A route-based network simulation framework for airport ground system disruptions. (October 2018)

• Record Type: Journal Article
• Authors: Damgacioglu, Haluk; Celik, Nurcin; Guller, Alyssa
• Is Part Of: Computers & industrial engineering. Volume 124(2018)
• Page Start: 449
• Page End: 461
• Publication Date: 2018-10
• Subjects: Airport resilience -- Airport ground management -- Network simulation -- Runway distance -- Taxiway congestion modeling; Engineering -- Data processing -- Periodicals; Industrial engineering -- Periodicals; 620.00285
• DOI: 10.1016/j.cie.2018.07.029
• Languages: English
• ISSNs: 0360-8352

Abstract

Highlights: Our route-based network simulation framework (RuNSim) mimics airport ground system. Network simulation is used to evaluate the airport's resilience for the first time. RuNSim provides quantitative analysis for airport ground system disruptions. LaGuardia Airport is selected as a case study to show capabilities of RunSim. Damage on the taxiway network and runway closure cases are assessed in detail. Abstract: Every year, delayed, cancelled, or diverted flights cost airports significant man-hours and millions of dollars all over the world. The Airlines for America reported that the total direct aircraft operating cost per block minute was $62.55 in 2016, and at this rate, delay minutes cost more than $7 billion in aircraft operations for scheduled US passenger airlines only. Keeping flights on schedule only becomes more difficult with today's ever increasing demand for air transportation and disruptive events including natural and human-caused hazards. In this study, we analyze the adversarial impact of such disruptive events on an airport ground system using a route-based network simulation framework (RuNSim). Aiming to increase an airport's ability to take quick, responsive actions against disruptions leading to flight delays and cancellations, RuNSim is comprised of four modules: (1) pre-processing, (2) runway simulation, (3) route-based taxiway simulation, and (4) apron simulation. Our proposed framework incorporates technical as well as regulatory constraints for safety and system uncertainties. The capabilities of the proposed approach are demonstrated through two different case studies based on real data obtained from the LaGuardia Airport ground system. In these case studies, two disruptive events, namely taxiway pavement network damage and runway closure, are investigated in terms of their impact on taxi-in and taxi-out times. Conclusions are drawn on the adverse impacts of these events on the airport ground network along with available actions to minimize such flight delays under these events.