In the news is a story of a driverless fatality in Tempe, Arizona. In the dark of night, a woman walking a bicycle across two lanes of traffic was struck and killed by one of Uber's new autonomous vehicles. Behind the wheel was a driver who was momentarily distracted, probably by a tablet in his hands, while the autopilot of the car cruised along at just under 40 miles per hour and ran the poor woman down. The article I read about the story quoted at least two experts who said that the lidar equipped machine should have easily seen the pedestrian and avoided the accident. I was most interested in the final paragraphs.
Raj Rajkumar, a Carnegie Mellon University professor and founder of an autonomous-vehicle software company that he later sold, suggested the laser sensor may have had a blind spot around the vehicle because of its position mounted on the roof. Still, he said, he would have expected the software to have reacted.
“Legally speaking, the pedestrian may be at fault,” Mr. Rajkumar said. “But mature, reliable self-driving vehicle technology would have done better by slowing down or changing lanes, and this major incident would have been prevented.”
I have been in the IT industry for decades and one of the most fabulously successful products ever was the iPhone. I've been using mine for 7 years. My mother has been using hers for 2 months and she gets lost all the time. She is computer literate, but a lot less so than I. The distance between what I can digest as a professional at this stage in my career and what ordinary folks can understand is the gap into which a great deal of VC money is thrown in expectation of aggregating many multiples of that in consumer spending. Yes, I have a very new, very advanced, very capable iPhone device in my pocket and I use it all of the time. It works exceedingly well for me because I am highly discriminating in my consumption of applications, and I know how application designers think when they are building for the iPhone. In that way I am immune to bad apps, and I don't get lost. Half of all wisdom is knowing what to throw away. Simple works best.
So while journalists will have ready access to founders and professors who will state what might be professionally obvious, pedestrians and the rest of the world are puzzled as to exactly what went wrong. I suspect as the story of autonomous vehicles grows, we will all find out sooner or later, most likely later. It has always been my opinion that as cars learn to pace themselves in traffic that we humans are going to have the hardest time understanding their protocols. Indeed the future of driver education will not focus so much on skills of the drivers as to understanding how cars have been programmed to think about themselves and about traffic. That's a long, dark and narrow road for all of us to travel.
What's legal today ought to be perfectly obvious. We have had crosswalks for generations. We have had crosswalks in law for generations. These things are perfectly obvious because we've had a very long time to learn the legal and physical truth about crosswalks. Lidar? Not so much. There will not be human and animal analogs for the way lidar perceives or the way cars will communicate with each other. We will have to learn new concepts and adapt. Or we will simply have to drive.
What is it like to drive in traffic with cars that don't have human drivers? We are going to have to change our perception. We know 'idiot drivers' and are quick to identify their idiosyncrasies on the road, because we understand human inattention. He's weaving like a drunk. She's obviously on her cellphone. He's obliviously blasting beats. She's a student driver. He's an old man. But Tempe offers a perfect example of a driver unable to recognize his own vehicle's inattention.
I've been a gearhead all my life and am probably unusually attracted to and informed about cars given my inexperience in actually repairing them. So I am fairly geeky into racing and the skills associated with demanding driving. I will trust autonomous driving machines when they start winning rally races and drifting competitions. Analogously, when computers were only reliable in playing an excellent game of tic-tac-toe, the mastery of chess was the benchmark for intelligence. I think that's were autonomous cars are now, four squares of tic tac toe rather than just three, with three being mere cruise control and lane alerts. It ain't chess, and it's far from go.
Here's the thing though. When machine learning figures driving out, it's still going to think like a machine and not like a human. That means there will be hacks and vulnerabilities machines will have navigating 3d spaces that we humans will have to study very diligently to understand. I expect a lot of that diligent conceptualization to happen at Carnegie Mellon, but not in DMV parking lots. We can only hope that traffic law changes very slowly.