Dynamic Air Route Open-Close Problem for Airspace Management

Dynamic airspace management plans and assigns airspace resources to airspace users on demand to increase airspace capacity. Although many studies of air traffic flow management （ATFM） have sought to optimally allocate air traffic to get the best use of given airspace resources, few studies have focused on how to build an efficient air traffic network or how to adjust the current network in real time. This paper presents an integer program model named the dynamic air route open-close problem （DROP）. DROP has a cost-based objective function which takes into account constraints such as the shortest occupancy time of routes, which are not considered in ATFM models. The aim of DROP is to determine which routes will be opened to a certain user during a given time period. Simulation results show that DROP can facilitate utilization of air routes. DROP, a simplified version of an air traffic network constructing problem, is the first step towards realizing dynamic airspace management. The combination of ATFM and DROP can facilitate decisions toward more reasonable, efficient use of limited airspace resources.

Review on artificial intelligence techniques for improving representative air traffic management capability

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.

A study on basic research priorities and development suggestions for the digital transformation of air traffic management

Air traffic is exhibiting the characteristics of high density,high volume,and unmanned operations.To ensure smooth,efficient,safe,and reliable operations,it is necessary to promote the digital transformation of Air Traffic Management(ATM)with digitalization,autonomy,and collaboration as its typical features.This article,based on the background of current and foreseeable future ATM needs,deeply analyzes the challenges and opportunities faced by traditional ATM.It explores and proposes to further investigate the commonalities,characteristics,and evolution of air traffic,the interaction mechanism of"human-machine-environment"in air traffic,the integrated design of airborne avionics and ATM systems,the comprehensive integration of ATM based on vulnerability analysis,airspace classification management,air traffic flow management,key technologies of"perception-collision avoidance",wake vortex monitoring and interval reduction,unmanned aerial vehicle management,and the expansion of ATM capabilities in the"high frontier".The research suggests strengthening top-level planning,building an open,mutually beneficial,and win-win digital ATM ecological framework based on multi-party collaboration,coordinating the research and application of new digital ATM technologies,accelerating the occupation of the new track of low-altitude economy,and enhancing ATM capabilities driven by the digital transformation of ATM.

Civil unmanned aircraft system operation in national airspace: A survey from Air Navigation Service Provider perspective

Unmanned Aircraft Systems(UASs) have advanced technologically and surged exponentially over recent years. Currently, due to safety concerns, most civil operations of UAS are conducted in low-level uncontrolled area or in segregated controlled airspace. As the industry progresses, both operational and technological capabilities have matured to the point where UASs are expected to gain greater freedom of access to both controlled and uncontrolled airspace. Extensive technical and regulatory surveys have been conducted to enable the expanded operations. However, most surveys are derived from the perspective of UAS own operating mechanism and barely consider interactions of their non-segregated activities with the Air Traffic Management(ATM) system. Hence, to fill the gap, this paper presents a survey conducted from the perspective of Air Navigation Service Provider(ANSP), which serves to accommodate these new entrants to the overall national airspace while continuing flight safety and efficiency. The primary objectives of this paper are to:(A) describe what typical ANSP-supplied UAS Traffic Management(UTM) architecture is required to facilitate all types of civil UAS operations;(B) identify three major ANSP considerations on how UAS can be accommodated safely in civil airspace;(C) outline future directions and challenges related with UAS operations for the ANSP.

Dynamic Air-Route Adjustments——Model,Algorithm,and Sensitivity Analysis

Dynamic airspace management （DAM） is an important approach to extend limited air space resources by using them more efficiently and flexibly. This paper analyzes the use of the dynamic air-route adjustment （DARA） method as a core procedure in DAM systems. DARA method makes dynamic decisions on when and how to adjust the current air-route network with the minimum cost. This model differs from the air traffic flow management （ATFM） problem because it considers dynamic opening and closing of air-route segments instead of only arranging flights on a given air traffic network and it takes into account several new constraints, such as the shortest opening time constraint. The DARA problem is solved using a two-step heuristic algorithm. The sensitivities of important coefficients in the model are analyzed to determine proper values for these coefficients. The computational results based on practical data from the Beijing ATC region show that the two-step heuristic algorithm gives as good results as the CPLEX in less or equal time in most cases.