CARLA AD Challenge track4 sample

Clone the repository:

git clone https://github.com/felipecode/track4sample.git 
cd coiltraine

You need pygame:

pip install pygame

The checkpoints should now be allocated already on the proper folders.

Download the latest CARLA 0.9.x version. Then, after unpacking it, define where the root folder was placed:

export CARLA_ROOT=<path_to_carla_root>

Install the latest CARLA API:

easy_install ${CARLA_ROOT}/PythonAPI/*-py3.5-linux-x86_64.egg

Make sure you set the PYTHONPATH PythonAPI path:

 export PYTHONPATH=${CARLA_ROOT}/PythonAPI:$PYTHONPATH

Get the agent performance on the CARLA Challenge

Clone the scenario runner repository:

cd
git clone https://github.com/carla-simulator/scenario_runner.git

Setup the scenario runner challenge repository by setting the path to your CARLA root folder.

cd scenario_runner
bash setup_environment --carla-root <path_to_carla_root_folder>

Export the track4sample path to the PYTHONPATH:

cd ~/track4sample
export PYTHONPATH=`pwd`:$PYTHONPATH

Going back to the scenario runner folder, execute the challenge with the conditional imitation learning baseline

python3  srunner/challenge/challenge_evaluator.py --file --scenario=group:ChallengeBasic --agent=../track4sample/Track4SampleAgent.py