Optimizing pushback decisions to valuate airport surface surveillance information

Pierrick Burgain, Olivia J. Pinon, Eric Feron, John Paul Clarke, Dimitri N. Mavris

Research output: Contribution to journalArticlepeer-review

21 Scopus citations

Abstract

As airport surface surveillance technologies develop, aircraft ground position information becomes more easily available and accurate. This paper provides a better understanding of the value of future surface surveillance systems where departures, and more specifically pushback times, will be optimized. It analytically quantifies the potential benefits yielded by providing surveillance information to the agent or system that is entrusted with tactically optimizing pushback clearances under nominal conditions. A stochastic model of surface operations is developed for single-ramp surface operations and calibrated to emulate departure surface operations at LaGuardia Airport. Two levels of information are examined within a tactically optimized collaborative decision-making framework. For each level, emissions, number of taxiing aircraft, and runway utilization rate are analyzed and compared with a simple threshold policy to evaluate surface surveillance information. Safety benefits, however, are not considered in this paper. It is estimated that optimally controlling pushback clearances from a single-ramp area using detailed surface surveillance information does not provide significant benefits when compared with controlling pushback clearances using a gate-holding policy based on the number of aircraft currently taxiing. However, when the runway is functioning at intermediate capacity (50%-72% runway utilization rates), e.g., under adverse weather conditions, surveillance information may improve optimization of departure operations. In such case, emissions and the number of taxiing aircraft are reduced by up to 6% when compared with the gate-holding policy and by up to 3% when compared with the performance of an intelligent operator with limited information. © 2011 IEEE.
Original languageEnglish (US)
Pages (from-to)180-192
Number of pages13
JournalIEEE Transactions on Intelligent Transportation Systems
Volume13
Issue number1
DOIs
StatePublished - Jan 1 2012
Externally publishedYes

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