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Ui-Jeong Lee, Sang-Jun Ahn, Dong-Young Choi, Sang-Min Chin and Dae-Sung Jang
As the usability of and demand for unmanned aerial vehicles (UAVs) have increased, it has become necessary to establish a UAS traffic management (UTM) system for efficient UAV operations at low altitudes. To avoid collisions with ground obstacles, other ...
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Pei-Chi Shao
Resulting from a mature accomplishment of the unmanned aircraft system (UAS), it is feasible to be adopted into logistic delivery services. The supporting technologies should be identified and examined, accompanying with the risk assessment. This paper s...
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Nichakorn Pongsakornsathien, Suraj Bijjahalli, Alessandro Gardi, Angus Symons, Yuting Xi, Roberto Sabatini and Trevor Kistan
Recent evolutions of the Unmanned Aircraft Systems (UAS) Traffic Management (UTM) concept are driving the introduction of new airspace structures and classifications, which must be suitable for low-altitude airspace and provide the required level of safe...
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Shao Xuan Seah and Sutthiphong Srigrarom
This paper explores the use of deep reinforcement learning in solving the multi-agent aircraft traffic planning (individual paths) and collision avoidance problem for a multiple UAS, such as that for a cargo drone network. Specifically, the Deep Q-Networ...
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Chin E. Lin, Pei-Chi Shao and Yu-Yuan Lin
The hierarchical unmanned aerial systems (UAS) traffic management (UTM) is proposed for UAS operation in Taiwan. The proposed UTM is constructed using the similar concept of ATM from the transport category aviation system. Based on the airspace being div...
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Yibing Xie, Nichakorn Pongsakornsathien, Alessandro Gardi and Roberto Sabatini
Advances in the trusted autonomy of air-traffic management (ATM) systems are currently being pursued to cope with the predicted growth in air-traffic densities in all classes of airspace. Highly automated ATM systems relying on artificial intelligence (A...
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Seyed Mohammad Hashemi, Seyed Ali Hashemi, Ruxandra Mihaela Botez and Georges Ghazi
This paper presents a methodology for designing a highly reliable Air Traffic Management and Control (ATMC) methodology using Neural Networks and Peer-to-Peer (P2P) blockchain. A novel data-driven algorithm was designed for Aircraft Trajectory Prediction...
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Sugjoon Yoon, Dongcho Shin, Younghoon Choi and Kyungtae Park
In order to study air traffic control of UAS?s (Unmanned Aerial Systems) in very low altitudes, the UTM (UAS Traffic Management) simulator has to be as flexible and expandable as other research simulators because relevant technologies and regulations are...
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