It happened so fast, I had no time to react. I was headed home on my bike when a pickup truck came roaring past on the left, avoiding me by mere millimeters. It wasn’t any skill on my part that prevented a painful accident. It was pure luck.
If Google has its way, luck won’t be a factor in these all too common car vs. bike showdowns in the near future. Much has been written about the company’s autonomous cars, which replace drivers with sensors, servos, and many lines of computer code—some of which was designed specifically with roadies in mind.
“The way we approached the problem is, ‘What’s the right, safe thing to do in each one of the cases?’” says Nathaniel Fairfield, a principal engineer at Google X. “We look at a scenario or a class of scenarios, and we get a lot of data and a lot of experience. We look at how people have been interacting. What’s your instinct? What would I do in this case? And we also look at how different behaviors and approaches can work out.”
The main goal (and challenge) is to avoid collisions with cars, bikes, and pedestrians. “In most cases, you really can get ahead of the problem. Instead of getting into a situation where you suddenly have to make a call about which way to go, you can anticipate the situation.” That means the autonomous car needs to sense oncoming cyclists well ahead of time, and then determine whether it can clear the rider long before a possible collision.
To do this, the car has cameras, LIDAR, and radar that give it a 360-degree view of its surroundings. The cameras distinguish between things like stoplights and road signs; the lasers and radar determine the speed and direction of moving objects.
While the majority of the programming is designed to track any moving object—be it a car, bicyclist, or pedestrian—there is also some bike-specific code on board. “Something we have found to be important are the hand signals,” says Fairfield. “When a cyclist sticks out their arm, they are not just doing it for fun or accidentally. It is a very clear, very strong signal, so we have taught the car to recognize cyclists’ hand signals.”
The car also knows what it means when a rider claims the whole lane. “[The cyclist is signaling that he] doesn’t want to be passed right now,” says Fairfield. “For a car driver, that’s sort of a judgment call: ‘Is the cyclist trying to claim the lane, or should I blast past?’ That’s something that we are very responsive to. We really pay attention to when other road users are acting in a way that is sending us a message about what their intentions are.”
The Google engineers have also given cyclists the right of way at stoplights. “When we are stopping at a stoplight and a cyclist pulls up right next to us, we try to figure out what we should do. Should we go first, or should [the cyclist] go first? We can afford to wait and be conservative. When the light turns green, let [the cyclist] make the first move,” says Fairfield.
Of course, the Google self-driving car isn’t subject to road rage, either. “We are not sitting in that car feeling that adrenaline, getting irritated or angry. We are sitting back here, days later, looking at all this data and trying to understand what the appropriate response is and making a cool, collected data-driven judgment call,” says Fairfield.
In the end, it boils down to one thing cyclists have been waiting to hear from car drivers for a long, long time: cyclists, like pedestrians, are particularly vulnerable road users. Google wants to be extra careful around them. And that could make all the difference.
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