High quality data for adverse driving conditions

The CADC dataset aims to promote research to improve self-driving in adverse weather conditions. This is the first public dataset to focus on real world driving data in snowy weather conditions.

It features:

• 56,000 camera images
• 7,000 LiDAR sweeps
• 75 scenes of 50-100 frames each
• 10 annotation classes
• Full sensor suite: 1 LiDAR, 8 Cameras, Post-processed GPS/IMU
• Adverse weather driving conditions, including snow

Instances Per Label

Data Collection

Complex Driving Scenarios in Adverse Conditions

For this dataset, routes were chosen with various levels of traffic, a variety of vehicles and always with snowfall.

Sequences were selected from data collected within the Region of Waterloo, Canada.

Vehicle, Sensor and Camera Details

We collected data using the Autonomoose, a Lincoln MKZ Hybrid mounted with a full suite of LiDAR, inertial and vision sensors.

Please refer to the figure below for the sensor configuration of the Autonomoose.

Wide Angle Cameras

• 10 Hz capture frequency
• 1/1.8¡± CMOS sensor of 1280x1024 resolution
• Images are stored as PNG

LiDAR

• 10 Hz capture frequency
• 32 channels
• 200m range
• 360¡ã horizontal FOV; 40¡ã vertical FOV (-25¡ã to +15¡ã)

Post-processed GPS and IMU