{"title":"Metrics to Characterize Airport Operational Performance Using Surface Surveillance Data","authors":"H. Khadilkar, H. Balakrishnan","doi":"10.2514/ATCQ.21.2.183","DOIUrl":null,"url":null,"abstract":"Detailed surface surveillance datasets from sources such as the Airport Surface Detection Equipment, Model-X (ASDE-X) can potentially be used to analyze airport operations, in addition to their primary purpose of enhancing safety. This paper describes how surface surveillance data can be used to measure airport performance characteristics in three different ways: charactering surface flows, including identification of congestion hotspots, queue dynamics and departure throughput; developing metrics to evaluate the daily operational performance; and developing metrics to gauge long-term performance across different runway configurations and operating conditions. The proposed metrics have been developed with active feedback from operations personnel at Boston Logan International Airport, and are therefore evaluated and discussed using this airport as an example. These metrics can provide useful feedback on operational performance to airport operators, and, therefore, have the potential to improve the efficie...","PeriodicalId":221205,"journal":{"name":"Air traffic control quarterly","volume":"2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Air traffic control quarterly","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2514/ATCQ.21.2.183","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
Detailed surface surveillance datasets from sources such as the Airport Surface Detection Equipment, Model-X (ASDE-X) can potentially be used to analyze airport operations, in addition to their primary purpose of enhancing safety. This paper describes how surface surveillance data can be used to measure airport performance characteristics in three different ways: charactering surface flows, including identification of congestion hotspots, queue dynamics and departure throughput; developing metrics to evaluate the daily operational performance; and developing metrics to gauge long-term performance across different runway configurations and operating conditions. The proposed metrics have been developed with active feedback from operations personnel at Boston Logan International Airport, and are therefore evaluated and discussed using this airport as an example. These metrics can provide useful feedback on operational performance to airport operators, and, therefore, have the potential to improve the efficie...