate the reliability of the air traffic network based on the reliability indexes.
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