As someone who regularly spends several hours a week on a bicycle, wondering if the diesel rumble of a truck coming up behind me is the last sound I’ll ever hear, I was sorely disappointed to read that help, in the form of robotic vehicles, might be a long time coming.
A story by Peter Fairley on the IEEE Spectrum blog looks at the successes that self-driving car companies have had in developing software and sensors that can recognise other cars and predict their movements, and contrasts it with the failure to do the same with bicycles…
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. “A car is basically a big block of stuff. A bicycle has much less mass and also there can be more variation in appearance — there are more shapes and colors and people hang stuff on them”.
The autonomous vehicle technology is already starting to appear in automated emergency braking (AEB) systems, which is great for avoiding collisions with other cars, but not so helpful for cyclists…
AEB systems still suffer from a severe limitation that points to the next grand challenge that [autonomous vehicle] developers are struggling with: predicting where moving objects will go. Squeezing more value from cyclist-AEB systems will be an especially tall order, says Olaf Op den Camp, a senior consultant at the Dutch Organization for Applied Scientific Research (TNO). Op den Camp, who led the design of Europe’s cyclist-AEB benchmarking test, says that it’s because cyclists movements are especially hard to predict.
[Computer scientist Jana ]Kosecka agrees: “Bicycles are much less predictable than cars because it’s easier for them to make sudden turns or jump out of nowhere.”
It’s not completely out of our hands, though. As artificial intelligence systems slowly learn to cope with bicycles, cyclists can try to see the road as a self-driving car might see it and do their best to ride predictably. At least it’s more comforting than just hoping the guy who’s about to pass you is looking at the road and not at his smart phone.