{"title":"机场拥挤与登机口延误的关系","authors":"P.T.R. Wang, N. Tene, L. Wojcik","doi":"10.1109/DASC.2002.1067926","DOIUrl":null,"url":null,"abstract":"The relationship between airport congestion and passenger delays at an airport is determined by many factors. Among these factors are scheduled and actual flight times, flight itineraries, airport capacity, and turn around time between flights. From the existing recorded data, it is possible to present a general profile of both airport congestion and passenger delays, measured with respect to the published schedule, at major airports within the US. This paper illustrates the discrepancy between the two measurements. Airport congestion may be masked by flight schedules which account for routine arrival delays and/or with slack time provided for turn around at an airport. It is possible for an airport to be heavily utilized, with little or unnoticeable at-gate delays (measured with respect to scheduled arrival time). On the other hand, at-gate delays can occur at under-utilized airports. Arrival and departure queuing delays are better indicators of airport congestion than passenger delays. Average flight at-gate delays are derived from performance data and compared with simulation results for 30 of the busiest airports in USA for a good weather day. The effects of variations in schedule flight time and slack time are studied parametrically in the simulation and calibrated to match the recorded baseline national airspace system (NAS) delay profiles. This paper illustrates a technique for estimating NAS-wide impact of propagated flight delays, based upon a method for calibration a system-level simulation against real world delays as well as delays derived from other simulations.","PeriodicalId":190149,"journal":{"name":"Proceedings. The 21st Digital Avionics Systems Conference","volume":"56 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2002-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Relationship between airport congestion and at-gate delay\",\"authors\":\"P.T.R. Wang, N. Tene, L. Wojcik\",\"doi\":\"10.1109/DASC.2002.1067926\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The relationship between airport congestion and passenger delays at an airport is determined by many factors. Among these factors are scheduled and actual flight times, flight itineraries, airport capacity, and turn around time between flights. From the existing recorded data, it is possible to present a general profile of both airport congestion and passenger delays, measured with respect to the published schedule, at major airports within the US. This paper illustrates the discrepancy between the two measurements. Airport congestion may be masked by flight schedules which account for routine arrival delays and/or with slack time provided for turn around at an airport. It is possible for an airport to be heavily utilized, with little or unnoticeable at-gate delays (measured with respect to scheduled arrival time). On the other hand, at-gate delays can occur at under-utilized airports. Arrival and departure queuing delays are better indicators of airport congestion than passenger delays. Average flight at-gate delays are derived from performance data and compared with simulation results for 30 of the busiest airports in USA for a good weather day. The effects of variations in schedule flight time and slack time are studied parametrically in the simulation and calibrated to match the recorded baseline national airspace system (NAS) delay profiles. This paper illustrates a technique for estimating NAS-wide impact of propagated flight delays, based upon a method for calibration a system-level simulation against real world delays as well as delays derived from other simulations.\",\"PeriodicalId\":190149,\"journal\":{\"name\":\"Proceedings. The 21st Digital Avionics Systems Conference\",\"volume\":\"56 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2002-12-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings. The 21st Digital Avionics Systems Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/DASC.2002.1067926\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings. The 21st Digital Avionics Systems Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DASC.2002.1067926","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Relationship between airport congestion and at-gate delay
The relationship between airport congestion and passenger delays at an airport is determined by many factors. Among these factors are scheduled and actual flight times, flight itineraries, airport capacity, and turn around time between flights. From the existing recorded data, it is possible to present a general profile of both airport congestion and passenger delays, measured with respect to the published schedule, at major airports within the US. This paper illustrates the discrepancy between the two measurements. Airport congestion may be masked by flight schedules which account for routine arrival delays and/or with slack time provided for turn around at an airport. It is possible for an airport to be heavily utilized, with little or unnoticeable at-gate delays (measured with respect to scheduled arrival time). On the other hand, at-gate delays can occur at under-utilized airports. Arrival and departure queuing delays are better indicators of airport congestion than passenger delays. Average flight at-gate delays are derived from performance data and compared with simulation results for 30 of the busiest airports in USA for a good weather day. The effects of variations in schedule flight time and slack time are studied parametrically in the simulation and calibrated to match the recorded baseline national airspace system (NAS) delay profiles. This paper illustrates a technique for estimating NAS-wide impact of propagated flight delays, based upon a method for calibration a system-level simulation against real world delays as well as delays derived from other simulations.