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https://github.com/commonroad/commonroad-crime

🚧 🚔 ⚠ Toolbox to compute Criticality Measures for Automated Vehicles
https://github.com/commonroad/commonroad-crime

autonomous-driving criticality safety-critical safety-critical-systems safety-monitoring scenario-analysis time-to-collision time-to-react

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🚧 🚔 ⚠ Toolbox to compute Criticality Measures for Automated Vehicles

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README

        

# CommonRoad-CriMe
![image info](https://raw.githubusercontent.com/CommonRoad/commonroad-crime/develop/docs/figures/CriMe-banner.png)
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Toolbox to compute **Cri**ticality **Me**asures
(e.g. time-to-collision, time-to-react,...). Such measures
can be used to trigger warnings and emergency maneuvers
in driver assistance systems or repair an infeasible
trajectory. If you have questions or want to report problems or suggestions, please start a [Github discussion](https://github.com/orgs/CommonRoad/discussions) /
[Github issue](https://github.com/CommonRoad/commonroad-crime/issues/).


Live Demo

## 🚀 Installation Guide

`commonroad-crime` can be installed with:

``` bash
$ pip install commonroad-crime
```

Develop CriMe locally

For adding new measures, we recommend using [Anaconda](https://www.anaconda.com/) to manage your environment so that even if you mess something up, you can always have a safe and clean restart. A guide for managing python environments with Anaconda can be found [here](https://conda.io/projects/conda/en/latest/user-guide/tasks/manage-environments.html).

After installing Anaconda, create a new environment with:
``` bash
$ conda create -n commonroad-py38 python=3.8 -y
```

Here the name of the environment is called **commonroad-py38**. You may also change this name as you wish. In such case, don't forget to change it in the following commands as well. **Always activate** this environment before you do anything related:

```sh
$ conda activate commonroad-py38
or
$ source activate commonroad-py38
```
Then, install the dependencies with:

```sh
$ cd
$ pip install -e .
$ conda develop .
```

To test the installition, run unittest:
```bash
$ cd tests
$ python -m unittest -v
```

To get started your journey with our criticality measures, check the `tutorials` and the following tips.

Add new criticality measure

1. create a new branch with `feature-` and checkout the branch
2. navigate to `commonroad_crime/data_structure/type.py` to find the correct category of the measure and add an
enumeration entry `: `
3. navigate to `commonroad_crime/measure` to find the above-mentioned category and create a python file named
`.py`. Then create a class inheriting the `CriMeBase` under `commonroad_crime/data_structure/base.py`
4. similar to other measures, you need to implement the `compute()` and `visualize()` functions

Define configuration parameters of the measure

1. navigate to `commonroad_crime/data_structure/configuation.py` to find the above-mentioned category and add a new
instance to the class as `self. = config_relevant.`
2. you can then directly call the values using `self.configuration..` in your measure class
3. to override the default parameter values, create a `yaml` file (name it the same as the scenario) in `./config_files` and modify the values there

## 🚧 Documentation

The documentation of our toolbox is available on our website: https://cps.pages.gitlab.lrz.de/commonroad/commonroad-criticality-measures/.

Build documentation locally
In order to generate the documentation via Sphinx locally, run the following commands in the root directory:

```bash
$ pip install -r ./docs/requirements_doc.txt
$ cd docs/sphinx
$ make html
```

The documentation can then be launched by browsing ``./docs/sphinx/build/html/index.html/``.

## 🌟 Contributors (in alphabetical order by last name)

- Liguo Chen
- Marius Erath
- Yuanfei Lin
- Sebastian Maierhofer
- Ivana Peneva
- Kun Qian
- Oliver Specht
- Sicheng Wang
- Youran Wang
- Zekun Xing
- Ziqian Xu

## 🔖 Citation
If you use `commonroad-crime` for academic work, we highly encourage you to cite our paper:
```text
@InProceedings{lin2023crime,
title = {{CommonRoad-CriMe}: {A} Toolbox for Criticality Measures of Autonomous Vehicles},
author = {Yuanfei Lin and Matthias Althoff},
booktitle = {Proc. of the IEEE Intell. Veh. Symp.},
pages = {1-8},
year = {2023},
}
```
If you use this project's code in industry, we'd love to hear from you as well;
feel free to reach out to [Yuanfei Lin](mailto:[email protected]) directly.