Measuring the impact of traffic flow management on interarrival duration: An application of autoregressive conditional duration
| dc.contributor.author | Diana, Tony | |
| dc.date.accessioned | 2021-09-09T15:26:18Z | |
| dc.date.available | 2021-09-09T15:26:18Z | |
| dc.date.issued | 2014-11-17 | |
| dc.description.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. | en_US |
| dc.description.uri | https://www.sciencedirect.com/science/article/pii/S0969699714001410?via%3Dihub#! | en_US |
| dc.format.extent | 7 pages | en_US |
| dc.genre | journal articles | en_US |
| dc.identifier | doi:10.13016/m22p9c-lazk | |
| dc.identifier.citation | Diana, Tony; Measuring the impact of traffic flow management on interarrival duration: An application of autoregressive conditional duration; Journal of Air Transport Management, Volume 42, Pages 219-225, 17 November, 2015; https://doi.org/10.1016/j.jairtraman.2014.11.002 | en_US |
| dc.identifier.uri | https://doi.org/10.1016/j.jairtraman.2014.11.002 | |
| dc.identifier.uri | http://hdl.handle.net/11603/22974 | |
| dc.language.iso | en_US | en_US |
| dc.publisher | Elsevier | en_US |
| dc.relation.isAvailableAt | The University of Maryland, Baltimore County (UMBC) | |
| dc.relation.ispartof | UMBC Data Science Collection | |
| dc.rights | This item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author. | en_US |
| dc.rights | Public Domain Mark 1.0 | * |
| dc.rights | This work was written as part of one of the author's official duties as an Employee of the United States Government and is therefore a work of the United States Government. In accordance with 17 U.S.C. 105, no copyright protection is available for such works under U.S. Law | |
| dc.rights.uri | http://creativecommons.org/publicdomain/mark/1.0/ | * |
| dc.title | Measuring the impact of traffic flow management on interarrival duration: An application of autoregressive conditional duration | en_US |
| dc.type | Text | en_US |