See https://flow-project.github.io/ for Detail information of this framework
- Install prequisites:
sudo apt-get install libgl1-mesa-glx libegl1-mesa libxrandr2 libxss1 libxcursor1 libxcomposite1 libasound2 libxi6 libxtst6 - Download the Anaconda installation file for Linux in Anaconda, and unzip the file
- Install Anaconda
bash ~/Downloads/Anaconda3-2023.03-1-Linux-x86_64.sh
NOTE: we recommend you to running conda init 'yes'.
Following the below scripts in your terminal.
# Download FLOW github repo'.
git clone https://github.com/flow-project/flow.git
cd flow
# Create a conda env and install the FLOW
conda env create -f environment.yml
conda activate flow
python setup.py develop
# install flow on previoulsy created environment
pip install -e .
Install driving simulator (SUMO)
bash scripts/setup_sumo_ubuntu1804.sh
which sumo
sumo --version
sumo-gui
Testing the connection between FLOW and SUMO
conda activate flow
python examples/simulate.py ring
Install torch: conda install pytorch torchvision cudatoolkit=10.2 -c pytorch
NOTE: Should install at least 1.6.0 version of pytorch (Recommend torch = 1.11.0 & cudatoolkit=10.2).
Check the Pytorch Documents.
Install Ray: pip install -U ray==0.8.7
NOTE: Should install at least 0.8.6 version of Ray. (Recommend 0.8.7).
Clone this library: git clone (Will be updated)
sh ./requirements/env_requirements.sh
We provide the three driving scenarios as following table.
- Click Driving Scenario, You can check the illustrative image about driving scenario
- Click exp_config, You can check the code about driving scenario
| Driving Scenario | exp_config |
|---|---|
| Cut-in | UnifiedRing |
| Lane Reduction | MA_4BL |
| Highway | MA_5LC |
You can access the AD4RL googledrive by clicking the title name of driving scenario.
| Cut-in | Lane Reduction | Highway |
|---|---|---|
| cutin-expert | lanereduction-expert | highway-expert |
| cutin-medium | lanereduction-medium | highway-medium |
| cutin-random | lanereduction-random | highway-random |
| cutin-expert-medium | lanereduction-expert-medium | highway-expert-meidum |
| cutin-expert-random | lanereduction-expert-random | highway-expert-random |
| cutin-humanlike | lanereduction-humanlike | highway-humanlike |
python [algorithm] [exp_config] --dataset [dataset]
- [algorithm]: main_BC.py, main_BCQ.py, main_DDPGBC.py, main_EDAC.py, main_PLAS.py
- [exp_config]: UnifiedRing, MA_4BL, MA_5LC
- [dataset]: See the above table (e.g., cutin-expert, highway-NGSIM)