TY - JOUR
T1 - Increasing airspace capacity by improving ATCo's efficiency through an innovative handover mechanism
AU - Borràs, Alfons
AU - Calvet Liñan, Laura
AU - Piera, Miquel Àngel
N1 - Publisher Copyright:
© 2024 The Author(s)
PY - 2024/10
Y1 - 2024/10
N2 - The current lack of airspace capacity poses a major challenge to a sustainable and efficient air transport system, especially as future demand increases. Recent efforts to increase airspace capacity have focused on airspace sectorization. The digitization of Air Traffic Management (ATM) holds promise for overcoming current inefficiencies arising from the spatial fragmentation of airspace. While research has explored digitized ATM services to improve airspace capacity, there has been a notable gap in addressing spare capacity through enhancing synergies between adjacent sectors. This work proposes the application of an early handover (EHO) mechanism based on the spatio-temporal interdependencies among sectors and aircraft. Essentially, the mechanism involves alleviating overloaded sectors by redistributing peak demand to neighboring ones. This alleviation results in a reduction of the dedicated resources required to meet demand, facilitating the consolidation of sectors into larger units. Ultimately, this consolidation enhances airspace efficiency by minimizing the ATCo resources necessary for ATM. A simple and fast heuristic is proposed to select the aircraft for early handover to the air traffic controller of another sector, together with a specific schedule. A Colored Petri Net model is implemented to formalize the dynamic spatio-temporal interdependencies among adjacent sectors and to illustrate the EHO applicability using an academic exercise for illustration purposes. Afterwards, a simulation study based on real European airspace data is employed to illustrate and validate the mechanism. Finally, a discussion on the potential impacts of adopting the mechanism in real-life applications and lines of future research are provided.
AB - The current lack of airspace capacity poses a major challenge to a sustainable and efficient air transport system, especially as future demand increases. Recent efforts to increase airspace capacity have focused on airspace sectorization. The digitization of Air Traffic Management (ATM) holds promise for overcoming current inefficiencies arising from the spatial fragmentation of airspace. While research has explored digitized ATM services to improve airspace capacity, there has been a notable gap in addressing spare capacity through enhancing synergies between adjacent sectors. This work proposes the application of an early handover (EHO) mechanism based on the spatio-temporal interdependencies among sectors and aircraft. Essentially, the mechanism involves alleviating overloaded sectors by redistributing peak demand to neighboring ones. This alleviation results in a reduction of the dedicated resources required to meet demand, facilitating the consolidation of sectors into larger units. Ultimately, this consolidation enhances airspace efficiency by minimizing the ATCo resources necessary for ATM. A simple and fast heuristic is proposed to select the aircraft for early handover to the air traffic controller of another sector, together with a specific schedule. A Colored Petri Net model is implemented to formalize the dynamic spatio-temporal interdependencies among adjacent sectors and to illustrate the EHO applicability using an academic exercise for illustration purposes. Afterwards, a simulation study based on real European airspace data is employed to illustrate and validate the mechanism. Finally, a discussion on the potential impacts of adopting the mechanism in real-life applications and lines of future research are provided.
KW - Airspace network efficiency
KW - Airspace network costs
KW - STAM mechanism
KW - Early handover
KW - Colored Petri net
KW - Simulation
UR - http://www.scopus.com/inward/record.url?scp=85202342443&partnerID=8YFLogxK
UR - https://www.mendeley.com/catalogue/272041e0-35d5-3762-a44e-71ec9f11cb74/
U2 - 10.1016/j.cie.2024.110513
DO - 10.1016/j.cie.2024.110513
M3 - Article
SN - 1879-0550
VL - 196
JO - Computers & industrial engineering (Online)
JF - Computers & industrial engineering (Online)
M1 - 110513
ER -