Distributed Air Traffic Control Research Articles

Landing system of a swarm of small unmanned aerial vehicles

The distributed information-measurement and management landing system is proposed to ensure safe landing of a swarm of small unmanned aerial vehicles on a robotic platform. The requirements for the proposed landing system are developed and the system structure diagram is presented. It includes a distributed air traffic control and management system in the landing zone, a space-time unmanned aircraft holding area with an ordered toroidal structure, and a buffer landing zone. When a small unmanned aerial vehicle leaves a holding area for a landing line, it is recommended to use multiple access protocols. The paper specifies the combination of the main elements of the landing system structure diagram, the pattern and features of their functioning, and develops a generalized algorithm for managing a swarm of small unmanned aerial vehicles in the information-measurement and management landing system.

A framework for modelling dependable real-time distributed systems

A systematic way to introduce fault-tolerant and time-dependent properties into a complex software system is presented. The approach is based on an extended Petri Net model, called the G-Net, enhanced with a deterministic timing scheme. In the Timed G-Net (TGN) model, exception handling and timing mechanisms are used to introduce fault-tolerant and real-time properties. The basic idea is to use basic building blocks with timing properties to allow objects to treat a timing error by raising an exception and triggering some corrective actions. Using TGNs as these basic building blocks, we fur titer refine the model into a Smart Object (SMO) model. In each SMO, a TGN specification associated with a set of attributes, monitor/error-handler links and protocols support the construction of more reliable applications through an automatic transformer. This framework can contribute to alleviating the burden on the developers in designing a complex real-time dependable system. We use examples to show that a simplified real-time distributed air traffic control system can be modelled effectively using the SMO model.

Distributed artificial intelligence approach to air traffic control

The idea of distributed planning and problem solving as a reliable and effective methodology for air traffic control is introduced. Some basic concepts and terminology of distributed planning are first discussed, then a novel coordinator-coworker structure is described; this is a control mechanism that can dynamically reorganise the planning system in response to the task at hand. The information structure supporting such a control mechanism is made up of hierarchically organised distributed scratch pads. It also provides the basis for ‘self-repairing’ when individual nodes fail to operate, and allows for a graceful degradation of the whole system. The problems of air traffic control are analysed and the kernel design of the airborne processors in a location-centred co-operative planning system is described. The simulation-based planning process and its timing and selection considerations are explained. Three different organisational structures are implemented: the local centralised archi tecture, and the location-centred co-operative planning system with one- and two-level co ordinator-coworker hierarchies. The vehicle of the empirical studies, the distributed air traffic control testbed, is then introduced, and performance mea sures of the three organisational structures are compared in it. Finally, the design and the results of a series of experiments performed are discussed.