daweidavidwang / CommonRoad_tutorial

Install Common-Road

create a clean conda environment (python==3.7)

pip install commonroad-all

git clone https://gitlab.lrz.de/tum-cps/commonroad-scenario-designer.git

cd commonroad-scenario-designer

conda install -c conda-forge cartopy

pip install -r requirements.txt && python setup.py install

Run example

Map Convert From OpenDRIVE format

1. run python file "opendrive_converter.py"

Opendrive_converter.py is used to convert OpenDRIVE map to CommonRoad scenario XML file

modify the first two line in Opendrive_converter.py to try with your OpenDRIVE file

2. run python file opendrive_demo.py

opendrive_demo.py parses the XML scenario file and renders it with Matplotlib.

modify the second line in opendrive_demo.py to run other scenario

Planning example

install commonroad planning pack first

1. git clone https://gitlab.lrz.de/tum-cps/commonroad-search.git

2. cd commonroad-search && pip install -r requirements.txt

3. run python file planning_example.py

The black point denotes the vehicle's position.

Dynamic obstacle example

install requirement

1. pip install lxml

examine the static scenario

2. run dynamic_demo.py

add dynamic obstacle to ZAM_Tutorial-1_1_no_obs.xml

3. run dynamic_obstable_example,py

There will be a new generated file named "output.xml"

4. modify the first line of dynamic_demo.py to "output.xml"

run demo again, you will see a moving vehicle in this scenario

5. run dynamic_demo.py

IV challenge tutorial

install requirements

1. pip install cvxpy

run IV_challenge.py

2. python IV_challenge.py

This solution is submitted to: https://commonroad.in.tum.de/solutions/ranking/PM3:WX1:ZAM_Tutorial-1_1_T-1:2020a

planning example with route planner

install requirements

1. pip install commonroad-route-planner

RL example

install requirements

1. sudo apt-get install libeigen3-dev libboost-all-dev libomp-dev
2. ./install_commonroad_rl.sh

generate data for RL training

1. python -m commonroad_rl.tools.pickle_scenario.xml_to_pickle -i scenario/inceptio_highway -o scenario/pickle/

train your RL model

1. python RL_example.py

test and plot result

1. python -m commonroad_rl.evaluate_model
   --algo ppo2
   --model_path logs
   --test_path scenario/pickle/
   --viz_path imgs