Canadian Adverse Driving Conditions dataset

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...

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Bibliographic Details
Published in:The International journal of robotics research 2021-04, Vol.40 (4-5), p.681-690
Main Authors: Pitropov, Matthew, Garcia, Danson Evan, Rebello, Jason, Smart, Michael, Wang, Carlos, Czarnecki, Krzysztof, Waslander, Steven
Format: Article
Language:English
Subjects:
Annotations
Datasets
Driving conditions
Lidar
Object recognition
Time synchronization
Weather
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Summary: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.
ISSN:0278-3649
1741-3176
DOI:10.1177/0278364920979368