When was the last time you got a traffic ticket, dear reader? If and when that happened, it was most likely for something stupid and somewhat reckless such as texting, speeding or not noticing a red light in time to stop… or perhaps you didn’t see anybody coming and you were in a hurry. In any case, these errors behind the wheel are reckless, sometimes dangerous and self-serving. Basically, human nature in a nutshell. Very few of you have likely been pulled over for going too slowly. For those that have, congratulations, you now have something in common with the A.I. behind Google’s self-driving car project.
Black Friday 2017 Deals: Find Great Deals on Android Smartphones, TV’s, Smart Speakers, Chromebooks and More.
On November 12, in the afternoon, a Mountain View police officer noticed a line of cars backing up on a 35 MPH street, stuck behind a car putting along at 24 MPH. Upon closer inspection, the officer found it to be a Google self-driving car. He pulled it over to ask about how the car figures out how fast it should be going and to let them know that it was unlawful to impede traffic in such a manner. Google limits the vehicles to 25 MPH in autonomous mode for safety reasons and this generally works well in most areas, with the vehicles lawfully not allowed to operate in areas where the speed limit is above 35 MPH. It seems, however, they’ll have to raise the limit a bit or switch to manual control at times to avoid holding up traffic like what happened today.
With the information concerning the laws in hand, the Googlers set off on more automated adventures without a ticket. For those keeping score at home, that’s roughly 1.2 million miles, or about 90 years of cumulative experience, without a ticket or an at-fault accident. Despite obvious flaws springing from being fully automated with an option for human takeover, which are being ironed out, the Google self-driving car project maintains a near-spotless driving record, showing that it’s just about ready for prime time. Testing and tweaking will continue for some time, with complex machine learning algorithms and networks hard at work each day thereof and with every autonomous vehicle’s consumer-transporting journeys.