Applying digital twins for the management of information in turnaround event operations in commercial airports

J Conde, A Munoz-Arcentales, M Romero… - Advanced Engineering …, 2022 - Elsevier
The aerospace sector is one of the many sectors in which large amounts of data are
generated. Thanks to the evolution of technology, these data can be exploited in several …

A computer vision framework using convolutional neural networks for airport-airside surveillance

P Thai, S Alam, N Lilith, BT Nguyen - Transportation Research Part C …, 2022 - Elsevier
Modern airports often have large and complex airside environments featuring multiple
runways, with changing configurations, numerous taxiways for effective circulation of flights …

A review of sustainability in aviation: A multidimensional perspective

D Guimarans, P Arias, M Tomasella, CL Wu - … transportation and smart …, 2019 - Elsevier
The notable growth of air transportation in recent years has led to increasingly congested
airports and airspace. Working at nearly maximum capacity involves risks that normally …

Machine learning approach to predict aircraft boarding

M Schultz, S Reitmann - Transportation Research Part C: Emerging …, 2019 - Elsevier
Reliable and predictable ground operations are essential for punctual air traffic movements.
Uncertainties in the airborne phase have significantly less impact on flight punctuality than …

[HTML][HTML] A spatial–temporal network perspective for the propagation dynamics of air traffic delays

Q Cai, S Alam, VN Duong - Engineering, 2021 - Elsevier
Intractable delays occur in air traffic due to the imbalance between ever-increasing air traffic
demand and limited airspace capacity. As air traffic is associated with complex air transport …

Airport surface movement prediction and safety assessment with spatial–temporal graph convolutional neural network

X Zhang, S Zhong, S Mahadevan - Transportation research part C …, 2022 - Elsevier
Collisions during airport surface operations can create risk of injury to passengers, crew or
airport personnel and damage to aircraft and ground equipment. A machine learning model …

Simulation-based turnaround evaluation for Lelystad Airport

MM Mota, G Boosten, N De Bock, E Jimenez… - Journal of Air Transport …, 2017 - Elsevier
The airport of Lelystad in North Holland will be upgraded to attract commercial traffic from
Schiphol. In this paper we present the simulation-based analysis for Lelystad Airport with the …

Reviewing the DATAS of aviation research data: Diversity, availability, tractability, applicability, and sources

MZ Li, MS Ryerson - Journal of Air Transport Management, 2019 - Elsevier
The field of aviation research is entering the era of big data. While data-driven
advancements in aviation have clearly brought about applicable models and results with …

Process Mining for resilient airport operations: a case study of Munich Airport's turnaround process

J Rott, F König, H Häfke, M Schmidt, M Böhm… - Journal of air transport …, 2023 - Elsevier
The aviation industry has faced significant challenges in recent years, including a
punctuality crisis in 2018/19 and the ongoing impact of COVID-19 on operations since …

Using serious games and simulations for teaching co-operative decision-making

IA Ștefan, JB Hauge, F Hasse, A Ștefan - Procedia Computer Science, 2019 - Elsevier
Teaching students and training employees for management responsibilities, enabling
acquisition of new skills, of knowledge and experiences to better respond to market and job …