English

Canadian Adverse Driving Conditions Dataset

Computer Vision and Pattern Recognition 2021-04-16 v3

Abstract

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 vehicle dataset that focuses on adverse driving conditions specifically. It contains 7,000 frames collected through a variety of winter weather conditions of annotated data from 8 cameras (Ximea MQ013CG-E2), Lidar (VLP-32C) and a GNSS+INS system (Novatel OEM638). 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.

Keywords

Cite

@article{arxiv.2001.10117,
  title  = {Canadian Adverse Driving Conditions Dataset},
  author = {Matthew Pitropov and Danson Garcia and Jason Rebello and Michael Smart and Carlos Wang and Krzysztof Czarnecki and Steven Waslander},
  journal= {arXiv preprint arXiv:2001.10117},
  year   = {2021}
}
R2 v1 2026-06-23T13:22:25.993Z