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https://github.com/tudo-aqua/stars-auna-experiments

This repository analyzes driving data recorded with model race cars in a platooning scenario using the STARS framework.
https://github.com/tudo-aqua/stars-auna-experiments

auna autonomous-robots autonomous-vehicles classification formal-verification platooning stars

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This repository analyzes driving data recorded with model race cars in a platooning scenario using the STARS framework.

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README 

        
# STARS experiments based on data from model race cars



This repository analyzes driving data recorded using the [STARS

framework](https://github.com/tudo-aqua/stars). The data was recorded using the [AuNa](https://github.com/HarunTeper/AuNa)

Repository.



## Running the Analysis



This project is a Gradle project with a shipped gradle wrapper. To execute the analysis simply execute:



- Linux/Mac: `./gradlew run`

- Windows: `./gradlew.bat run`



## Analysis Results



After the analysis is finished you can find the results in the `analysis-result-logs` sub-folder which will be

created during the analysis.



For each execution of the analysis pipeline a sub-folder with the start date and time ist created. In it, each metric

of the analysis has its own sub-folder. The analysis separates the results of each metric into different categories

with different detail levels.

- `*-severe.txt` lists all failed metric results

- `*-warning.txt` lists all warnings that occurred during analysis

- `*-info.txt` contains the summarized result of the metric

- `*-fine.txt` contains a more detailed result of the metric

- `*-finer.txt` contains all possible results of the metric

- `*-finest.txt` contains all possible results of the metric including meta information



## Meta data information



The scenario data has the following properties:

- `robot width`: 0.2m

- `robot length`: 0.4m

- `track width`: 1.4m (each 0.7m orthogonal from the center)

- `velocity goal`: Depends on the data set, is either 3m/s or 0.8 m/s

- `standstill distance`: 1.25m

- `time distance`: 0.25s

- `target distance at any time`: `standstill distance` + `time distance` * `speed`



## Track overview (Line)

![flw_track_waypoints_line.png](images%2Fflw_track_waypoints_line.png)



## Track overview (Scatter)

![flw_track_waypoints_scatter.png](images%2Fflw_track_waypoints_scatter.png)



## Track segmentation

As it is visible in the scatter plot above, the straight parts of the track are only mapped by two points.

Therefore, we extracted these 4 coordinates for the two straights. We identified the following points:

- (x=-7.09735979561802,y=-1.89133616892839) (lower left corner)

- (x=2.93225065116357, y=-3.27073098672295) (lower right corner)

- (x=-6.09016702472381,y=3.17436982808834) (upper left corner)

- (x=2.7643231790252, y=4.33303506387608) (upper right corner)



## Domain Model

Here you can find the domain model that is used for this experiments.

All interfaces marked in green come from the [STARS

framework](https://github.com/tudo-aqua/stars) and are implemented with concrete classes in this repository.

The left-hand part of the diagram displays the structure of the messages

that are sent by the platooning vehicles. The right-hand part of the diagram

shows all classes that are necessary for our analysis.



![Platooning Data Model.svg](astah/Platooning_Data_Model.svg)



#### (Optional) Git Hooks

If you want to use our proposed Git Hooks you can execute the following command:

```shell

git config --local core.hooksPath .githooks

```