A Spatial-Temporal Network Perspective for the Propagation Dynamics of Air Traffic Delays

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 systems,delays can be magnified and propagated throughout these systems,resulting in the emergent behavior known as delay propagation.An understanding of delay propagation dynamics is pertinent to modern air traffic management.In this work,we present a complex network perspective of delay propagation dynamics.Specifically,we model air traffic scenarios using spatial–temporal networks with airports as the nodes.To establish the dynamic edges between the nodes,we develop a delay propagation method and apply it to a given set of air traffic schedules.Based on the constructed spatial-temporal networks,we suggest three metrics-magnitude,severity,and speed-to gauge delay propagation dynamics.To validate the effectiveness of the proposed method,we carry out case studies on domestic flights in the Southeastern Asia region(SAR)and the United States.Experiments demonstrate that the propagation magnitude in terms of the number of flights affected by delay propagation and the amount of propagated delays for the US traffic are respectively five and ten times those of the SAR.Experiments further reveal that the propagation speed for US traffic is eight times faster than that of the SAR.The delay propagation dynamics reveal that about six hub airports in the SAR have significant propagated delays,while the situation in the United States is considerably worse,with a corresponding number of around 16.This work provides a potent tool for tracing the evolution of air traffic delays.

Collision risk assessment of reduced aircraft separation minima in procedural airspace using advanced communication and navigation

With the advancement of Communication,Navigation and Surveillance(CNS)technolo-gies such as space-based Automatic Dependent Surveillance-Broadcast/Contract(ADS-B/C),large separation minima may be reduced in procedural airspaces.It is of great significance to know the upper limit of the Reduced Separation Minima(RSM)for a procedural airspace and the corre-sponding consequences on collision risk with specifics of the advanced ADS-B and control interven-tion model.In this work,an interactive software is first developed for collision risk estimation.This software integrates the International Civil Aviation Organization(ICAO)collision risk models for lateral and longitudinal collision risk calculation for the Singapore procedural airspace.Results demonstrate that the lateral and longitudinal collision risk of Singapore procedural airspace with respect to current control procedures meets the ICAO Target Level of Safety(TLS)standard.Moreover,the feasibility of reducing the horizontal separations implemented in the Singapore pro-cedural airspace with respect to advanced CNS techniques is investigated.It is found that if advanced CNS technologies are applied,then the current 50-NM lateral and longitudinal separa-tion standards can be reduced to 22 NM(1 NM=1.825 km)and 20 NM,respectively,to meet the TLS standards based on current demand.A method is then devised to expand the traffic demand by p for p∈[10%,200%].It is found that the minimum lateral and longitudinal separa-tions can be reduced from 50 NM to be within the range of[23,31]NM,and 20 NM,respectively,for p∈[10%,200%],while the collision risk still meets the TLS standards.

An evolutionary computational framework for capacity-safety trade-off in an air transportation network

Airspace safety and airport capacity are two key challenges to sustain the growth in Air Transportation. In this paper, we model the Air Transportation Network as two sub-networks of airspace and airports, such that the safety and capacity of the overall Air Transportation network emerge from the interaction between the two. We propose a safety-capacity trade-off approach,using a computational framework, where the two networks can inter-act and the trade-off between capacity and safety in an Air Transport Network can be established. The framework comprise of an evolutionary computation based air traffic scenario generation using a flow capacity estimation module(for capacity), Collision risk estimation module(for safety) and an air traffic simulation module(for evaluation). The proposed methodology to evolve air traffic scenarios such that it minimizes collision risk for given capacity estimation was tested on two different air transport network topologies(random and small-world) with the same number of airports. Experimental results indicate that though airspace collision risk increases almost linearly with the increasing flow(flow intensity) in the corresponding airport network, the critical flow depend on the underlying network configuration. It was also found that, in general, the capacity upper bound depends not only on the connectivity among airports and their individual performances but also the configuration of waypoints and mid-air interactions among conflicts. Results also show that airport network can accommodate more traffic in terms of capacity but the corresponding airspace network cannot accommodate the resulting traffic flow due to the bounds on collision risk.