{"title":"通过分配3d轨迹来分离空中交通流","authors":"D. Gianazza, Nicolas Durand","doi":"10.1109/DASC.2004.1391275","DOIUrl":null,"url":null,"abstract":"This paper introduces two algorithms which allocate optimal separated 3D-trajectories to the main traffic flows. The first approach is a 1 vs. n strategy which applies an A* algorithm iteratively to each flow. The second is a global approach using a genetic algorithm, applied to a population of trajectory sets. The algorithms are first tried on a toy problem, and then applied to real traffic data, using operational aircraft performances. The cumulated costs of the trajectory deviations are used to compare the two algorithms.","PeriodicalId":422463,"journal":{"name":"The 23rd Digital Avionics Systems Conference (IEEE Cat. No.04CH37576)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2004-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"17","resultStr":"{\"title\":\"Separating air traffic flows by allocating 3D-trajectories\",\"authors\":\"D. Gianazza, Nicolas Durand\",\"doi\":\"10.1109/DASC.2004.1391275\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper introduces two algorithms which allocate optimal separated 3D-trajectories to the main traffic flows. The first approach is a 1 vs. n strategy which applies an A* algorithm iteratively to each flow. The second is a global approach using a genetic algorithm, applied to a population of trajectory sets. The algorithms are first tried on a toy problem, and then applied to real traffic data, using operational aircraft performances. The cumulated costs of the trajectory deviations are used to compare the two algorithms.\",\"PeriodicalId\":422463,\"journal\":{\"name\":\"The 23rd Digital Avionics Systems Conference (IEEE Cat. No.04CH37576)\",\"volume\":\"38 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2004-10-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"17\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"The 23rd Digital Avionics Systems Conference (IEEE Cat. No.04CH37576)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/DASC.2004.1391275\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"The 23rd Digital Avionics Systems Conference (IEEE Cat. No.04CH37576)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DASC.2004.1391275","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 17
摘要
本文介绍了两种为主要交通流分配最优分离三维轨迹的算法。第一种方法是1 vs. n策略,它将a *算法迭代地应用于每个流。第二种是使用遗传算法的全局方法,应用于轨迹集的总体。这些算法首先在一个玩具问题上进行了试验,然后利用作战飞机的性能将其应用于真实的交通数据。用轨迹偏差的累积代价对两种算法进行比较。
Separating air traffic flows by allocating 3D-trajectories
This paper introduces two algorithms which allocate optimal separated 3D-trajectories to the main traffic flows. The first approach is a 1 vs. n strategy which applies an A* algorithm iteratively to each flow. The second is a global approach using a genetic algorithm, applied to a population of trajectory sets. The algorithms are first tried on a toy problem, and then applied to real traffic data, using operational aircraft performances. The cumulated costs of the trajectory deviations are used to compare the two algorithms.