The reason is that super narrow roads, including country roads and urban back-alleys have occasional wide-spots and turn outs where people can pass. They have to, to be two-way. And these will all be on the map. Cars on such a road would desire traffic data about other cars on the road. They will be able to make predictions about when they might encounter another car coming the other way. Most interestingly, one or both of the cars can adjust their speed so that they will encounter one another precisely at one of the wider spots where passing can take place.
In fact, if they do this well, they might drive a one-lane road at a nice fast speed, barely slowing down in these wider passing zones, in part because by knowing the width of the vehicles they will be able to confidently pass quite closely. If a robocar is meeting a human driven car, it would leave some slop, picking the right passing zone, arriving early in case the other car is faster than expected, waiting if it is slower.
Pros & Cons of Google’s Restructuring
Everybody has heard about Google’s restructuring. In the restructuring, Google X, which includes the self-driving car division, will be a subsidiary of the new Alphabet holding company, and no longer part of Google.
Brad Templeton was a consultant on that team and recently offered some perspective on how the restructuring might affect Google’s self-driving cars.
This remarkable ability would allow us to build low-traffic roads and alleys which are mostly only one lane wide, but which could carry traffic fairly quickly and safely in both directions. Gassee’s problem is far from a problem – it’s actually a great opportunity to vastly decrease the cost and land requirements of road construction. I wrote about this a couple of years ago, in fact.
Even without communication, a robocar would do pretty well here. Its map would tell it, should it encounter another vehicle on the road it can’t pass, just where the closest passing spot is. It could back up if need be, or if the other car should back up, it could nudge in that direction, or even display instructions to a human driver on a screen. It would be able to do this far better than humans could because of its accurate measurements and driving ability. Generally, any human car should defer to the robocar’s superior knowledge and superior ability to manage a close pass-by. The car would figure it out the moment it sensed the other car, and immediately adjust speed to meet at a passing point, or possibly to back up. Unlike humans, they will be able to drive in reverse at high speed if they have 360 degree sensors.
Human drivers could actually play a role in this. Those running a mobile app like WAZE could know about other cars running the app, or robocars. The app could give them advice to speed up or slow down to encounter the other car at a wide spot. Of course, if there are cars not using the app, they would just fall back to the old fashioned human approach. One could imagine a sign at the entry to a narrow road saying, “We recommend running the XYZ app for a smoother trip down this road.”
Not all these problems that people put forward were as easily resolved as this one, so I am not calling for people to “shut up and let the experts get to work.” There are many problems yet to be solved. Most of them can be be solved by punting because you don’t need to drive everywhere. Though Google has shown that having a steering wheel that can be grabbed while moving is a bad idea, I do expect most cars to have some form of control that can be activated when a car is stopped. If a road needs the human touch, it will be available.
About the Author
Brad Templeton is a developer of and commentator on self-driving cars, software architect, board member of the Electronic Frontier Foundation, internet entrepreneur, futurist lecturer, writer and observer of cyberspace issues, hobby photographer, and an artist. Templeton has been a consultant on Google’s team designing a driverless car and lectures and blogs about the emerging technology of automated transportation. He is also noted as a speaker and writer covering copyright law and political and social issues related to computing and networks. He writes and researches the future of automated transportation at Robocars.com