Assessing the impact of tactical airport surface operations on airline schedule block time setting |
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| Affiliation: | 1. Department of Civil and Environmental Engineering, Institute of Transportation Studies, University of California, Berkeley, 107 McLaughlin Hall, Berkeley, CA 94720, USA;2. Department of Civil and Environmental Engineering, Institute of Transportation Studies, University of California, Berkeley, 114 McLaughlin Hall, Berkeley, CA 94720, USA;1. EURECOM, Communication System Department, Sophia Antipolis, France;2. Université Côte d’Azur, Inria, CNRS, LJAD, France;1. Department of Civil and Environmental Engineering, University of California, Berkeley, 107 McLaughlin Hall, Berkeley 94720, USA;2. Department of Civil and Environmental Engineering, University of California, Berkeley, 114 McLaughlin Hall, Berkeley, CA 94720, USA;3. University of California, Santa Cruz, NASA Ames Research Center, Moffett Field, CA 94035, USA;4. NASA Ames Research Center, Moffett Field, CA 94035, USA;1. College of Business, University of Nebraska-Lincoln, Lincoln, NE, United States;2. Isenberg School of Management, University of Massachusetts Amherst, Amherst, MA, United States |
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| Abstract: | ![]()
With the growth of air traffic, airport surfaces are congested and air traffic operations are disrupted by the formation of bottlenecks on the surface. Hence, improving the efficiency and predictability of airport surface operations is not only a key goal of NASA’s initiatives in Integrated Arrival/Departure/Surface (IADS) operations, but also has been recognized as a critical aspect of the FAA NextGEN implementation plan. While a number of tactical initiatives have been shown to be effective in improving airport surface operations from a service provider’s perspective, their impacts on airlines’ scheduled block time (SBT) setting, which has been found to have direct impact on airlines’ on-time performance and operating cost, have received little attention. In this paper, we assess this impact using an econometric model of airline SBT combined with a before/after analysis of the implementation of surface congestion management (SCM) at John F. Kennedy International Airport (JFK) in 2010. Since airlines do not consider gate delay in setting SBT, we find that reduction in taxi-out time variability resulting from SCM leads to more predictable taxi-out times and thus decreases in SBT. The JFK SCM implementation is used as a case study to validate model prediction performance. The observed SBT decrease between 2009 and 2011 at JFK is 4.8 min and our model predicts a 4.2 min decrease. In addition, Charlotte Douglas International Airport (CLT) is used as an example to demonstrate how different surface operations improvements scenarios can be evaluated in terms of SBT reduction. |
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| Keywords: | Airport surface operations Surface congestion management Scheduled block time Benefit assessment Taxi time variability |
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