The participation of Toyota sends a signal that automakers are taking autonomous vehicles seriously, experts say. "Having someone like Toyota, with that kind of industry pull, is a very important step," Dave Sullivan, manager of product analysis for AutoPacific Inc., told Design News. "Google is one thing. But having a big automaker exploring this is another." Sullivan added that he has seen and photographed Toyota's autonomous vehicles being tested near its research center in Ann Arbor, Mich.
A Lexus equipped with a 360-degree LIDAR (light detection and ranging) laser on its roof can detect objects as far away as 70 meters. (Source: Toyota Motor Corp.)
Up to now, the most notable driverless cars have come from outside the auto industry's original equipment market. In the Defense Department's 2005 DARPA Grand Challenge, five cars developed by research teams independently traversed a 140-mile course, including mountain roads and hairpin turns. In the 2007 Urban Challenge, six more vehicles finished successfully. Google's autonomous cars are also said to have logged more than a quarter-million driverless miles.
Still, technical challenges remain if driverless cars are ever to become products. Designers of driverless vehicles have previously told Design News that GPS systems don't update quickly enough, and must be augmented by supporting technologies, such as inertial sensors. Driverless cars are also still "learning" to determine what's in front of them, and whether it's time to stop or go.
Sullivan said that the challenges will have to be addressed over many years. "The big thing will be getting consumers to trust this technology," he told us. "A lot of them still have issues with their phones and computers, so how can we expect them to trust an autonomous car?"
A phrase I hear all to often where I work is "All's you gotta do". It's what people say when they think something is going to be a simple task. It's usually said by people that will NOT be implementing the task. After all, if people can do it (drive a car, and some of them quite challenged in the brain-power category), then surely machines can do it if we add enough sensors and processors. Yeah, right. And that's just the technical side (this is an autonomous, hopefully intelligent, safety critical Robot we are talking about).
Wet hardware (humans) is truly an amazing instrument. Capable of taking far more information than we are aware, while filling in the blanks for missing/conflicting/incomplete info, and adapting to unforeseen circumstances. This is truly a deceptively simple task.
The other side is legal. Will Toyota or Audi accept the legal liability for auto accidents that occur when "self-driving"? In reality, they must since it's their "brains" behind the wheel. But, when I have to buy auto insurance, how is my provider going to bill me? Or will they bill the auto manufactures? Or will the government do what it seems to be best at, which is grant immunity to big business leaving us to fend for ourselves against 2 ton death machines designed to be as cheap as possible.
When I first saw the article title, the first thing that came to my mind was that Toyota was trying to re-brand its issue with unintended acceleration (really, it wasn't unintended ...)
I agree with Nadine, that the idea of cars driving themselves entirely--sophisticated sensors or not--is a bit daunting. I like the idea of a car being able to park itself in a lot and perhaps come back and pick me up, but driving on its own I'm not quite comfortable with. Maybe it would be OK as long as someone was always in the car to override any error--but wouldn't a self-driving car make a driver lazy? And I don't know about anyone else, but I love driving...there is something soothing about it, especially long drives with good music. I have used long drives as therapy! Have we become so preoccupied by other things that we can't enjoy or accomplish this simple act?
I think that if you really analyzed it, you'd find that the human body has a large number of sensors all attached to a very sophisticated "inference engine". Subtle changes to the pressure on your hands tell you a lot about how hard the wheel is being turned. The part of your body in contact with your seat back, in conjunction with your inner ear, senses acceleration, peripheral vision picks up rapid movement just outside your field of vision, your eyes are constantly adjusting to varying light conditions and so on. Replicating the human driving experience through sensors hooked to a computer is seriously complicated business.
Please do not do hijack a discussion thread again for crap websites. Granted discussion threads almost always drift away from the original topic, but what you did is outside the realm of good behavior here.
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I can't really speak to the issue of whether they could do this with stereo vision and Kinect. But I can vouch for the fact that they do have a lot of sensors on these vehicles. To know where they are, the vehicles combine GPS data with "low-G" accelerometers and gyroscopes.Then they have to filter that data through dual- and quad-core processors. To avoid obstacles, they use infrared cameras and, in some cases, LIDAR systems containing as many as 64 separate lasers to create a "point cloud" of obstacles ahead. I suspect that as they get better at this, we may see the number of sensors drop, but right now they still feel they need a lot of sensing capability to handle this chore.
I missed this at CES but I was only at the show for a day.
As a Californian, I'm NOT looking forward sharing the road with self-driving cars. Our Governor signed a bill authorizing driverless vehicles in 2013. Maybe I'm old-fashioned about it but I think human skills are superior to sensors.
Chuck, the thing that strikes me is the number of sensors. How many sensors does the current technology, the human driver, use? Not many. I really think these researchers are barking up the wrong tree. They probably only need an accelerometer and a stereo vision systems like the Kinect. Perhaps GPS would be useful as well.
In an age of globalization and rapid changes through scientific progress, two of our societies' (and economies') main concerns are to satisfy the needs and wishes of the individual and to save precious resources. Cloud computing caters to both of these.
For industrial control applications, or even a simple assembly line, that machine can go almost 24/7 without a break. But what happens when the task is a little more complex? That’s where the “smart” machine would come in. The smart machine is one that has some simple (or complex in some cases) processing capability to be able to adapt to changing conditions. Such machines are suited for a host of applications, including automotive, aerospace, defense, medical, computers and electronics, telecommunications, consumer goods, and so on. This discussion will examine what’s possible with smart machines, and what tradeoffs need to be made to implement such a solution.