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Canadian Adverse Driving Conditions Dataset

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arxiv 2001.10117 v3 pith:FFF37ROK submitted 2020-01-27 cs.CV

Canadian Adverse Driving Conditions Dataset

Matthew Pitropov , Danson Garcia , Jason Rebello , Michael Smart , Carlos Wang , Krzysztof Czarnecki , Steven Waslander This is my paper
classification cs.CV
keywords datasetconditionsadversecollecteddrivingautonomouscanadianlidar
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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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.

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