OpenCDA v0.1.2 Release

Map manager

OpenCDA now adds a new component map_manager for each cav. It will dynamically load road topology, traffic light information, and dynamic
objects information around the ego vehicle and save them into rasterized map, which can be useful for RL planning, HDMap learning, scene understanding, etc.
Key elements in the rasterization map:

• Drivable space colored by black
• Lanes
  • Red lane: the lanes that are controlled by red traffic lights
  • Green lane: the lanes that are controlled by green traffic lights
  • Yellow lane: the lanes that are not effected by any traffic light
• Objects are colored by white and represented as rectangles

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.

OpenCDA v0.1.0

The initial release of OpenCDA

• Integrated with CARLA and Sumo. Supports CARLA only mode and Co-Simulation mode.
• Provides a full-stack automated driving and cooperative driving software system. that contains perception, localization, planning, control, and V2X communication modules.
• Default perception, localization, planning, and control algorithms installed
• Default platooning and cooperative merge algorithms and protocols installed
• V2X feature supported, allowing simulating communication lagging and noise
• 10+ testing scenarios were provided.
• Customized maps were provided for highway testing.
• Benchmark evaluation measurements provided