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Aircraft taxiing trajectory prediction and conflict risk identification in airfield area based on AM-LSTM
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Xinglong WANG, Yanfeng XU
China Safety Science Journal | 2024, 34(1) : 116 - 124
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China Safety Science Journal | 2024, 34(1): 116-124
Safety engineering technology
Aircraft taxiing trajectory prediction and conflict risk identification in airfield area based on AM-LSTM
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Xinglong WANG, Yanfeng XU
Affiliations
  • Key Laboratory of Internet of Aircrafts,Civil Aviation University of China,Tianjin 300300,China
Published: 2024-01-28 doi: 10.16265/j.cnki.issn1003-3033.2024.01.1517
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In order to address the increasing risk of conflict caused by the difficulty in effectively predicting aircraft point source localization,a time series trajectory prediction model AM-LSTM based on AM and LSTM was constructed,to predict the instantaneous point source location of the aircraft in the airfield area in a short time in the future. On this basis,the contour was expanded according to the aircraft type and glide heading,the aircraft speed was used as the safety distance weight,and the ray method was used to realize the determination of the contour conflict. Urumqi Dewopu Airport was used as an example for validation,and the trained trajectory prediction model was utilized to predict aircraft taxiing trajectories in the airfield area and identified taxiing conflicts between aircraft profiles. The results show that the AM-LSTM prediction model can accurately predict the aircraft movement trajectory in the airfield area,and the average displacement error of the trajectory position prediction in the next 3 s is 1.05 m,and the accuracy of trajectory point position prediction can reach 94.37%. Therefore,it can accurately identify the risk of taxiing conflict on the basis of trajectory prediction,which is conducive to guaranteeing the safe operation of the airfield area.

attention mechanism(AM)  /  long short term memory(LSTM)  /  airfield area  /  aircraft taxiing  /  taxiing trajectory
Xinglong WANG, Yanfeng XU. Aircraft taxiing trajectory prediction and conflict risk identification in airfield area based on AM-LSTM[J]. China Safety Science Journal, 2024 , 34 (1) : 116 -124 . DOI: 10.16265/j.cnki.issn1003-3033.2024.01.1517
Year 2024 volume 34 Issue 1
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doi: 10.16265/j.cnki.issn1003-3033.2024.01.1517
  • Online Date:2025-07-09
  • Published:2024-01-28
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    Key Laboratory of Internet of Aircrafts,Civil Aviation University of China,Tianjin 300300,China
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表12种不同金属材料的力学参数

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Number of
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鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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