A team of researchers is developing a dataset to fill a critical gap in self-driving cars’ learning models.
Researchers at the University of Maryland are working to make autonomous vehicles safer for blind pedestrians, reports Laurie Robinson in Maryland Today. According to the researchers, autonomous cars lack “solid data” for how blind pedestrians move and navigate streets and sidewalks.
“The oversight can hinder the ability of autonomous vehicles to safely predict the movements of blind pedestrians, whose behaviors, such as using a cane to feel the curbs or veering, might confuse current models, leading to potentially dangerous errors.” The research team is creating a dataset called BlindWays that uses real-world 3D motion-capture data to help the systems understand blind pedestrians more effectively.
In testing, the model reduced prediction errors by over 80 percent in some cases. “To enhance and expand the BlindWays dataset, the researchers plan to collaborate with organizations specializing in disability rights, mobility training and urban planning. These partnerships aim to diversify participants, locations and scenarios in the dataset.”
FULL STORY: Autonomous Cars Don’t Understand How Blind People Move Around. A Research Team Is Trying to Boost Safety.
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