A Causal STAM Model to Increase Airspace Network Capacity

ATM digitalization paves the way for new efficient solutions that overcomes present inefficiencies caused by spatial fragmented airspace. Lack of airspace capacity is an important factor that impacts on a sustainable and efficient air transport system with aggravated indicators in future growing demand scenarios. Despite research on new ATM digitalized services to improve airspace capacity, the mitigation of latent capacity by enhancing synergies among adjacent sectors has not been addressed yet. In this paper, spatio-temporal sector interdependencies are analyzed to quantify the topological interdependencies and evaluate the increment of capacity that can be achieved in those sectors that cannot fit the dynamic demand requirements. A sector network model has been implemented formalizing the ATC sectors as network nodes, and traffic flows at different levels of granularity as time-stamp perishable edges. The dynamic evolution of the occupancy in adjacent sectors together with the inverse correlation between saturated sectors, paves de way for a Short Term ATM Mechanism to improve the capacity invulnerability at sector level while at the same time provides a mechanism to improve the airspace capacity at network level.