Companies around the globe are racing to create fully autonomous vehicles that can handle anything the road throws at them. But, according to the University of Toronto's Steven Waslander, there's one scenario that hasn't yet received nearly as much attention as it deserves: winter.
"Winter conditions aggravate the remaining challenges in autonomous driving," says Waslander, an associate professor at the U of T Institute for Aerospace Studies in the Faculty of Applied Science & Engineering.
"Reduced visibility limits perception performance, and slippery road surfaces are a big challenge for vehicle control."
To drive safely in all conditions, including winter, Waslander says autonomous vehicles need to fully observe their surroundings despite limits to their sensor range to get advanced warning of challenging situations and to react quickly to changing conditions.
Along with fellow U of T Engineering researchers and members of the U of T Robotics Institute - including Timothy Barfoot, Jonathan Kelly and Angela Schoellig - Waslander is leading a new partnership that will address these challenges by bringing together the best minds from academia and industry. The project, called WinTOR: Autonomous Driving in Adverse Conditions, is a new collaboration that aims to transform Toronto into a global hub for research and development related to autonomous driving in winter. Corporate partners include leading companies in the autonomous vehicles sector such as General Motors Canada, LG Electronics, Applanix and Algolux.
It's one of six projects from U of T to receive support from the Ontario Research Fund. Five of the projects are led by researchers from the Faculty of Applied Science & Engineering, while the sixth is led by a researcher at the Faculty of Dentistry. (See the full list below.)
"With this investment, the Ontario Research Fund is supporting important work of U of T researchers that will benefit all Canadians," says Christine Allen, associate vice-president and vice-provost, strategic initiatives. "And it's exciting to see that two of the initiatives to receive funding, focused on advanced robotics and innovative mobility, are among U of T's key areas of strategic, interdisciplinary focus.
"Through these Institutional Strategic Initiatives we're mobilizing interdisciplinary cross-divisional research and collaboration to address societal challenges. We're committed to developing these initiatives to a scale that can attract support from government, philanthropic or industry sources - and WinTOR is a terrific example."
The WinTOR team already has a track record of success. Last year, Waslander and his collaborators published the Canadian Adverse Driving Conditions (CADC) dataset. Created using the Autonomoose, a self-driving vehicle designed by Waslander and his team, the open-source data record real winter driving conditions on roads in southwestern Ontario.
The valuable dataset is already being used by researchers from around the world to train new AI software. It joins a long list of research accomplishments from the project's research team, whose combined expertise covers the full extent of autonomous driving perception and planning domains, including object detection and tracking, robust state estimation and calibration, localization and mapping, prediction and planning and safety-critical learning control.
