FFRENETIX Motion Planner & Multi-agent Scenario Handler
Welcome to the TUM FRENETIX Motion Planner. Here you find the modules, the code and the information to run our high performance motion planning algorithm for autonomous driving tasks.
📖 Overview Modules
This repository includes a Frenet trajectory planning algorithm and a Multi-agent Simulation Framework in the [CommonRoad](https://commonroad.in.tum.de/) scenario format.
The trajectories are generated according to the sampling-based approach in [1-5] including two different implementations.
The Repo provides a python-based and a C++-accelerated Motion Planner [Frenetix](https://github.com/TUM-AVS/Frenetix/) implementation.
The multi-agent simulation can be used to integrate and test different planning algorithms. FRENETIX is an modular and adaptive motion planning environment that allows researchers to add and exchange the following modules:
Detailed documentation of the functionality behind the single modules can be found below.
1. [General Motion Planning Algorithm](README.md)
2. [Frenetix C++ Trajectory Handler](https://github.com/TUM-AVS/Frenetix)
3. [Commonroad Scenario Handler](cr_scenario_handler/README.md)
4. [Module M2: Behavior Planner](behavior_planner/README.md)
5. [Module M3: Occlusion-aware Module](https://github.com/TUM-AVS/Frenetix-Occlusion)
6. [Module M4: Trajectory Prediction: Wale-Net](https://github.com/TUMFTM/Wale-Net)
7. [Module M5: Risk-Assessment](https://github.com/TUMFTM/EthicalTrajectoryPlanning)
8. [Module M6: Reinforcement Learning Module Extension](https://github.com/TUM-AVS/Frenetix-RL)
🔧 Requirements & Pre-installation Steps
### Requirements
The software is developed and tested on recent versions of Linux. We strongly recommend to use [Ubuntu 22.04](https://ubuntu.com/download/desktop) or higher.
For the python installation, we suggest the usage of Virtual Environment with Python 3.11, Python 3.10 or Python 3.9
For the development IDE we suggest [PyCharm](http://www.jetbrains.com/pycharm/)
### Pre-installation Steps
1. Make sure that the following **dependencies** are installed on your system for the C++ implementation:
* [Eigen3](https://eigen.tuxfamily.org/dox/)
* On Ubuntu: `sudo apt-get install libeigen3-dev`
* [Boost](https://www.boost.org/)
* On Ubuntu: `sudo apt-get install libboost-all-dev`
* [OpenMP](https://www.openmp.org/)
* On Ubuntu: `sudo apt-get install libomp-dev`
* [python3.11-full](https://packages.ubuntu.com/jammy/python3.11-full)
* On Ubuntu: `sudo apt-get install python3.11-full` and `sudo apt-get install python3.11-dev`
2. **Clone** this repository & create a new virtual environment `python3.11 -m venv venv`
3. **Install** the package:
* Source & Install the package via pip: `source venv/bin/activate` & `pip install .` or `poetry install`
* [Frenetix](https://pypi.org/project/frenetix/) should be installed automatically. If not please write [rainer.trauth@tum.de](mailto:rainer.trauth@tum.de).
4. **Optional**: Download additional Scenarios [here](https://gitlab.lrz.de/tum-cps/commonroad-scenarios.git)
🚀🚀🚀 Frenetix-Motion-Planner Step-by-Step Manual
1. Do the **Requirements & Pre-installation Steps**
2. **Change** Configurations in _configurations/_ if needed.
3. **Change** Settings in **main.py** if needed. Note that not all configuration combinations may work. The following options are available:
1. **use_cpp**: If _True_: The C++ Frenet Implementations will be used.
2. Set the scenario name you want to use.
4. **Run** the planner with `python3 main.py`
5. **Logs** and **Plots** can be found in _/logs/ 🚗🛣️🚙 Multi-agent Simulation Framework
#### Run Multi-agent Simulation
1. Do the **Requirements & Pre-installation Steps**
2. **Change** Configurations in _configurations/_ if needed. \
By **default**, a multi-agent simulation is started with **all agents**. \
The multi-agent simulation settings can be adjusted in _configurations/simulation/simulation_.
3. **Change** Settings in **main_multiagent.py** if needed
1. Set the scenario name you want to use.
3. **evaluation_pipeline**: If _True_: Start an evaluation pipeline with all scenarios
4. **Run** the simulation with `python3 main_multiagent.py`
5. **Logs** and **Plots** can be found in _/logs/ 🚸 Occlusion-aware Module
Also checkout the external Occlusion-aware Module [here](https://github.com/TUM-AVS/Frenetix-Occlusion).