Aircraft route forecasting under adverse weather conditions

Hauf, T.; Hupe, Patrick; Sauer, Manuela; Rokitansky, Carl-Herbert; Lang, Jürgen; Sacher, Danièl; Chan, Pak Wai; Sakiew, Ludmila

doi:10.1127/metz/2016/0786

Cited by 4 publications

(1 citation statement)

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“…It is also shown that the stronger the headwind, the higher the airborne delay that can be realized. Hauf et al (2017) forecast deviation routes through a field of storms for arriving and departing aircraft. They use storm nowcasts (i.e.…”

Section: Study Backgroundmentioning

confidence: 99%

Wind Effect Analysis on Air Traffic Congestion in Terminal Area via Cellular Automata

Enayatollahi

Atashgah

2018

Aviation

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The behavior of any traffic flow is sensitive to the speed pattern of the vehicles involved. The heavier the traffic, the more sensitive the behavior is to speed changes. Focusing on air traffic flow, weather condition has a major role in the deviations of aircraft operational speed from the desired speed and causes surplus delays. In this paper, the effects of wind on delays in a terminal area are analyzed using a Cellular Automaton (CA) model. Cellular automata are discrete models that are widely used for simulating complex emerging properties of dynamic systems. A one-dimensional cellular array is used to model the flow of the terminal traffic into a wind field. The proposed model, due to the quickness and acceptable level of accuracy, can be utilized online in the tactical phase of air traffic control processes and system-level decision-makings, where quick response and system behavior are needed. The modeled route is an RNAV STAR route to Atlanta International Airport. The model is verified by real traffic data in a non-delayed scenario. Based on simulation results, the proposed model exhibits an acceptable level of accuracy (3–15% accuracy drop), with worthy time and computational efficiency (about 2.9 seconds run time for a 2-hour operation).

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Section: Study Backgroundmentioning

confidence: 99%