The use of artificial intelligence(AI)has increased since the middle of the 20th century,as evidenced by its applications to a wide range of engineering and science problems.Air traffic management(ATM)is becoming incr...The use of artificial intelligence(AI)has increased since the middle of the 20th century,as evidenced by its applications to a wide range of engineering and science problems.Air traffic management(ATM)is becoming increasingly automated and autonomous,making it lucrative for AI applications.This paper presents a systematic review of studies that employ AI techniques for improving ATM capability.A brief account of the history,structure,and advantages of these methods is provided,followed by the description of their applications to several representative ATM tasks,such as air traffic services(ATS),airspace management(AM),air traffic flow management(ATFM),and flight operations(FO).The major contribution of the current review is the professional survey of the AI application to ATM alongside with the description of their specific advantages:(i)these methods provide alternative approaches to conventional physical modeling techniques,(ii)these methods do not require knowing relevant internal system parameters,(iii)these methods are computationally more efficient,and(iv)these methods offer compact solutions to multivariable problems.In addition,this review offers a fresh outlook on future research.One is providing a clear rationale for the model type and structure selection for a given ATM mission.Another is to understand what makes a specific architecture or algorithm effective for a given ATM mission.These are among the most important issues that will continue to attract the attention of the AI research community and ATM work teams in the future.展开更多
目前,已经有许多的机遇速率的流量控制方法应用于 ABR 网络。这些方法中大多都能提高主动连接的公平性和连接利用率。同时,也给交换机带来更大的复杂性。本文中提出了一个流量控制方法,将部分速率计算工作从交换机转移到终端系统中进行...目前,已经有许多的机遇速率的流量控制方法应用于 ABR 网络。这些方法中大多都能提高主动连接的公平性和连接利用率。同时,也给交换机带来更大的复杂性。本文中提出了一个流量控制方法,将部分速率计算工作从交换机转移到终端系统中进行。结果表明,该方法能减少交换机的速率计算工作及交换复杂性,还降低了交换机在每一时间间隔内计算每条链路负载因子的难度,使占用队列长度保持在稳定状态。仿真结果表明该方法具有比 ERICA+算法更好的运行效果。展开更多
基金supported by the National Natural Science Foundation of China(62073330)the Natural Science Foundation of Hunan Province(2020JJ4339)the Scientific Research Fund of Hunan Province Education Department(20B272).
文摘The use of artificial intelligence(AI)has increased since the middle of the 20th century,as evidenced by its applications to a wide range of engineering and science problems.Air traffic management(ATM)is becoming increasingly automated and autonomous,making it lucrative for AI applications.This paper presents a systematic review of studies that employ AI techniques for improving ATM capability.A brief account of the history,structure,and advantages of these methods is provided,followed by the description of their applications to several representative ATM tasks,such as air traffic services(ATS),airspace management(AM),air traffic flow management(ATFM),and flight operations(FO).The major contribution of the current review is the professional survey of the AI application to ATM alongside with the description of their specific advantages:(i)these methods provide alternative approaches to conventional physical modeling techniques,(ii)these methods do not require knowing relevant internal system parameters,(iii)these methods are computationally more efficient,and(iv)these methods offer compact solutions to multivariable problems.In addition,this review offers a fresh outlook on future research.One is providing a clear rationale for the model type and structure selection for a given ATM mission.Another is to understand what makes a specific architecture or algorithm effective for a given ATM mission.These are among the most important issues that will continue to attract the attention of the AI research community and ATM work teams in the future.
文摘目前,已经有许多的机遇速率的流量控制方法应用于 ABR 网络。这些方法中大多都能提高主动连接的公平性和连接利用率。同时,也给交换机带来更大的复杂性。本文中提出了一个流量控制方法,将部分速率计算工作从交换机转移到终端系统中进行。结果表明,该方法能减少交换机的速率计算工作及交换复杂性,还降低了交换机在每一时间间隔内计算每条链路负载因子的难度,使占用队列长度保持在稳定状态。仿真结果表明该方法具有比 ERICA+算法更好的运行效果。
