V2V4Real: A Real-World Large-Scale Dataset for Vehicle-to-Vehicle Cooperative Perception
University of California, Los Angeles · Cleveland State University · +3 more institutions
Abstract
Modern perception systems of autonomous vehicles are known to be sensitive to occlusions and lack the capability of long perceiving range. It has been one of the key bottlenecks that prevents Level 5 autonomy. Recent research has demonstrated that the Vehicle-to-Vehicle (V2V) cooperative perception system has great potential to revolutionize the autonomous driving industry. However, the lack of a real-world dataset hinders the progress of this field. To facilitate the development of cooperative perception, we present V2V4Real, the first large-scale real-world multi-modal dataset for V2V perception. The data is collected by two vehicles equipped with multi-modal sensors driving together through diverse…
Citation impact
- FWCI
- 22.63
- Percentile
- 100%
- References
- 73
Authors
13Topics & keywords
- Computer science
- Perception
- Minimum bounding box
- Scale (ratio)
- Artificial intelligence
- Bounding overwatch
- Haptic perception
- Modal