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Flight schedules are highly sensitive to delays and witness these events on a very frequent basis. In an interconnected and interdependent air transportation system, these delays can magnify and cascade as the flight itineraries progress, causing reactionary delays. The airlines, passengers and airports bear the negative economic implications of such phenomenon. The current research draws motivation from this behavior and develops a multi-agent based method to predict the reactionary delays of flights, given the magnitude of primary delay that the flights witness at the beginning of the itinerary. Every flight is modeled as an agent which functions in a dynamic airport environment, receives information about other agents and updates its own arrival and departure schedule. To evaluate the performance of the method, this paper carries out a case study on the flights in Southeast Asia, which covers eleven countries. The model is tested on a six-month ADS-B dataset that is collected for the calendar year 2016. Through the reactionary delay values predicted by the multi-agent based method, the flights are first classified as delayed or un-delayed in terms of departure. The classification results show an average accuracy of 80.7%, with a delay classification threshold of 15 minutes. Further, a delay multiplier index is evaluated, which is a ratio of the total delays (primary+reactionary delays) and the primary delays for each aircraft. The majority of delay multiplier values range between 1-1.5, which signifies that for except a few outliers, the primary delays do not significantly cascade into reactionary delays for the flights in Southeast Asia. The outliers represent scenarios where primary delays magnify and propagate as reactionary delays over subsequent flight legs. Therefore, the proposed method can assist in better flight scheduling by identifying itineraries which experience higher reactionary delays.INDEX TERMS Air traffic management, agent-based method, ground delay analysis, Southeast Asian airports, reactionary delays.

Continuous Descent Approaches (CDAs) can significantly reduce fuel burn and noise impact by keeping arriving aircraft at their cruise altitude for longer than during conventional approaches(to descend as late as possible)and then having them make a continuous descent to the runway at near idle thrust with no level flight segments. The CDA procedures are fixed routes that are vertically optimized. With the changing traffic conditions and variable noise abatement rules the benefits of CDA operations are not yet fully realized.In this paper we propose a methodology to generate aircraft-specific dynamic CDA routes that are both laterally and vertically optimized on given objectives (noise, emission and fuel) from an Initial Approach Fix (IAF) to Final Approach Fix (FAF). The methodology utilizes real-time aircraft position and defined objectives to generate CDA routes which can then be converted into a set of artificial waypoints for continuous descent in transition airspace. The methodology involves discretizing the terminal airspace into concentric cylinders with artificial waypoints and uses enumeration and elimination (based on aircraft performance envelope) from one waypoint to other to identify all the possible routes. For each transition a variety of metrics including noise, emission and fuel burn are computed. From the resulting set of possible CDA routes, those routes are identified that represent the best trade-off on the given objectives. One of these routes is then used to dynamically update the flight route for executing the CDA procedure.For noise we used The Overall Sound Pressure Level (OPSL) and for emissions we used four pollutants , , 2 and . The dynamic CDA algorithm is implemented in a high-fidelity simulator ATOMS for Sydney Terminal Area with 34L as arrival runway for a Melbourne-Sydney flight (B737-400 aircraft, CFM56-3C-1 engines with a nominal weight of 58000 kg). The dynamic CDA routes are then compared on noise, emission and fuel burn with same flight conducting a typical CDA procedure (MANFA ONE Arrival) at the Sydney airport. The results shows that the methodology generates 64 possible solutions (dynamic CDA routes) from IAF to FAF in the transition airspace, of which 5 solutions were non-dominated. Dynamic CDA approach shows a reduction of 14.96% in noise, 11.6% reduction in emission and 1.5% reduction in fuel burn when compared to a standard CDA trajectory.The paper also investigates the throughput capacity of transition airspace for multiple flights performing CDA operation. The methodology incorporates a delay algorithm which uses the flights' estimated time of arrival (ETA) at the IAF and then allocates them a conflict free CDA route by searching through available routes. The approach takes into account the aircraft category and corresponding time occupancy at each artificial waypoint of the proposed CDA routes and propagate delays back when conflict exists.