Google Robot Car: The Future of Cruise Control, Convoys, Car-Sharing

Just when we think Google has run out of surprises, we learn from John Markoff at The New York Times that a small team of Google engineers has been quietly running robots on our highways. Not just one or two robots sneaking a few miles down a lonely country road late at night, but eight autonomous vehicles traveling more than 140,000 miles in the last year on everything from freeways to traffic-clogged downtown districts. I have viewed the route maps for several of these trips and can attest to the fact that Google’s car-bots have confidently traversed roads that would leave many drivers white-knuckled, from San Francisco’s pretzel-twisty Lombard Street to Big Sur’s narrow, cliff-hugging Highway One.

I sensed that something was up, from rumors of strange Google Street View vehicles seen on local highways.

I have been closely watching automotive robotics ever since attending the first DARPA robotic Grand Challenge in 2005, and I know Sebastian Thrun, the entrepreneurial Stanford professor and Google distinguished software engineer who co-created Street View and now leads the team who put Google’s car-bots on the road. And like others, I sensed that something was up, from rumors of strange Google Street View vehicles seen on local highways to word that a particularly bright Stanford robotics Ph.D. student had disappeared into the Google campus. But nothing prepared me for the sheer magnitude of the surprise. Thrun and his colleagues have accomplished something that even the most optimistic experts in the field thought was five to 10 years off. Little wonder that Thrun’s team jokingly refers to the effort as their “Drive-thru Manhattan Project.”

Before word of Google’s robot surprise, the consensus among researchers was that autonomous robotic cars would not be commonplace on our highways for at least two decades. That number will now have to be revised downward, but it would be a mistake to expect robocars to start appearing in auto showrooms any time soon. Barriers range from regulatory anxieties to the auto industry’s famously conservative engineering culture, and more than a few daunting technical challenges. The good news is that near-robotic vehicles are just around the corner and they are guaranteed to deliver more than their share of surprise along with some very tangible benefits. Here are a few developments that I think are especially likely in the near future:

Cruise control on steroids

The same technologies that allowed Google’s car-bots to find their way down the coast will be put to work making us safer drivers. Better sensors and artificial intelligence will deliver adaptive cruise control capable of responding to sudden slowdowns and anticipating fog-hidden pileups. These systems will link to data in the cloud (like Google Maps and Street View) to provide smart real-time hazard identification, routing and warnings when drivers are speeding above posted limits. Our cars will chide us if we tailgate and watch us as we drive and jolt us awake if are distracted or drifting off to sleep.

We can already buy cars that parallel park, but Sebastian’s team overcame an even greater challenge, teaching their car-bots to merge into freeway traffic. Merging is a social activity that that combines manners with Newtonian physics at 60 mph at a point typically located in a driver’s blind spot. Anyone who has been cut off by some jerk refusing to let them in, or tripped up by an over-polite driver slowing down to make space, knows just how complex this problem is. Google’s car-bots have perfect peripheral vision, software that reads the body language of the other cars and most importantly, no ego. Just as we already can buy cars that parallel park, I’ll bet that near-future telematic systems will help us merge, warn us of erratic drivers, and help us escape impending collisions. Of course these capabilities will arrive first in the luxury market, but thanks to Moore’s Law, what appears in a 2012 Acura or BMW will quickly trickle down to low-cost Kias, Minis and Civics.

Robotic convoys

Because Google’s car-bots were venturing onto public roads, they never left the parking lot without a stand-by driver behind the wheel and an engineer monitoring the software systems from the passenger seat. Robots operated in controlled spaces such as private industrial parks or on the battlefield could operate under different rules. The Pentagon’s research agency, DARPA, launched its 2004 Robotic Grand Challenge with the explicit goal of catalyzing the technology required to enable fully robotic convoys by 2015. The generals won’t get their wish that soon, but Google’s robo-triumph suggests that they will get the next best thing. Imagine a convoy comprised of a single human-controlled lead vehicle and a line of unmanned autonomous supply vehicles obediently following behind like a line elephants in a circus.

Fewer drivers means fewer targets—and fewer potential hostages. It also means different tactical driving strategies. Unlike humans, robots can safely tailgate at 60 mph comfortably hovering just a few feet off the bumper of the next vehicle in line. Robots can engage in evasive maneuvers that would challenge a Formula One driver, and they can take risks that would make a Medal of Honor recipient pause. Google’s car-bots are proof that we have all the technology needed to build autonomous convoy vehicles; now it is just a matter of production engineering.

Car-sharing becomes practical

Why buy a car when you can subscribe to one? This is the alluring premise behind services like Zipcar and City CarShare, but thanks to an assortment of small annoyances, car sharing is a tiny industry that remains more promise than reality. Advanced telematics could be what makes car-sharing practical by adding features calculated to protect occasional drivers and the cars they share. Collision-avoidance systems would spare drivers the grief of an accident and allow for lower insurance rates. Cloud-based mapping and traffic alerts would dramatically increase the convenience of shared cars and provide better monitoring and diagnostics for the system operators. Thrun even thinks we can create a service where instead of picking up your car in a nearby parking space, the driverless car will come to you like a well-trained spaniel.

I doubt Thrun’s self-fetching car will arrive soon, but his sentiment underscores just how transforming advanced telematics could be. The economics of car-sharing means that technologies too expensive to put in anything other than a high-end BMW could easily be incorporated into a new shared volks-vehicle for the masses. The result could be an entirely new industry and a profound shift in the notion of car ownership. Demographers are already noting a subtle shift in attitudes toward cars among twentysomethings. Unlike their parents, they are ever less interested in autos. This is true even in car-crazy Germany and California. In Japan, unhappy car dealers even have a term for it— kuruma banare, or “demotorization.” Give young people a convenient way to borrow a car when they need it, and interest in cars as an emancipating status symbol will plummet. This is bad news for car sellers, but a huge opportunity for an entrepreneur eager to create an entirely new industry.

So, when do I get my robot car?

No time soon. Robust robot cars for ordinary consumers may lie off beyond the second term of the Jenna Bush administration, but Google’s car-bots have made the path to them clear. True robo-cars won’t arrive out of the blue; they will evolve out of an accelerating evolutionary species radiation of ever smarter, more capable vehicles that will make driving safer and more efficient. In fact, by the time our cars show us out from behind the wheel, we will hardly notice because they will have been doing so much of the work already. In the meantime, keep an eye out for the occasional car-bot while you are stuck in traffic. They will be easy to spot as they will be the only cars driving below the speed limit and they won’t cut you off when you try to merge.

Paul Saffo is managing director of Foresight at Discern Analytics, and teaches at Stanford University.