The Cyclist Problem
February 3, 2018
Autonomous cars have a potentially fatal flaw: They struggle to detect and react to cyclists on the road. According to a January 2017 report by IEEE Spectrum, bicycles are generally considered “the most difficult detection problem that autonomous vehicle systems face.” It’s not surprising: Bikes are relatively small, nimble, and sometimes unpredictable, and human drivers have a hard time sharing the road with bike riders as well. In 2015, 818 cyclists died in collisions with motorists, and 45,000 experienced injuries in car-bike collisions. In 2016, the number of deaths rose to 835. Seventy-one percent of those happened in urban areas.
It’s a multifaceted problem. Some drivers haven’t been educated as to how to properly share the road with cyclists, some cyclists don’t know how they’re supposed to behave, and infrastructure in many places doesn’t facilitate peaceful coexistence on the same roadways. Autonomous vehicles, with their advanced sensing capabilities and predictable, programmed behavior, offer the opportunity to help change that. However, we’re increasingly learning that A.I. can amplify our own biases and human failings. If humans aren’t doing a good job of detecting and preventing vehicle-bike collisions, how can we create machines that do the job even better?