Commit da3947cb authored by Duncan Deveaux's avatar Duncan Deveaux
Browse files

Updated readme

parent 8ed85865
......@@ -20,14 +20,18 @@ In order to add new locations to the study, the following process should be foll
1. A Topology description has to be generated for the wanted location ID. The Topology description is a simple class instance which indicates the center point of the roundabout. It also provides a list of circular lanes that the roundabout contains.
1. In order to define the Topology object, please refer to the comments and tools in the [visualization.py](visualization.py) file.
* Replace the `input_file`, `input_meta_file` and `input_recordingMeta_file` with a tracks file of the wanted location ID.
* A plot of all tracks of the file will appear. Use it to choose the center point of the roundabout and the distance of lanes to the center of the roundabouts.
* Each lane should be 2.25meters long, see [topology.py](topology.py) for a simple example of a topology for Location 0.
* Play with the `topology` object in line 85 of [visualization.py](visualization.py) until the generated blue lanes accurately wrap the tracks.
* Replace the `input_file`, `input_meta_file` and `input_recordingMeta_file` with a tracks file of the wanted location ID.
* A plot of all tracks of the file will appear. Use it to choose the center point of the roundabout and the distance of lanes to the center of the roundabouts.
* Each lane should be 2.25meters long, see [topology.py](topology.py) for a simple example of a topology for Location 0.
* Play with the `topology` object in line 85 of [visualization.py](visualization.py) until the generated blue lanes accurately wrap the tracks.
2. Use the [parse.py](parse.py) file to generate TTC-augmented data for the wanted location.
1. Replace the `input_ids` variable with a list of all tracks id of the wanted location.
2. **Do replace the `topology` object on line 73 with the new topology you generated in the first step.**
3. Upon running the updated script, TTC-augmented data will be generated in a newly created ttc_parse/ directory.
3. Use the [analysis.py](analysis.py) file to generate the scatter plots and correlation analysis between the variation of TTC values and the amount of risk.
1. Replace the `input_ids` variable with the list of all tracks id of the wanted location.
2. Run the script to see the plotted results!
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