{"title":"通过灰狼优化的轨迹调整来减轻移动部门的空中交通复杂性","authors":"Simon Bruno Göppel, Ehsan Asadi, Michael Schultz","doi":"10.1016/j.trc.2025.105176","DOIUrl":null,"url":null,"abstract":"<div><div>This study introduces a novel approach to optimizing air traffic complexity within moving sectors, a concept designed for flow-centric air traffic management. Moving sectors dynamically allocate controller workload by grouping aircraft with similar trajectories and interactions. A trajectory adjustment method is proposed, incorporating Grey Wolf Optimization, to reduce traffic complexity through minor lateral path modifications. This approach maintains operational constraints, such as handover times, while ensuring minimal disruption to aircraft trajectories. Two case studies demonstrate significant improvements, with reductions in average traffic complexity of up to 27% and peak complexity loads of up to 30%. These findings highlight the potential of flow-centric procedures to enhance airspace capacity, ensuring safety and efficiency in future air traffic management systems.</div></div>","PeriodicalId":54417,"journal":{"name":"Transportation Research Part C-Emerging Technologies","volume":"178 ","pages":"Article 105176"},"PeriodicalIF":7.6000,"publicationDate":"2025-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Trajectory adjustments via grey wolf optimization to mitigate air traffic complexity in moving sectors\",\"authors\":\"Simon Bruno Göppel, Ehsan Asadi, Michael Schultz\",\"doi\":\"10.1016/j.trc.2025.105176\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>This study introduces a novel approach to optimizing air traffic complexity within moving sectors, a concept designed for flow-centric air traffic management. Moving sectors dynamically allocate controller workload by grouping aircraft with similar trajectories and interactions. A trajectory adjustment method is proposed, incorporating Grey Wolf Optimization, to reduce traffic complexity through minor lateral path modifications. This approach maintains operational constraints, such as handover times, while ensuring minimal disruption to aircraft trajectories. Two case studies demonstrate significant improvements, with reductions in average traffic complexity of up to 27% and peak complexity loads of up to 30%. These findings highlight the potential of flow-centric procedures to enhance airspace capacity, ensuring safety and efficiency in future air traffic management systems.</div></div>\",\"PeriodicalId\":54417,\"journal\":{\"name\":\"Transportation Research Part C-Emerging Technologies\",\"volume\":\"178 \",\"pages\":\"Article 105176\"},\"PeriodicalIF\":7.6000,\"publicationDate\":\"2025-06-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Transportation Research Part C-Emerging Technologies\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0968090X25001809\",\"RegionNum\":1,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"TRANSPORTATION SCIENCE & TECHNOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Transportation Research Part C-Emerging Technologies","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0968090X25001809","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"TRANSPORTATION SCIENCE & TECHNOLOGY","Score":null,"Total":0}
Trajectory adjustments via grey wolf optimization to mitigate air traffic complexity in moving sectors
This study introduces a novel approach to optimizing air traffic complexity within moving sectors, a concept designed for flow-centric air traffic management. Moving sectors dynamically allocate controller workload by grouping aircraft with similar trajectories and interactions. A trajectory adjustment method is proposed, incorporating Grey Wolf Optimization, to reduce traffic complexity through minor lateral path modifications. This approach maintains operational constraints, such as handover times, while ensuring minimal disruption to aircraft trajectories. Two case studies demonstrate significant improvements, with reductions in average traffic complexity of up to 27% and peak complexity loads of up to 30%. These findings highlight the potential of flow-centric procedures to enhance airspace capacity, ensuring safety and efficiency in future air traffic management systems.
期刊介绍:
Transportation Research: Part C (TR_C) is dedicated to showcasing high-quality, scholarly research that delves into the development, applications, and implications of transportation systems and emerging technologies. Our focus lies not solely on individual technologies, but rather on their broader implications for the planning, design, operation, control, maintenance, and rehabilitation of transportation systems, services, and components. In essence, the intellectual core of the journal revolves around the transportation aspect rather than the technology itself. We actively encourage the integration of quantitative methods from diverse fields such as operations research, control systems, complex networks, computer science, and artificial intelligence. Join us in exploring the intersection of transportation systems and emerging technologies to drive innovation and progress in the field.