OpenCDA v0.1.1 Release
Check https://opencda-documentation.readthedocs.io/en/latest/md_files/release_history.html to see more visulizations.
v0.1.1
Cooperative Perception
OpenCDA now supports data dumping simultaneously for multiple CAVs to develop V2V perception
algorithms offline. The dumped data includes:
- LiDAR data
- RGB camera (4 for each CAV)
- GPS/IMU
- Velocity and future planned trajectory of the CAV
- Surrounding vehicles' bounding box position, velocity
Run the following script to collect cooperative data:
python opencda.py -t cooperception_datadump_town06_carla -v 0.9.12(or 0.9.11)
Besides the above dumped data, users can also generate the future trajectory for each
vehicle for trajectory prediction purpose. Run python root_of_opencda/scripts/generate_prediction_yaml.py
to generate the prediction offline.
This new functionality has been proved helpful. The newest paper OPV2V: An Open Benchmark Dataset and Fusion Pipeline for Perception with Vehicle-to-Vehicle Communication has utilized this new feature to collect cooperative data. Check https://mobility-lab.seas.ucla.edu/opv2v/ for more information.
CARLA 0.9.12 Support
OpenCDA now supports both CARLA 0.9.12 and 0.9.11. Users needs to set CARLA_VERSION variable before
installing OpenCDA. When users run opencda.py, -v argument is required to classify the CARLA version for
OpenCDA to select the correct API.
Weather Parameters
To help estimate the influence of weather on cooperative driving automation, users now can
define weather setting in the yaml file to control sunlight, fog, rain, wetness and other conditions.
Bug Fixes
Some minor bugs in the planning module are fixed.