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.

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Low cost carriers usually operate from no-frills budget terminals which are designed for quick aircraft turnaround, faster passenger connections with minimal inter-gate passenger transfer times. Such operations are highly sensitive to factors such as aircraft delays, turnaround time and flight connection time and may lead to missed connections for self-connecting transfer passengers. In this paper, we propose a passenger-centric model to analyze the effect of turnaround times, minimum connection times and stochastic delays on missed connections of self-connecting passengers. We use Singapore Changi International Airport Terminal 4, which mainly caters to budget/low cost carriers, as a case study to demonstrate the impact of operational uncertainties on these passenger connections, considering an optimal gate assignment by using heuristic search for scheduled arrivals. The proposed model also incorporates reassignment of gates in the disrupted scenario to minimize spatial deviation from the optimized gate assignments. Results show that the chances of missed connections can be significantly reduced by operationally maintaining higher turnaround time and minimum connection time and by bringing down delays at the airport. Specifically, by maintaining the flight turnaround time at 50 min, minimum connection time at 60 min and by containing arrival delays within 70% of the current delay spread at Terminal 4, transfer passenger missed connections can be prevented for almost all the flights. The gate assignment method adopted in this study is generic and may help to identify the gates, which are more prone to missed connections given operational uncertainties under different flight scenarios. INDEX TERMS Low cost carrier, self-connecting passengers, missed connections, flight delays, gate reassignment.

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