Data-driven airport management enabled by operational milestones derived from ADS-B messages

M Schultz, J Rosenow, X Olive - Journal of Air Transport Management, 2022 - Elsevier
Standardized, collaborative decision-making processes have already been implemented at
some network-relevant airports, and these can be further enhanced through data-driven …

A deep reinforcement learning approach for airport departure metering under spatial–temporal airside interactions

H Ali, DT Pham, S Alam… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Airport taxi delays adversely affect airports and airlines around the world leading to airside
congestion, increased Air Traffic Controllers/Pilot workload, and adverse environmental …

Deep reinforcement learning based airport departure metering

H Ali, PD Thinh, S Alam - 2021 IEEE International Intelligent …, 2021 - ieeexplore.ieee.org
Airport taxi delays adversely affect airports and airlines around the world in terms of
congestion, operational workload, and environmental emissions. Departure Metering (DM) …

[PDF][PDF] Using deep learning method to predict taxi time of aircraft: A case of Hong Kong airport

N Li, QY Jiao, L Zhang, SC Wang - J. Aeronaut. Astronaut. Aviat, 2020 - researchgate.net
The increasing availability of A-CDM (Airport-Collaborative Decision system) data gives the
opportunity to better understand the airport ground operation. Taxi time, as one of the key …

Toward Greener and Sustainable Airside Operations: A Deep Reinforcement Learning Approach to Pushback Rate Control for Mixed-Mode Runways

H Ali, DT Pham, S Alam - IEEE Transactions on Intelligent …, 2024 - ieeexplore.ieee.org
Airside taxi delays have adverse consequences for airports and airlines globally, leading to
airside congestion, increased Air Traffic Controller/Pilot workloads, missed passenger …

Airport taxiway conflict detection method based on network topology

G Wang, T Tan - 2020 IEEE 2nd International Conference on …, 2020 - ieeexplore.ieee.org
Because of the movements of aircraft on the ground were difficult to predict, conflicts on the
taxiway could not be detected by the methods of conflict detection in the air. According to the …

Integrated airside landside framework to assess passenger missed connections with airport departure metering

H Ali, DT Pham, S Alam, M Schultz - 2022 - dr.ntu.edu.sg
Airport departure metering can contain airside congestion but it may adversely impact
scheduled gate assignments leading to passenger missed connections. Using an integrated …

Aircraft Ground Taxiing Deduction and Conflict Early Warning Method Based on Control Command Information

J Zhuge, H Liang, Y Zhang, S Li… - Transportation …, 2022 - journals.sagepub.com
Aircraft taxiing conflict is a threat to the safety of airport operations, mainly owing to human
error in control command information. To solve this problem, an aircraft taxiing deduction …

Identification of Key Risk Hotspots in Mega-Airport Surface Based on Monte Carlo Simulation

W Tian, X Zhou, J Yin, Y Li, Y Zhang - Aerospace, 2024 - mdpi.com
The complex layout of the airport surface, coupled with interrelated vehicle behaviors and
densely mixed traffic flows, frequently leads to operational conflict risks. To address this …

Data driven and learning based approaches for integrated landside airside operations optimization

H Ali - 2022 - dr.ntu.edu.sg
Asia has witnessed a meteoric rise in its air traffic in the last decade; leading the region to
experience the fastest air traffic growth, globally. However, air traffic infrastructure has not …