Research Article Open Access

Collision Avoidance Modelling in Airline Traffic Based on the Change of Airplane Movements and Dynamic Clouds

Yudhi Purwananto1, Chastine Fatichah1, Waskitho Wibisono1, Ary Mazharuddin Shiddiqi1, Bagus Jati Santoso1, Radityo Anggoro1 and Nurlita Dhuha Fatmawati1
  • 1 Institut Teknologi Sepuluh Nopember, Indonesia


An Air Traffic Controller (ATC) system aims to manage airline traffic to prevent collision of the airplane, called the Collision Avoidance (CA). The study on CA, called Conflict Detection and Resolution (CDR), becomes more critical as the airline traffic has grown each year significantly. Previous studies used optimization algorithms for CDR and did not involve the presence of cumulonimbus clouds. Many such clouds can be found in tropical regions like in Indonesia. Therefore, involving such clouds in the CDR optimization algorithms will be significant in Indonesia. We developed a CDR-based CA modelling that involves the Cumulonimbus (CB) clouds by considering three airplane maneuvers, i.e., Velocity, angle Turn and Altitude level Change (VTAC). Our optimization algorithm is developed based on a Mixed-Integer Programming (MIP) solver due to its efficiency. This proposed algorithm requires two input data, namely the initial airplane and cloud states input and the flight parameter such as velocity, angle and altitude levels. The outputs of our VTAC optimization algorithm are the optimum speed, altitude and angle turn of an airplane that is determined based on the currently calculated variables. Extensive experiments have been conducted to validate the proposed approach and the experiment results show that collisions between airplanes and clouds can be avoided with minimum change of the initial airplane velocity, angle and altitude levels. The VTAC algorithm produced longer distance to avoid collision between airplanes by at least 1 Nautical Mile (NM) compared to the VAC algorithm. The addition of angle in the VTAC algorithm has improved the result significantly.

Journal of Computer Science
Volume 17 No. 1, 2021, 33-43


Submitted On: 1 September 2020 Published On: 20 January 2021

How to Cite: Purwananto, Y., Fatichah, C., Wibisono, W., Shiddiqi, A. M., Santoso, B. J., Anggoro, R. & Fatmawati, N. D. (2021). Collision Avoidance Modelling in Airline Traffic Based on the Change of Airplane Movements and Dynamic Clouds. Journal of Computer Science, 17(1), 33-43.

  • 1 Citations



  • Air Traffic Control
  • Collision Avoidance
  • Conflict Detection and Resolution
  • Sequential Mixed Integer Linear Optimization