A Comparison Framework for Conflict Detection and Resolution Multi Agent Modeling Methods in Air Traffic Management

Nowadays air traffic density increased, thus existing air traffic management systems are not able to manage the massive capacities of air traffic perfectly. To solve problems in current air traffic management systems, the aviation industry focused on a new concept called Free flight. Nonetheless, the most important challenge in current air traffic management and especially in free flight is conflict detection and resolution between different aircrafts. So far a number of methods have been presented in order to automate air traffic management using multi agent systems technology. However, there has been a little discussion about the efficiency of these methods. Also, there has not been created a comprehensive comparison of these methods. In this paper, we presented a clear framework to categorization and comparing different multi agent models for conflict detection and resolution in air traffic management. Then, using this framework, we evaluated various proposed models. Our comparison framework is based on characteristic such as: agent selection (the entity which selected as Agent), agent’s actions, agents’ interaction method in the process of conflict detection and resolution, the strategy used in agents’ implementation, type of the multi agent system (pure multi agent system or combined), conflict detection method, conflict resolution method, Plan Dimensions, Maneuvers, and management the multiple aircrafts’ conflict. Document type: Articl

Autonomous terminal area operations for unmanned aerial systems

After many years of successful operation in military domains, Unmanned Aerial Systems (UASs) are generating significant interest amongst civilian operators in sectors such as law enforcement, search and rescue, aerial photography and mapping. To maximise the benefits brought by UASs to sectors such as these, a high level of autonomy is desirable to reduce the need for highly skilled operators. Highly autonomous UASs require a high level of situation awareness in order to make appropriate decisions. This is of particular importance to civilian UASs where transparency and equivalence of operation to current manned aircraft is a requirement, particularly in the terminal area immediately surrounding an airfield. This thesis presents an artificial situation awareness system for an autonomous UAS capable of comprehending both the current continuous and discrete states of traffic vehicles. This estimate forms the basis of the projection element of situation awareness, predicting the future states of traffic. Projection is subject to a large degree of uncertainty in both continuous state variables and in the execution of intent information by the pilot. Both of these sources of uncertainty are captured to fully quantify the future positions of traffic. Based upon the projection of future traffic positions a self separation system is designed which allows an UAS to quantify its separation to traffic vehicles up to some future time and manoeuvre appropriately to minimise the potential for conflict. A high fidelity simulation environment has been developed to test the performance of the artificial situation awareness and self separation system. The system has demonstrated good performance under all situations, with an equivalent level of safety to that of a human pilot