Proof of Concept demonstrating modelling of UAS ground risk from open source data sources. This constructs a spatiotemporal population density map and evaluates the risk posed by a parameterised UAS. This risk map can then be used by pathfinding algorithms to determine routes that have a fixed risk threshold or minimize flight risk completely.
All data processing is performed locally, so performance depends on your machine spec. At least 8GiB of RAM is essential however.
Funded by the Engineering and Physical Sciences Research Council on the E-Drone project (EP/V002619/1).
This is intended to provide guidance on overflight risks in terms of risk-to-life (RtL) and is by no means an extensive or complete picture of the ground risks. While the software is intended to promote safe drone flight, use of this software does not in itself guarantee safe or legal drone operation. For the UK, the CAA provides further information
A Windows 64-bit installer is provided with each release. This is the easiest option for just using the tool. This works on its own, however is not able to take advantage of the GPU, causing rather slow risk map generation. For this reason it is highly recommended to install the Nvidia CUDA Toolkit.
A CLI is provided to allow for automation. Currently this requires building your own wheels as local wheel dependencies cannot be packaged and distributed. The included data files also take the package above the PyPI limit.
See BUILD.md for further instructions.
MIT License
Copyright (c) 2022 Aliaksei Pilko
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