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Airspace and air traffic management
Published in Lucy Budd, Stephen Ison, Air Transport Management, 2020
Controlled airspace can further be categorised as being a control zone, a control area, a terminal control area or an airway depending on its location and the function it performs: Control zones (CTZs) are located around certain aerodromes, and ATC is provided to all flights. CTZs extend upwards from the ground surface to a specific upper limit which varies according to location.A control area (CTA) is usually located above a control zone between defined flight levels.
Airport capacity management
Published in Gert Meijer, Fundamentals of Aviation Operations, 2020
The Terminal Control Area (TCA, or TMA: Terminal Maneuvering Area) is the connection between the airport and the ‘airways’. It is the space in which arriving aircraft are continuously being put in sequence for landing. The better this sequencing is done, the more aircraft can land on a runway until the maximum landing capacity of the runway is reached due to the requirement that no more than one aircraft may occupy a runway in use for landing. It is also the area where departing aircraft climb and ‘fan-out’ from the take-off runway in the direction of their intended flight path.
Cognitive Engineering: Designing for Situation Awareness
Published in Eduardo Salas, Aaron S Dietz, Situational Awareness, 2017
Rasmussen differentiated two levels for understanding the essential properties of a problem—functional purpose and abstract function. The functional purpose level describes the goals and values that constrain performance in a functional system. The goals are defining attributes of a system. Most complex systems have a few global goals that often pose conflicting demands on the humans within the system. In commercial aviation the goals might be to transport passengers from one location to another in a safe, convenient, comfortable, and profitable way while operating within the boundaries established by legislation, union agreements, and company strategy. In tactical aviation, the goals might be maximum damage to a target with minimal collateral damage to self and civilians. Obviously, the goals often come into conflict. The safest, most convenient, and most comfortable means of transporting passengers will not always be the most profitable. Thus, a value system provides the context for judgments about what is safe enough, convenient enough, comfortable enough, and profitable enough. In a similar way, combat pilots must weigh the probability of destroying targets against the risks to themselves and to civilians. Trade-offs among the various goals obviously must be considered in the design and management of the system (e.g., in determining regulations for minimum separations between aircraft within a terminal control area, or in determining rules of engagement for tactical aircraft). In addition, these goals and the related value systems provide an important context for every decision and action made within the system. For example, the pilot must weigh passenger safety against convenience and profit when deciding the appropriate response to threatening weather or an engine malfunction. It would be impossible to fully understand and evaluate a pilot’s performance without some knowledge of the goals and value systems that constrain that performance.
An efficient algorithm for solving the system optimisation problem in transportation
Published in International Journal of Systems Science, 2020
Han Yun-xiang, Huang Xiao-qiong
In this section, we study different cases to demonstrate the performance and effectiveness of the proposed method. First, we describe the basic setup of experimental verification, then discuss each experimental process and give the corresponding conclusions. Shanghai International Airport is one of the busiest airports in the world. The available data in its terminal control area includes ADS-B records. The airspace structure considered in the case study is shown in Figure 2, which highlights nine departure routes, each of which has a specific length. In addition, it is assumed that each departure route has a unique starting point with a fixed configuration. For PIKAS, both 22D and 24D use the same fix. In order to calculate the demand of departure routes in the area under consideration, air traffic controllers need the transit time between each location point and the requested route. These values are shown in Table 1. When departure aircraft approaches the exit fix, the aircraft is handed off from a terminal control area controller to area control centre controllers, and it begins following the corresponding standard instrument departure (SID) route. This section presents numerical results obtained by the proposed optimisation algorithm discussed in section 2 for various configurations of departure routes. To evaluate the model efficiency introduced in this study, we compared the analysis results with different process time (Han et al., 2017).
Leverage points: insights from a field study in the air traffic control system
Published in Theoretical Issues in Ergonomics Science, 2020
Stathis Malakis, Tom Kontogiannis
Approach control units employ a planning controller who establishes the overall plan for the entry and exit of aircraft in the Terminal Control Area (TMA) and an executive controller who communicates and controls the aircraft in the TMA and carries out the overall traffic plan. The planning controller also coordinates with adjacent units, such as area control and airport control, to manage the transfer of aircraft in accordance to prescribed procedures (i.e. Letters of Agreement). When traffic builds up to high levels or an unusual event comes up, the executive controller informs the planning controller to manage changes in priorities. The separation minima for our approach control unit were 5 nautical miles (Nm) horizontally and 1000 ft vertically.
Hybrid simulated annealing and reduced variable neighbourhood search for an aircraft scheduling and parking problem
Published in International Journal of Production Research, 2020
Shuang Zheng, Zhen Yang, Zhengwen He, Nengmin Wang, Chengbin Chu, Haiyang Yu
Focusing on different aspects of airport services, studies on aircraft scheduling can be classified into three main categories: the Terminal Control Area (TCA) scheduling problem, airport runway scheduling problem, and airport stand scheduling problem.