Abstract
This chapter aims to explore methods and procedures for route planning in urban air space for Advanced Air Mobility (AAM) operations using a 3D GIS environment. Route planning for urban air space through data analytics is produced to support planners in decision-making by visualizing the key influential factors in a 3D urban environment. Having defined two use cases for the City of Atlanta, different data types are needed to account for those factors and are introduced and tested. The use case for the Atlanta Aerotropolis has represented the need to plan a short-distance inner-city AAM network to serve as a public transportation network. In contrast, the other use case is a remote terminal shuttle service for the Atlanta airport. Recommendations on validating and optimizing the AAM networks are made at the end of this chapter.
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Wang, X., Yang, P.PJ., Balchanos, M., Mavris, D. (2023). Urban Airspace Route Planning for Advanced Air Mobility Operations. In: Goodspeed, R., Sengupta, R., Kyttä, M., Pettit, C. (eds) Intelligence for Future Cities. CUPUM 2023. The Urban Book Series. Springer, Cham. https://doi.org/10.1007/978-3-031-31746-0_11
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