MATLAB code to generate representative UAS trajectories based on open source geospatial features, such as those provided by OpenStreetMap.
Development is ongoing and future updates to this software are expected. This software is in the open beta / preview stage. Documentation will be improved in future updates.
- Uncorrelated Geospatial Model
| Acronym | Phrase |
|---|---|
| AGL | above ground level |
| BVLOS | beyond visual line of sight |
| CFIT | controlled flight into terrain |
| MSL | mean sea level |
| OSM | OpenStreetMap |
Our overall objective was the development of low altitude unmanned and manned aircraft encounter models to support DAA research. A public, easily accessible corpus of UAS trajectories, however, is not available since beyond visual line of sight (BVLOS) operations are not routine and there is a lack of reporting requirements. Therefore, we seek to generate representative BVLOS UAS trajectories without actual UAS flights as training data.
This section specifies the run order and requirements for the initial setup the repository. Other repositories in this organization are reliant upon this setup being completed.
Immediately after cloning this repository, create a persistent system environment variable titled AEM_DIR_GEOSPATIAL with a value of the full path to this repository root directory.
On unix there are many ways to do this, here is an example using /etc/profile.d. Create a new file aem-env.sh using sudo vi /etc/profile.d/aem-env.sh and add the command to set the variable:
export AEM_DIR_GEOSPATIAL=PATH TO DIRECTORYYou can confirm AEM_DIR_GEOSPATIAL was set in unix by inspecting the output of env.
This is a set of boilerplate scripts describing the normalized script pattern that GitHub uses in its projects. The GitHub Scripts To Rule Them All was used as a template. Refer to the script directory README for more details.
You will need to run these scripts in this order to download the open source geospatial data.
Complete the initial setup of the em-core repository.
Code developed in Windows for Matlab 2018a. The dev machine had a CPU of Intel Xeon Gold 6130 at 2.10GHz and 64 GB of RAM. The built-in Matlab function parfor is used routinely throughout the code. With a local parallel pool (parpool) of 12 nodes, Matlab can claim 42+ GB of RAM and 50% CPU. Majority of the computation intensive work is related to working with digital elevation models.
Run the MATLAB startup script, startup_geospatial.
First, run RUN_1_OSM which calls OSMParse to load and parse the Geofabrik OpenStreetMap extracts. This will create a set of MATLAB tables for each specified ISO-3166-2 administrative boundary corresponding to features for land use, points of interest, railway, transportation, waterways, and roadways. This step is only for the OpenStreetMap data, other data sources are directly loaded and parsed in Step 2 run script examples.
Specifically, OSMParse has the following input parameters:
| Variable | Description | Example |
|---|---|---|
| iso_3166_2 | Features to based trajectories off of | US-MA |
| isSave | If true, save to file | true |
| outName | Output filename | OSM_1_US-MA.mat |
| isComputeElv | If true, calculate elevation for each feature | false |
| dem | Digital elevation model name | globe |
- RUN in MATLAB, the
RUN_2-*scripts to generate trajectories for specific features of interest. Trajectories will be rejected if projected to CFIT.
| Script | Type | Generated Trajectories |
|---|---|---|
RUN_2_Landuse_POIS |
Pattern | Inspections of features of OSM points of interest polygons (e.g. golf course) or land use polygons (e.g. beach, cliff, farm, vineyard, etc.) |
RUN_2_DOF |
Point | Obstacle inspection |
RUN_2_WindTurbine |
Point | Wind turbine inspection |
RUN_2_ElectricTransmission |
Track | Electric power transmission line inspection |
RUN_2_GSHHG |
Track | Coastline and shoreline inspections |
RUN_2_Pipeline |
Track | Four types of pipeline inspection |
RUN_2_Railway |
Track | Railway inspection |
RUN_2_Road |
Track | Freeway and primary road inspection |
RUN_2_Waterway |
Track | Large river, stream, artificial waterway, and small drainage ditch inspection |
Specifically, GenerateTracks has the following input parameters:
| Variable | Description | Example |
|---|---|---|
| S | Features to based trajectories off of | |
| outDirBase | Name of parent output directory | [getenv('AEM_DIR_GEOSPATIAL') filesep 'output' filesep 'trajectories' filesep 'US-MA] |
| airspace | Output of RUN_Airspace_1.m from em-core |
[getenv('AEM_DIR_CORE') filesep 'output' filesep 'airspace.mat']; |
| alt_tol_ft | Altitude tolerance for terrain following | 25 |
| demDir | Directory containing DEM | [getenv('AEM_DIR_CORE') filesep 'data' filesep 'DEM-SRTM1'] |
| dem | Digital elevation model name | srtm1 |
| demDir | Directory containing backup DEM | [getenv('AEM_DIR_CORE') filesep 'data' filesep 'DEM-GLOBE'] |
| dem | Digital elevation model name of backup | globe |
| alt_ft_agl | Cruise altitude in feet AGL | 400 |
| airspeed_kt | Cruise airspeed in knots | 60 |
| climbRate_fps | Maximum climb rate | 16 |
| descendRate_fps | Maximum descent rate | -16 |
| maxSpacing_ft | Maximum allow able spacing between sequential waypoints | 2000 |
| trackMode | Trajectory behavior | holdalt |
| pointRadius_ft | Lateral distance away from point being inspected | 250 |
| pointHeight_ft | Maximum height when inspecting a point | 50 |
| pointPts | Number of points when inspecting a point | 100 |
| vertLef_ft | Vertical distance travel for each complete spiral leg | 25 |
| S_obstacle | Table of obstacles that can't be flown through (deprecated) | [] |
| isCheckObstacle | If true, remove trajectories that fly through any S_obstacle (deprecated) |
false |
| isRePathObstacle | If true, try to path plan around obstacles (deprecated) | false |
Refer to the em-pairing-geospatial or em-pairing-uncor-importancesampling repositories on how to pair the generated trajectories to create encounters.
Please use this DOI number reference when citing the software:
A. Weinert, M. Edwards, L. Alvarez, and S. Katz, “Representative Small UAS Trajectories for Encounter Modeling,” in AIAA Scitech 2020 Forum, 2020, pp. 1–10.
@inproceedings{weinertGeneratingRepresentativeSmall2018,
title = {Representative Small UAS Trajectories for Encounter Modeling},
url = {https://doi.org/10.2514/6.2020-0741},
doi = {10.2514/6.2020-0741},
booktitle = {AIAA Scitech 2020 Forum},
author = {Andrew J. Weinert and Matthew Edwards and Luis Alvarez and Sydney Michelle Katz},
month = jan,
year = {2020},
}A. Weinert and N. Underhill, “Generating Representative Small UAS Trajectories using Open Source Data,” in 2018 IEEE/AIAA 37th Digital Avionics Systems Conference (DASC), 2018, pp. 1–10.
@inproceedings{weinertGeneratingRepresentativeSmall2018,
title = {Generating {Representative} {Small} {UAS} {Trajectories} using {Open} {Source} {Data}},
url = {https://ieeexplore.ieee.org/document/8569745},
doi = {10.1109/DASC.2018.8569745},
booktitle = {2018 {IEEE}/{AIAA} 37th {Digital} {Avionics} {Systems} {Conference} ({DASC})},
author = {Weinert, Andrew and Underhill, Ngaire},
month = sep,
year = {2018},
keywords = {Aircraft, Atmospheric modeling, FAA, Monte Carlo methods, Standards, Surveillance, Trajectory},
pages = {1--10}
}This software uses data originally sourced from © OpenStreetMap contributors, which provides data under the Open Database License.
Geofabrik provides OpenStreetMap OSM extracts free of restrictive licensing terms.
DISTRIBUTION STATEMENT A. Approved for public release. Distribution is unlimited.
This material is based upon work supported by the Federal Aviation Administration under Air Force Contract No. FA8702-15-D-0001.
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