Taxi Event Extraction from Surveillance for Surface Performance Evaluation

Abstract

Estimated unimpeded taxi times can be used to quantify a flight’s taxiing delay when compared with its actual taxi time. Currently, flight unimpeded taxi times are calculated by the Federal Aviation Administration using a regression method where flights in the Aviation System Performance Metrics data are clustered on the season of operation, airline, airport, and calendar year. The method uses the airline-reported gate-Out, wheels-Off, wheels-On, gate-In (OOOI) times rounded to the nearest minute. For nonreporting airlines, these times are estimated from similar flights. The purpose of this paper is to evaluate the unimpeded time using a surveillance-based approach by identifying the time a flight spent waiting in the system and comparing with the total taxi time. This study focuses on analyzing both arrivals and departures for six U.S. airports (Atlanta, Charlotte, Denver, Houston, New York Kennedy, and Chicago O'Hare) during the month of July 2015. The study results show how the non-surveillance-based and surveillance-based metrics compare, with nonsurveillance methods including the current regression method and the 5th-to-15th clustering method described in current literature. The benefits of using surveillance information for surface performance are explored, as spatial analyses allow for quick identification of taxiway locations that were the most susceptible to delays.