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Measuring the impact of traffic flow management on interarrival duration: An application of autoregressive conditional duration
Affiliation:1. Department of General Physics, State Pedagogical University, Lenin St. 86, Voronezh 394043, Russia;2. Institute for Solid State Physics RAS, Chernogolovka, Moscow District 142132, Russia;3. NBIC-Centre, Kurchatov Institute, Kurchatov Sq. 1, 123182 Moscow, Russia;1. Hubei Collaborative Innovation Center for Advanced Organochemical Materials, Ministry-of-Education Key Laboratory for the Synthesis and Applications of Organic Functional Molecules, Hubei University, Wuhan 430062, China;2. Department of Physics, Pukyong National University, Busan 608-737, Republic of Korea;3. Department of Physics, Changwon National University, Changwon 641-773, Republic of Korea;1. College of Materials Science and Engineering, Nanjing Tech University, Nanjing 210009, PR China;2. DLG Power Battery (Zhangjiagang) Co., Ltd, Zhangjiagang 215600, PR China;1. PG – Ciência dos Materiais, Universidade Federal do Vale do São Francisco, 48902-300 Juazeiro, BA, Brazil;2. Instituto de Física, Universidade Federal Fluminense, 24210-346 Niterói, RJ, Brazil;1. University of Pennsylvania, Department of City and Regional Planning, 210 S 34th Street #102, Philadelphia, PA 19104, USA;2. University of Pennsylvania, Department of Electrical and Systems Engineering, 200 South 33rd Street, Philadelphia, PA 19104, USA
Abstract:The Federal Aviation Administration has several tools in its arsenal to manage traffic flows. However, it is very difficult to assess with certainty the impact of traffic flow management procedures such as Time-Based Flow Management (TBFM) or Traffic Management Initiatives (TMI) on airport performance because operational data are not readily available to analysts. This study uses the case of Fort Lauderdale–Hollywood International Airport (FLL) where traffic flow management procedures have been implemented to manage a reduction of airport capacity due to runway constructions. Based on an Autoregressive Conditional Duration (ACD) model, the analysis shows that the use of traffic flow management procedures contributed to reducing the volatility of interarrival duration whether separation relies on time-metering (TBFM) or distance between aircraft (TMI). The lessons learned from this case study may have important implications for airports whose available capacity is severely constrained.
Keywords:Autoregressive conditional duration  Airport capacity  Delay  Time-based flow management  Traffic management initiatives
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