Canadian Adverse Driving Conditions dataset. (April 2021)

• Record Type: Journal Article
• Authors: Pitropov, Matthew; Garcia, Danson Evan; Rebello, Jason; Smart, Michael; Wang, Carlos; Czarnecki, Krzysztof; Waslander, Steven
• Is Part Of: International journal of robotics research. Volume 40:Number 4/5(2021)
• Page Start: 681
• Page End: 690
• Publication Date: 2021-04
• Subjects: Autonomous vehicle -- camera -- dataset -- GPS -- IMU -- lidar -- winter weather; Robots -- Periodicals; Robots, Industrial -- Periodicals; 629.89205
• DOI: 10.1177/0278364920979368
• Languages: English
• ISSNs: 0278-3649

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 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.