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Urban airspace availability assessment (below 1500 m)
Urban airspace availability assessment (below 1500 m)
Summary
Background
The airspace to be used by UAM aircraft is already occupied by various airspace constructs, such as arrival and departure procedures, special use airspace, and temporary flight restrictions. UAM operators should be aware of which airspace is accessible at each altitude, in order to derive safe and efficient route options.
Objective
This study aimed to assess airspace accessible by UAM aircraft in four ATC integration scenarios, each of which considers different sets of airspace constructs that UAM aircraft should not use.
Contribution
This study is one of the first researches to highlight not only the amount but also the shape of available airspace depends on the types of airspace constructs to be considered, the altitude to fly at, and the size of required separation.
Related publication
Vascik, P. D., Cho, J., Bulusu, V., & Polishchuk, V. (2019) A Geometric Approach Towards Airspace Assessment for Emerging Operations, ATM Seminar 2019. [pdf]
Vascik, P. D., Cho, J., Bulusu, V., & Polishchuk, V. (2020). Geometric Approach Towards Airspace Assessment for Emerging Operations. Journal of Air Transportation, 1-10. [pdf]
The 2D snapshops of available airspace in the four ATC integration scenario at different altitudes (MSL) (Colors are assigned to each of the constructs: controlled airspace in purple, airport procedures in blue for SFO and in green for OAK, minimum vectoring altitude in red, terrains and buildings in black, and UAS facility map in grey)
Method
Airspace constructs and airspace availability
Airspace constructs, such as airport procedures, are airspace volumes with specified properties defined to ensure the safety and efficiency of air traffic [1]. Each airspace construct may or may not allow UAM flight, and airspace outside airspace constructs is assumed to allow UAM aircraft to navigate. For details of data sources, please refer to [2].
ATC integration scenarios
Airspace availability was evaluated for four scenarios, as defined in Figure 2 [2]. In each scenario, UAM aircraft are restricted from flying through different sets of airspace constructs.
Figure 1. Case study airspace in San Francisco Bay area, displayed with airspace constructs (For details of data sources, please refer to [2])
Figure 2. Four ATC integration scenarios with different combinations of airspace constructs (extracted from [2])
Geometric data processing
Each three-dimensional (3-D) airspace construct is represented as a polygon mesh. To obtain a two-dimensional (2-D) boundary of available airspace at a given altitude h, the construct is sliced with a horizontal plane at h.
The key step in processing a geometrically complex construct data is to sample boundary points of the unstructured polygon mesh. To slice the unstructured mesh model, we sampled an ordered set of boundary points of each 3-D construct at desired altitudes h, as illustrated in Figure 3.
The slicing algorithm adopted in this study has two main steps – plane-triangle intersection and contour construction [3,4].
Figure 3. Geometric processing steps to extract contours of available airspace at h (extracted from doctoral dissertation)
Figure 4. Illustration of slicing an unstructured 3D mesh
Results
Fig. 4 shows changes in the available airspace in each scenario with respect to altitude. The snapshots of airspace availability at six altitudes are presented in Fig. 5.
Key findings
The airspace reserved for arrival and departure procedures (blue and green) in scenarios 3 and 4 is nearly negligible at 30 m
% of available airspace is at its peak in the San Francisco Bay area between 600 ft and 1000 ft in scenarios 2, 3, and 4, as displayed in Fig. 4
The altitudes between 600 ft and 1000 ft have the highest availability, because the influence of low-altitude airspace constructs (terrain, surface obstacles, and Part 107 airspace) reduces, while the influence of higher-altitude constructs (minimum vectoring altitudes and airport procedures) are not yet introduced.
Figure 5. % of available airspace in each scenario with respect to altitude from 0 to 5000 ft (MSL) (extracted from [2])
Figure 6. The 2D snapshops of available airspace in each scenario at different altitudes (MSL) (Colors are assigned to each of the constructs: controlled airspace in purple, airport procedures in blue for SFO and in green for OAK, minimum vectoring altitude in red, terrains and buildings in black, and UAS facility map in grey) (extracted from [2])
Future directions
There needs a special approach to model the highly obstructed and dynamically changing nature of UAM airspace, in order to generate route options and manage high-density air traffic in such an environment.
I am planning to apply the methodology introduced in "Fast and robust path enumeration in 3D" (Click for more details) to generate route options for UAM aircraft within a few miliseconds in dynamically changing environment.
References
[1] Mueller, E. R., Kopardekar, P. H., & Goodrich, K. H. (2017). Enabling airspace integration for high-density on-demand mobility operations. In 17th AIAA Aviation Technology, Integration, and Operations Conference (p. 3086).
[2] Vascik, P. D., Cho, J., Bulusu, V., & Polishchuk, V. (2020). Geometric Approach Towards Airspace Assessment for Emerging Operations. Journal of Air Transportation, 1-10. [pdf]
[3] McMains, S., & Séquin, C. (1999, June). A coherent sweep plane slicer for layered manufacturing. In ACM Symposium on Solid and Physical Modeling: Proceedings of the fifth ACM symposium on Solid modeling and applications (Vol. 8, No. 11, pp. 285-295).
[4] Minetto, R., Volpato, N., Stolfi, J., Gregori, R. M. M. H., & da Silva, M. V. G. (2017). An optimal algorithm for 3D triangle mesh slicing. CAD Computer Aided Design, 92, 1–10. https://doi.org/10.1016/j.cad.2017.07.001
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