Code and Data for "U-Space Utilisation of Airspace under Various Layer Function Assignments and Allocations"

doi: 10.4121/980484ec-5187-4f73-9e57-2e0dcd1330cc.v3
The doi above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
doi: 10.4121/980484ec-5187-4f73-9e57-2e0dcd1330cc
Datacite citation style:
Morfin Veytia, Andres (2023): Code and Data for "U-Space Utilisation of Airspace under Various Layer Function Assignments and Allocations". Version 3. 4TU.ResearchData. dataset. https://doi.org/10.4121/980484ec-5187-4f73-9e57-2e0dcd1330cc.v3
Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite
Dataset
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version 3 - 2023-07-05 (latest)
version 2 - 2023-06-09 version 1 - 2023-06-08
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This contains the code and output logs to run the BlueSky simulator for "U-Space Utilisation of Airspace under Various Layer Function Assignments and Allocations". The code provided here is a modified version of the main fork of BlueSky (https://github.com/TUDelft-CNS-ATM/bluesky).


The first step is to install the correct environment. Refer to `condaenv.txt` for the list of packages needed to run the simulator.


After setting up the environment, we then need to save all of the potential paths of drones in `bluesky/plugins/streets/path_plan_dills`. Note that this takes about 180GB of storage so make sure to have enough available. The paths can be downloaded from https://surfdrive.surf.nl/files/index.php/s/EcPGLvaBu7cZfTA. There are some example paths saved in this dataset but it will not be possible to run all of the experiment without downloading the paths.


The scenarios for sub-experiment 1 are saved in `bluesky/scenario/subexperiment1`.


The scenarios for sub-experiment 2 are saved in `bluesky/scenario/subexperiment2`.


To run the scenarios we first need to start a bluesky server by running the following code inside `bluesky`:


`python BlueSky.py --headless`


In another terminal we can start a bluesky client by running:


`python BlueSky.py --client`


In the bluesky console we can now run each batch scenario by typing and entering:


`batch batch_subexperiment_1.scn` or

`batch batch_subexperiment_2.scn`


The logs of the scenarios are saved in `bluesky/output`.


Without the paths, it will not possible to run the simulations. However, this code currently has some paths so that it is possible to run some example scenarios. The zeroth repetition for the low imposed traffic demand case can be run without all of the paths. For example, `bluesky/scenario/subexperiment1/Flight_intention_low_40_0_1to1.scn` and `bluesky/scenario/subexperiment2/Flight_intention_low_40_0_baseline.scn` can be run directly with this dataset.


First start bluesky by running:


`python BlueSky.py`


In the console, type.


`ic subexperiment2/Flight_intention_low_40_0_baseline.scn`


Please do not hesistate to contact me with any questions.


-Andres



history
  • 2023-06-08 first online
  • 2023-07-05 published, posted
publisher
4TU.ResearchData
format
.py, .log, .txt, .md
funding
  • Metropolis 2: A unified approach to airspace design and separation management for U-space (grant code 892928) [more info...] European Commission
organizations
TU Delft, Faculty of Aerospace Engineering, Department of Control & Operations

DATA

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