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The Self-Driving Car's Bicycle Problem

IEEE Spectrum Robotics Channel

Nuno Vasconcelos, a visual computing expert at the University of California, San Diego, says bikes pose a complex detection problem because they are relatively small, fast and heterogenous. Consider the Deep3DBox algorithm presented recently by researchers at George Mason University and stealth-mode robotic taxi developer Zoox, based in Menlo Park, Calif. On an industry-recognized benchmark test, which challenges vision systems with 2D road images, Deep3DBox identifies 89 percent of cars. More automakers are expected to follow suit as European auto safety regulators begin scoring AEB systems for cyclist detection next year. In December, Wiedenmeier warned that self-driving taxis deployed by Uber Technologies were violating California driving rules designed to protect cyclists from cars and trucks crossing designated bike lanes.