Airport is arguably one of the most complex system in existing transportation facilities that is operated by diverse group and stakeholder and is much influenced by external factors. For example, in the event of a plane, facilities and other airport accidents, responsible stakeholder involved in the accidents are greater than any other transportation areas. Despite the importance of robust maintenance of the facility, in recent years, we are observing signs of increase in possibility of airport operation failure due to rapid increase in aviation demand, growing expectations of aviation services, and increase in automation and connection systems with the introduction of advanced systems.
Republic of Korea is not the only country that is experiencing these issues. United States of America (USA) and United Kingdom (UK) has also experienced these issues in the past. In order to resolve the problem, they have shifted away from responding to the emergency situation and they have introduced airport irregular operations when responding to disrupted normal flight schedules. Such efforts are also being made in Korea to improve efficiency of airport operations and implementation of management systems to prevent and respond to serious accidents. However, there are no specific definition and methodology to determine airport irregular operations and ripple effects for predictive and preemptive response since detailed studies has not been conducted. In order to solve these problems, following study took incremental approach to newly define the airport irregular operations by distinguishing terms between emergency situation and normal situation. Furthermore, the study suggests a methodology for identifying the concept of the matrix based on severity and duration rather than cause. The index of the airport operating system was set up as the increase of the delay time and a tool was developed to simulate the delay situation based on the actual operation data of the individual airport. We conducted simulation for airports located in Jeju, Gimpo, and Gimhae Airport where air traffic congestion is greater than other airports in Korea to establish classification of airport irregular operation based on unsupervised learning of the results.
A scenario analysis was carried out to verify the constructed methodology assuming that the airport irregular operations occur. In addition, we have verified characteristics of constructed model through ensemble learning, which is a type of supervised learning method, and confirmed its applicability. It was difficult to apply constructed classification model directly due to the data limitation but the study suggested potential applicability in the future once we accumulate more data and refine methodology.
For the policy utilization, we examined current airport irregular operation response system in Korea and conducted a survey for passengers related to flight delays and cancellations. The result has suggested that policy consideration is needed to improve the response system rather than focusing on improvement of facilities. It is also imperative to gain more information to satisfy customers and passengers in the airport. The developed methodology in this study can be utilized as a tool to meet these policy needs.
The study suggests alternatives to emergency response system with manual and the necessity of maximizing the effectiveness of the response system through the introduction of the BCP concept and a specific plan for the group decision making process. Moreover, the study briefly reviewed the quantitative expectation effect through preemptive response to the airport irregular operations and analyzed the social benefits.
Finally, the study comprehensively covers development of basic analytical methodology based on the policy needs of stakeholder in airport operation, and its application to policies such as system and manual improvement. The approach suggested in this study is different to the existing approach, so it is necessary to enhance publicity and a bond of sympathy, implement the learning method and develop the manual for the airport irregular operations through the actual verification and data accumulation. We expect airport operations seamless through preemptive and predictive response with described above.