Google’s driverless cars need a little more prep time before they can be released to driving consumers.
Google has great ambitions for its driverless cars, and the company believes that their vehicles will be on the streets by 2017. At the same time, however, driverless cars have their problems that their progress often blots out.
One major setback for Google’s next big thing has been the new California DMV regulations that mandate a driver’s seat and steering wheel so that humans can assume command should something go wrong in a driving circumstance. California’s hesitancy isn’t solely the state’s, seeing that there are a number of other states that are mandating the same thing (should they even want Google’s driverless cars to become a part of normal, everyday traffic). A number of states have yet to even consider the idea of driverless cars outnumbering current gas vehicles.
California’s regulations may prove tough for Google, with its eye on the next invention that keeps others scrambling to catch up, but its driverless vehicles have some hurdles of their own that the search engine giant must jump through before driverless cars are ready for the road.
One major problem with driverless cars, apart from DMV regulations, concerns technical glitches. In short, technical glitches are things that go wrong during a vehicle’s operation (with a computer, for example,) that could impact driver safety. One technical glitch pertains to traffic lights. It’s no secret that traffic lights, highways, and destinations change over time: new traffic lights are installed for driver safety reasons, new highways are created that lead to new businesses or expand highways due to traffic overflow, and so on. In these cases, however, driverless cars haven’t yet been trained to recognize new highways and stop lights.
Google’s driverless cars operate by way of Google maps navigation; so, when Google Maps are working properly on driverless cars, the cars themselves operate accordingly (they know where to go, what stop lights they’ll encounter along the way, etc.). With new offices, highways, and stop lights, however, Google Maps hasn’t yet integrated them – so Maps functionality is disappointing in such a case.
With that said, Google’s autonomous vehicles may have some sense of direction, but they’re not yet at the level of human understanding. Thus, driverless cars will disappoint in situations where they have no highway or traffic light on their Map (but one exists in reality). Getting driverless cars to drop off users may prove difficult.
Next, parking is an issue. Driverless cars are excellent at parking in basic parking lots that have one level only and are right outside of buildings, but what can they do in instances where there are multiple parking decks, say, at hospitals or baseball or basketball stadiums, for example? In such an instance, a driverless car user would be out of luck and forced to rely on his or her own understanding of the surroundings (and, if you’re going to a stadium for the first time, Google’s driverless cars couldn’t help you navigate a packed parking lot all that well).
Then there are weather conditions. Google’s driverless cars have recorded over 700,000 miles of navigation, but these have all been performed during excellent weather. Google’s driverless cars haven’t yet navigated rain, snow, sleet, or hail in order to know whether or not they’re ready for the consumer market. If you’ve lived in Minnesota or Alaska, or driven in hard rain and snowstorms, you’ll know that current vehicles don’t do the trick (for many of us). What can Google’s driverless cars contribute in such instances? Technologically-advanced vehicles that put us no closer to safety than current ones won’t win over the majority of average consumers.
Last but not least, Google’s driverless cars are having trouble with pedestrians. This may make some of our hearts skip a beat, but Google’s driverless cars do come with top-car sensors that stop when an individual crosses the street. However, some reports suggest that driverless cars are having trouble distinguishing police officers from the general public. Of course, this will require some effort regarding computer input, as well as how Google will expect its driverless cars to behave when approached by an officer, etc. Google can innovate in this area in excellent ways, but it’ll require some time beyond highway testing.
What we see with Google’s driverless cars is great potential, where consumers can start to enjoy being out on the road again without added stress from on-the-road activity. At the same time, using computers in vehicles complicates things. Computers, like everything else we take for granted, stop working, malfunction, need repair, and often perform terribly when commands aren’t input correctly. It’ll be no different with Google’s driverless cars.
Driverless cars have proven efficient in basic driving skills, but driving through various weather conditions (and dealing with other swerving and speeding vehicles on the streets) will prove to be its greatest obstacles yet.