J. Ren, Shiru Qu, Lili Wang, Yu Wang, Tingting Lu, Lijing Ma
{"title":"Research on en route capacity evaluation model based on aircraft trajectory data","authors":"J. Ren, Shiru Qu, Lili Wang, Yu Wang, Tingting Lu, Lijing Ma","doi":"10.3934/era.2023087","DOIUrl":null,"url":null,"abstract":"For the sake of refined assessment of airspace operation status, improvement of the en route air traffic management performance, and alleviation of the imbalance of demand-capacity and airspace congestion, an en route accessible capacity evaluation model (based on aircraft trajectory data) is proposed in this paper. Firstly, from the perspective of flux, the en route capacity is defined and expanded from a two-dimensional concept to a three-dimensional concept. Secondly, based on the indicators of spatial flow and instantaneous density, an evaluation model of en route capacity is given. Finally, a case study is performed to validate the applicability and feasibility of the model. Results show that the en route accessible capacity, instantaneous density, and spatial flow can describe the temporal and spatial distribution of air traffic flow more precisely, as compared to the conventional indicators, such as route capacity, density, and flow. The proposed model envisages three innovations: (ⅰ) the definition of airspace accessible capacity with reference to capacity of road traffic, (ⅱ) the computation model for flux-based airspace accessible capacity and en route accessible capacity, and (ⅲ) two indicators of en route characteristics named instantaneous density and spatial flow are introduced for evaluating the micro-state of the en route. Furthermore, because of the capacity depiction of the spatial and temporal distribution of air traffic congestion within an airspace unit, this model can also help air traffic controllers balance the distribution of traffic flow density, reduce the utilization rate of horizontal airspace, and resolve flight conflicts on air routes in advance.","PeriodicalId":48554,"journal":{"name":"Electronic Research Archive","volume":null,"pages":null},"PeriodicalIF":1.0000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Electronic Research Archive","FirstCategoryId":"100","ListUrlMain":"https://doi.org/10.3934/era.2023087","RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MATHEMATICS","Score":null,"Total":0}
引用次数: 0
Abstract
For the sake of refined assessment of airspace operation status, improvement of the en route air traffic management performance, and alleviation of the imbalance of demand-capacity and airspace congestion, an en route accessible capacity evaluation model (based on aircraft trajectory data) is proposed in this paper. Firstly, from the perspective of flux, the en route capacity is defined and expanded from a two-dimensional concept to a three-dimensional concept. Secondly, based on the indicators of spatial flow and instantaneous density, an evaluation model of en route capacity is given. Finally, a case study is performed to validate the applicability and feasibility of the model. Results show that the en route accessible capacity, instantaneous density, and spatial flow can describe the temporal and spatial distribution of air traffic flow more precisely, as compared to the conventional indicators, such as route capacity, density, and flow. The proposed model envisages three innovations: (ⅰ) the definition of airspace accessible capacity with reference to capacity of road traffic, (ⅱ) the computation model for flux-based airspace accessible capacity and en route accessible capacity, and (ⅲ) two indicators of en route characteristics named instantaneous density and spatial flow are introduced for evaluating the micro-state of the en route. Furthermore, because of the capacity depiction of the spatial and temporal distribution of air traffic congestion within an airspace unit, this model can also help air traffic controllers balance the distribution of traffic flow density, reduce the utilization rate of horizontal airspace, and resolve flight conflicts on air routes in advance.