{"title":"Predicting pilot behavior during midair encounters using long short-term memory network","authors":"Yang Hu, Xiaoyan Wang","doi":"10.1177/09544100231198150","DOIUrl":null,"url":null,"abstract":"Characterized by the wide use of advanced automation and the introduction of new operation concepts, the future air transportation system will be more complex. Advanced pilot behavior models with improved capability are required to support the design and analysis of the midair encounter situations in the future air transportation system. This paper first filters midair encounter data from Automatic Dependent Surveillance-Broadcast (ADS-B) observations. Based on the acquired midair encounter data, a comprehensive pilot behavior model is proposed based on a multi-layer Long Short-Term Memory (LSTM) network. The model is designed for the purpose of enhancing the predicting capability of pilot behaviors in both horizontal and vertical planes. Finally, the performance of the proposed model to predict pilot behavior in both horizontal and vertical planes is studied through evaluating against realistic midair encounter situations.","PeriodicalId":54566,"journal":{"name":"Proceedings of the Institution of Mechanical Engineers Part G-Journal of Aerospace Engineering","volume":"42 1","pages":""},"PeriodicalIF":1.0000,"publicationDate":"2023-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the Institution of Mechanical Engineers Part G-Journal of Aerospace Engineering","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1177/09544100231198150","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, AEROSPACE","Score":null,"Total":0}
引用次数: 0
Abstract
Characterized by the wide use of advanced automation and the introduction of new operation concepts, the future air transportation system will be more complex. Advanced pilot behavior models with improved capability are required to support the design and analysis of the midair encounter situations in the future air transportation system. This paper first filters midair encounter data from Automatic Dependent Surveillance-Broadcast (ADS-B) observations. Based on the acquired midair encounter data, a comprehensive pilot behavior model is proposed based on a multi-layer Long Short-Term Memory (LSTM) network. The model is designed for the purpose of enhancing the predicting capability of pilot behaviors in both horizontal and vertical planes. Finally, the performance of the proposed model to predict pilot behavior in both horizontal and vertical planes is studied through evaluating against realistic midair encounter situations.
期刊介绍：
The Journal of Aerospace Engineering is dedicated to the publication of high quality research in all branches of applied sciences and technology dealing with aircraft and spacecraft, and their support systems. "Our authorship is truly international and all efforts are made to ensure that each paper is presented in the best possible way and reaches a wide audience.
"The Editorial Board is composed of recognized experts representing the technical communities of fifteen countries. The Board Members work in close cooperation with the editors, reviewers, and authors to achieve a consistent standard of well written and presented papers."Professor Rodrigo Martinez-Val, Universidad Politécnica de Madrid, Spain
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