24 Jun '18, 9am

#UofToronto, #Uber researchers make advances with new autonomous driving algorithm

A self-driving vehicle has to detect objects, track them over time, and predict where they will be in the future in order to plan a safe maneuver. These tasks are typically trained independently from one another, which could result in disasters should any one task fail. Researchers at the University of Toronto’s department of computer science and Uber’s Advanced Technologies Group (ATG) in Toronto have developed an algorithm that jointly reasons about all these tasks—the first algorithm to bring them all together. Importantly, their solution takes as little as 30 milliseconds per frame. We try to optimize as a whole so we can correct mistakes between each of the tasks themselves. When done jointly, uncertainty can be propagated and computation shared. —Wenjie Luo, U Toronto PhD student in computer science Luo and Bin Yang, a PhD student in computer science, along with thei...

Full article: http://www.greencarcongress.com/2018/06/20180624-uotuber....

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