The Airport Operations Control Center (AOC) has a continuous need to monitor the operating status of airport runways. Runway operations are determined by air traffic control departments based on factors such as weather and flight pressure. Due to the current management and technology conditions, the AOC can only continuously observe runways periodically through equipment such as video surveillance and field radar to analyze and determine the operating status of runways, resulting in dispersed concentration and increased workload for duty officers. To meet the AOC’s needs for real-time monitoring of runway operating status, this paper uses real-time aircraft trajectory data (ADS-B) and combines airport runway area information to define identification sensing areas, builds a geographic information analysis model, realizes airport parallel runway identification, and flight take-off and landing details. Analysis, and then construct a runway operating status feature matrix; finally, according to the operating status matrix, realize the automatic identification and determination of multi-runway operating modes. Considering the variability of operating modes, this paper defines switching rules between different operating modes to ensure timely switching of operating mode identification and avoid misjudgment caused by accidental data. This method can provide the airport operating center with accurate and timely runway status monitoring data to improve the efficiency and safety management level of airport operation management.


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    Title :

    A Feature Analysis Based Automatic Recognition Method for Airport Multi-runway Operating States


    Contributors:
    Wang, Guangchao (author) / Zhang, Jian (author) / Chen, Liren (author) / Mao, Yanfeng (author)


    Publication date :

    2023-10-11


    Size :

    2677284 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English




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