An Open Benchmark Dataset and Fusion Pipeline for Perception with Vehicle-to-Vehicle Communication

What is OPV2V?

 OPV2V is the first large-scale Open Dataset for Perception with V2V communication. By utilizing a cooperative driving co-simulation framework named OpenCDA and CARLA simulator, we collect divergent scenes with various numbers of connected vehicles to cover challenging driving situations like severe occlusions.

Key statistics:

  • aggregated sensor data  from multi-connected automated vehicles
  • 73 scenes, 6 road types, 9 cities
  • 12K frames of LiDAR point clouds and RGB camera images, 230K annotated 3D bounding box
  • comprehensive benchmark with 4 LiDAR detectors and 4 different fusion strategies (16 models in total)

Diverse Scenes

Suburb Midblock

Urban T-intersection

Urban Curvy Road

Freeway Entrance Ramp

Urban 4-way Intersection

Rural Curvy Road

Sensor Suites

  • Lidar: 120 m detection range, 130,0000 points per second, 26.8◦ vertical
  • 4x Camera: 110 ◦ FOV,  800×600 resolution
  • GNSS: 0.2m error

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