Abstract
Urban Air Mobility (UAM) has the potential to revolutionize urban transportation. It will exploit the third dimension to help smooth ground traffic in densely populated areas. To be successful, it will require an organized and integrated approach able to balance efficiency and safety while harnessing common airspace resources. We believe that mathematical optimization will play an essential role to support the development of Urban Air Mobility. In this paper, we describe two important problems from this domain, operators 4D volume deconfliction, and air taxi trajectory deconfliction.
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Hamadi, Y. (2020). Optimization for Urban Air Mobility. In: Kotsireas, I., Pardalos, P. (eds) Learning and Intelligent Optimization. LION 2020. Lecture Notes in Computer Science(), vol 12096. Springer, Cham. https://doi.org/10.1007/978-3-030-53552-0_1
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DOI: https://doi.org/10.1007/978-3-030-53552-0_1
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