Canadian Adverse Driving Conditions dataset. (April 2021)
- Record Type:
- Journal Article
- Title:
- Canadian Adverse Driving Conditions dataset. (April 2021)
- Main Title:
- Canadian Adverse Driving Conditions dataset
- Authors:
- Pitropov, Matthew
Garcia, Danson Evan
Rebello, Jason
Smart, Michael
Wang, Carlos
Czarnecki, Krzysztof
Waslander, Steven - 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.
- Is Part Of:
- International journal of robotics research. Volume 40:Number 4/5(2021)
- Journal:
- International journal of robotics research
- Issue:
- Volume 40:Number 4/5(2021)
- Issue Display:
- Volume 40, Issue 4/5 (2021)
- Year:
- 2021
- Volume:
- 40
- Issue:
- 4/5
- Issue Sort Value:
- 2021-0040-NaN-0000
- 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 - Journal URLs:
- http://ijr.sagepub.com/ ↗
http://www.uk.sagepub.com/home.nav ↗ - DOI:
- 10.1177/0278364920979368 ↗
- Languages:
- English
- ISSNs:
- 0278-3649
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 15720.xml