FILE PHOTO: A still frame taken from video released March 21, 2018 shows the exterior view of the self-driving Uber vehicle leading up to the fatal collision in Tempe, Arizona, U.S. on March 18, 2018. Tempe Police Department/Handout/File Photo via REUTERS ATTENTION EDITORS - THIS IMAGE WAS PROVIDED BY A THIRD PARTY. NO RESALES. NO ARCHIVE.
A few weeks after a woman was struck and killed by an Uber self-driving SUV in Arizona, the crash was recreated using heat seeking, thermal-imaging sensors. With that night vision technology – used by the military and luxury cars for decades – the pedestrian is clearly identified more than five seconds before impact, which would have given the car time to stop or swerve.
Since the Uber accident in March, autonomous car researchers’ eyes have been opening to the need to teach robots how to drive in the dark and avoid people who wander into the road. After all, pedestrian deaths are up 46% since 2009, and three-quarters of them happen at night, according to federal data. One fairly obvious solution has been in some cars for almost 20 years: night vision that can detect the heat of a human body.
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