Utilizing Regression Algorithms for ATS Route Forecasts

Dewansh Raheja (Air Traffic Management Research Institute, Nanyang Technological University, Singapore)
Y. X. LEE (Air Traffic Management Research Institute, Nanyang Technological University, Singapore)
Z. W. Zhong (School of Mechanical and Aerospace Engineering, Nanyang Technological University, Singapore)

Journal of ICT, Design, Engineering and Technological Science
Volume 1, Issue 1

Assuming the static nature of routes, our study aimed to employ traffic feedback results from European airspace design evaluation tool combined with econometric modelling to forecast air traffic on selected ATS routes in the ASEAN region. A case study involving evolution scenarios of the economy from 2004 to 2019 was used to show the importance of regression modelling and form an ATS route forecast procedure to illustrate current capabilities. The study findings show that the accumulation of flights over the airspace is likely to affect airway capacity and workload in the coming years. Thus, ATS route forecasts become necessary in order to meet such heavy traffic conditions and plan new ATS routes. The results of the study provide valuable insights on the ASEAN ATS route network and the future direction for efforts to prevent structure imbalances by increasing capacity or reducing demand.