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Urban centers have begun encouraging novel aviation missions to transport goods and people for relatively short distances and at low altitudes over dense populations. These novel aviation missions, known collectively as Urban Air Mobility or UAM, require community consensus and potentially airspace rules in order to enable the scale of operations that are envisioned. Small piloted air vehicles that fly with a few passengers do operate in urban areas today, and these vehicles can be studied as an early proxy for this future UAM traffic. The goal of this project is to leverage clustering methods, combined with additional environmental and other metadata, to identify corridors already in daily operation and their properties to aid in safety guidelines and policy making for Urban Air Mobility.
Skills
LaTEX
Artificial Intelligence (AI)
Machine Learning (ML)
Git
Documentation / Technical Writing
R programming
Python
Jupyter notebooks
