Living and driving in various snowy, sleety, slushy road conditions where the lines on the road are partially/completely covered, my first thought was how this would work during those conditions. I think my vehicle unexpectedly "assisting" me by applying torque to the wheel in one direction or another while I'm on a snowy/slushy road would be a danger of its own. Even if the lines are only partially covered with reflective white snow, how would it decipher in/out of lane position? This is one of those technologies that I would wait until a number of critical revisions have been tried out successfully before I would be comfortable adopting it myself.
Now I can safely text-and-drive!! Other than more complacency while driving, I wonder about the auto-correct function (if enabled). If you're fully alert, but have to suddenly swerve into adjacent lane to miss a rock or a kid, how hard would you have to fight the steering?
I would think it will takes years to perfect all the different nuances and variables that are necessary to create such an algorithm. As much as I applaud the effort and know eventually that the technology will evolve to a point that it's highly reliable and effective, it's going to take a long while until people feel confident, especially for setting the sensors so it actually initiates a correction, not just an alert. To me, it's like those rear-view cameras designed to help you back up. Have one on my car. Totally don't trust it.
I agree it would be nice if everyone didn't drive distracted but the reality of the data shows that distracted driving, I believe, is the largest cause of accidents. So I think it's great that Ford is looking to introduce something that will save lives.
I am a little leary that this product will be the best thing in the world because often the first solution on the market is the one that has the most problems and everyone learns from. However, you would also expect a safety device like this would require significant testing.
I, too, would love to see the algorythm. To me there seems to be a lot of variables and extenuating circumstances.
I understand what you mean about not driving drunk, drowsey or distracted. But life intervenes sometimes, especially for parents of young children. During those years, you're always drowsey and distracted. I remember filling a tippy cup with milk while driving. I held the tippy cup between my knees and opened the milk carton while steering. Coulda used this technology then. Give me the Google car that drives itself.
I'm wondering what sort of verification testing Ford did as far as assessing false positive and negative warnings and what their potential legal liability might be for accidents (proveable or not) caused by same. Relevant because one day this will be a control, rather than advisory, technology.
The algorithm that my employer puyrchased was never released because the project was cancelled because the technology did not work as claimed. So they are safe on that one. But there are quite a few systems around presently, since the trucking companies find this effort very useful. And I can tell you that there are very few things more boring than watching a video recording of a truck driver getting drowsy.
There is a system that monitors eye blinks, and at least one that watches the lines on the road, another that tracks the drivers focus, and then there was the one we had that tracked the drivers head movements. The failure is that some people can fall asleep without ever nodding their heads.
I'd be very interested to learn how the algorithm was verified, and what the legal liability might be in cases of accidents caused. --- proveably or not -- by false positives or false negatives. Granted, this is a warning, not a hard correct, but it's all the more interesting because that's where this technology is headed.
Having worked on aproject intended to provide a similar benefit, I can appreciate what Ford is accomplishing. The system will undoubtedly provide a warning, not a correction. My suggestion has been for the signal to be a recorded dog barking, and Ford is welcome to use that idea for free. The challenge is always to develope an algorithm that does not create false alarms. My employer had purchased the rights to some software and hardware that did not really work, except for the one sample that came as the demo. The most difficult part of the development is the code that determines the baseline that the drowsy driver deviates from. The problem with some systems is that they do the calibration right after the trip starts, which is usually before the driver enters the boring part of the trip. We verified that, at least for "big trucks", it was far better to do the calibration about 20 minutes after the trip began.
But the Ford plan of watching for lane departures is not so very new and original, so either they have licensed the technology or found a fundamentally different approach, which the two camera description would imply.
The one remaining problem now is liability, since some fool will fall asleep and claim that "they said it would keep him safe". It will be very interesting to see the instructions and disclaimers associated with their new system.
I think you missed the part of the article that strongly implied that each of the 3 steps were user-configurable as to capability; thus, if you didn't want the "auto-steering" mode, you could turn that off while keeping the warning, etc. Or you could just buy a car that would let you suffer the consequences of driving sleepy!
Robots that walk have come a long way from simple barebones walking machines or pairs of legs without an upper body and head. Much of the research these days focuses on making more humanoid robots. But they are not all created equal.
The IEEE Computer Society has named the top 10 trends for 2014. You can expect the convergence of cloud computing and mobile devices, advances in health care data and devices, as well as privacy issues in social media to make the headlines. And 3D printing came out of nowhere to make a big splash.
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.