{"title":"机场会不会挤塞?以纽约三大机场为例","authors":"Tony Diana","doi":"10.2514/ATCQ.17.2.173","DOIUrl":null,"url":null,"abstract":"In this study, the author first presents a methodology for identifying congested hours. The author next examines how delays in key airport operational variables my affect the odds of congestion. The author then uses count data regression analysis for identifying the factors most likely to predict the number of delayed airport departures and arrivals. Summer 2007 data from Newark Liberty International, New York John F. Kennedy International, and New York LaGuardia airports are used in the study. The author concludes that management of taxi operations and total available capacity are key to minimizing the existence of congestion.","PeriodicalId":221205,"journal":{"name":"Air traffic control quarterly","volume":"75 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Can Airport Congestion be Anticipated? A Case Study of the Three Largest New York Airports\",\"authors\":\"Tony Diana\",\"doi\":\"10.2514/ATCQ.17.2.173\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this study, the author first presents a methodology for identifying congested hours. The author next examines how delays in key airport operational variables my affect the odds of congestion. The author then uses count data regression analysis for identifying the factors most likely to predict the number of delayed airport departures and arrivals. Summer 2007 data from Newark Liberty International, New York John F. Kennedy International, and New York LaGuardia airports are used in the study. The author concludes that management of taxi operations and total available capacity are key to minimizing the existence of congestion.\",\"PeriodicalId\":221205,\"journal\":{\"name\":\"Air traffic control quarterly\",\"volume\":\"75 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-04-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Air traffic control quarterly\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2514/ATCQ.17.2.173\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Air traffic control quarterly","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2514/ATCQ.17.2.173","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Can Airport Congestion be Anticipated? A Case Study of the Three Largest New York Airports
In this study, the author first presents a methodology for identifying congested hours. The author next examines how delays in key airport operational variables my affect the odds of congestion. The author then uses count data regression analysis for identifying the factors most likely to predict the number of delayed airport departures and arrivals. Summer 2007 data from Newark Liberty International, New York John F. Kennedy International, and New York LaGuardia airports are used in the study. The author concludes that management of taxi operations and total available capacity are key to minimizing the existence of congestion.
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