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Francisco Javier Moreno Arboleda, Georgia Garani and Simon Zea Gallego
In this paper, a measure is proposed that, based on the trajectories of moving objects, computes the speed limit rate in each of the cells in which a region is segmented (the space where the objects move). The time is also segmented into intervals. In th...
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Yang Shen, Changjiang Zheng and Fei Wu
Urban highway tunnels are frequent accident locations, and predicting and analyzing road conditions after accidents to avoid traffic congestion is a key measure for tunnel traffic operation management. In this paper, 200 traffic accident data from the Yi...
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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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André Teixeira Silva, Sérgio Pedro Duarte, Sandra Melo, Adriana Witkowska-Konieczny, Michele Giannuzzi and António Lobo
This study explores attitudes towards urban air mobility (UAM) for e-commerce deliveries. UAM, which utilizes drones, has the potential to revolutionize transport services and logistics, leading to economic benefits and reductions in congestion and pollu...
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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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