Estimating economic severity of air traffic flow management regulations
The development of trajectory-based operations and the rolling network operations plan in
European air traffic management network implies a move towards more collaborative …
European air traffic management network implies a move towards more collaborative …
[HTML][HTML] Locally generalised multi-agent reinforcement learning for demand and capacity balancing with customised neural networks
Reinforcement Learning (RL) techniques are being studied to solve the Demand and
Capacity Balancing (DCB) problems to fully exploit their computational performance. A …
Capacity Balancing (DCB) problems to fully exploit their computational performance. A …
[HTML][HTML] Toward atm resiliency: A deep cnn to predict number of delayed flights and atfm delay
R Sanaei, BA Pinto, V Gollnick - Aerospace, 2021 - mdpi.com
The European Air Traffic Management Network (EATMN) is comprised of various
stakeholders and actors. Accordingly, the operations within EATMN are planned up to six …
stakeholders and actors. Accordingly, the operations within EATMN are planned up to six …
Efficient and fair traffic flow management for on-demand air mobility
The increased use of drones and air-taxis is expected to make airspace resources more
congested, necessitating the use of unmanned aircraft systems traffic management (UTM) …
congested, necessitating the use of unmanned aircraft systems traffic management (UTM) …
Aircraft and passenger recovery during an aircraft's unexpected unavailability
YN Yeti̇moğlu, MS Aktürk - Journal of Air Transport Management, 2021 - Elsevier
Airlines design their initial schedules under the assumption that all resources will be
available on time and flights will operate as planned. However, some disruptions occur due …
available on time and flights will operate as planned. However, some disruptions occur due …
[HTML][HTML] General multi-agent reinforcement learning integrating heuristic-based delay priority strategy for demand and capacity balancing
Reinforcement learning (RL) techniques have been studied for solving the demand and
capacity balancing (DCB) problem in air traffic management to exploit their full …
capacity balancing (DCB) problem in air traffic management to exploit their full …
Noise-Aware and Equitable Urban Air Traffic Management: An Optimization Approach
Urban air mobility (UAM), a transformative concept for the transport of passengers and
cargo, faces several integration challenges in complex urban environments. Community …
cargo, faces several integration challenges in complex urban environments. Community …
System Design and Operations of Package Delivery with Crowdshipping and Advanced Air Mobility
NP Farazi - 2024 - search.proquest.com
This dissertation presents methodological studies on designing, modeling, and evaluating of
package delivery systems that employ crowdshipping-and Advanced Air Mobility (AAM) …
package delivery systems that employ crowdshipping-and Advanced Air Mobility (AAM) …
Unearthing air traffic control officer strategies from simulated air traffic data
Z Zakaria, SW Lye - … , Emerging Technologies and Future Systems V …, 2022 - Springer
With the growth in air traffic volume, automation tools are being developed to increase the
capabilities of Air Traffic Control Officers (ATCOs). In this paper, a novel approach to unearth …
capabilities of Air Traffic Control Officers (ATCOs). In this paper, a novel approach to unearth …
[PDF][PDF] Resource-Constrained Airline Ground Operations: Optimizing Schedule Recovery under Uncertainty
J Evler - 2022 - core.ac.uk
Abstract Air Traffic Flow Management (ATFM) and airlines use different paradigms for the
prioritisation of flights. While ATFM regards each flight as individual entity when it controls …
prioritisation of flights. While ATFM regards each flight as individual entity when it controls …