GRAIC Beta Release v0.2.1

Release v0.2.1 includes:

• Add rostopics that publish road lane boundary information in left_lane_markers and right_lane_markers

This release also includes the following features:

• Integration with CARLA scenario runner
• ScenarioNode: generates scenarios(traffic situations involving other vehicles and pedestrians) on the track
• One new track: track5; we now have 3 tracks. Each track has a different race configuration
• New scoring function: summation of time passing each waypoint and a penalty for out of bounds and collisions. Lower scores are better
• Config for user code to know the vehicle type id (baseline.py and starter.py will automatically load the configurations)
• Link to GRAIC Docker v0.2.0: https://hub.docker.com/r/pricejiang/graic

GRAIC Beta Release v0.2.0

This release includes the following features:

• Integration with CARLA scenario runner
• ScenarioNode: generates scenarios(traffic situations involving other vehicles and pedestrians) on the track
• One new track: track5; we now have 3 tracks. Each track has a different race configuration
• New scoring function: summation of time passing each waypoint and a penalty for out of bounds and collisions. Lower scores are better
• Config for user code to know the vehicle type id (baseline.py and starter.py will automatically load the configurations)
• Link to GRAIC Docker v0.2.0: https://hub.docker.com/r/pricejiang/graic

GRAIC Beta Release v0.1.2

Since CARLA has officially updated carla-ros-bridge to support CARLA 0.9.11, we have updated our Docker image and made small modifications

• Link to GRAIC Docker v0.1.2: https://hub.docker.com/r/pricejiang/graic

GRAIC Beta Release v0.1.1

This release includes a patch in the perception module:

• Modified LaneInfo message type to include more information about left and right lanes
• Fixed disjoint lane markers at junctions of road segments

GRAIC Beta Release v0.1.0

This is the beta release of the GRAIC: A competition for intelligent racing
Features

• Created a basic structure of the competition framework
• Imlemented perception_module:
  • graic_raceinfo_publisher provides perfect obstacle information around the ego-vehicle perfect and lane markers that are within a certain distance in front of the ego-vehicle
  • loaction_publisher provides perfect location information of the ego-vehicle
• Created graic_msgs for the convenience of delivering perception results
• Implemented race_util_module
  • waypoint_node will provide milestones that vehicles must reach to score in the race
  • model-based-node provides a known dynamic model for vehicles
• Baseline controller provided in baseline.py
• Controller template provided in starter.py