Frame (networking)

GNSS applications

Meteorology

Pedagogy

Adverse weather

Lidar

Physical geography

Variety (cybernetics)

Ground truth

Artificial intelligence

Psychology

Geography

Tracking (education)

Scale (ratio)

Computer science

Cartography

Global Positioning System

Georeference

Environmental science

Remote sensing

Telecommunications

The International Journal of Robotics Research

The Canadian Adverse Driving Conditions (CADC) dataset was collected with the Autonomoose autonomous vehicle platform, based on a modified Lincoln MKZ. The dataset, collected during winter within the Region of Waterloo, Canada, is the first autonomous driving dataset that focuses on adverse driving conditions specifically. It contains 7,000 frames of annotated data from 8 cameras (Ximea MQ013CG-E2), lidar (VLP-32C), and a GNSS+INS system (Novatel OEM638), collected through a variety of winter weather conditions. The sensors are time synchronized and calibrated with the intrinsic and extrinsic calibrations included in the dataset. Lidar frame annotations that represent ground truth for 3D object detection and tracking have been provided by Scale AI.

Canadian Adverse Driving Conditions dataset