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Posted on 05/26/2014 3:15:22 PM PDT by Kaslin
I’ve been in the software business 20 years. So you can stop stroking your ego and deal with the facts.
The facts are this isn’t difficult stuff, the cars already have most of what they need to pull it off. A database doesn’t need to be continuously re-populated with lane switch information, the rules for the lane switching are already set the switching is already being handled by computers. If computers can do the switching computers can understand the switching.
Temporary road closure can be a problem. But even then the smart GPS have been programmed with those areas that tend to do this and are programmed to avoid them. And if avoidance isn’t an option there will be optical clues. Since the computer will HAVE to be able to see lights and signage manual signals and cones are not that tough.
You’re not paying attention to how the avoidance systems work. They go under the assumption that you DIDN’T see what they see, and they react, mostly stopping the car, sometimes with steering. Since the basic concept is that you didn’t see something the why (eyes closed, just not paying attention) is immaterial.
Your “one small example” actually shows why computers will be better. The computer will be able to see the brake lights, and won’t have the idiotic human instinct to “punish” the other driver with the horn, instead dedicating its entire action to actually avoiding the accident. Our standard action in that actually makes an accident more likely.
All of these things are solvable. Most of them are in the process of being added to cars right now. And no, the computers don’t use “one step logic”, they can handle multiple inputs and make the judgements. That’s computer logic happening right now in the medical field, and in military hardware.
I’ve got a 10 year old car and all the switches are fine, locks lock, windows go up and down. It’s not the 70s anymore, stuff actually lasts.
Nobody is bolting hundreds of thousands of dollars of equipment to the cars. That’s you holding onto your illusion.
Your list is all bunk. I’ll make you an iron clad guarantee, there will be self driving cars on the road by the end of the decade.
“I’ve been in the software business 20 years.”
In one of my early posts on this thread, I commented on the ‘IT’ mentality, vs the ‘car’ mentality.
Nail. Meet head.
I will never convince you.
Ok, I’ll still be here in ten years. I’ll put an appointment on my Outlook calendar to check for self driving cars in May, 2024 - assuming my appointment will hold for ten years...software reliability and all...
If you spent less time putting people in boxes and more time paying attention to the facts you might actually wind up as smart as you think you are. Meanwhile most of the “problems” you see are actually solved right now in other hardware (medical, military, mining, shipping), it’s just a matter of getting it in cars.
BEfore I explain all this, do you understand how celestial terrestrial and LAN based GPS operate?
I have a dumb question.
If this is so easy....what on earth is Google spending their money on?
Shouldn’t they just hire you?
IOW, doesn’t the reality that one of the largest computer related companies in the world is still trying to work out the details give you pause?
Isn’t illogical to dismiss my statements about the cost of the electronics - when Google is in actuality using the exact electronics I am describing?
Does it really make sense to claim the technology already exists and for the most part is already installed on cars....when Google have to bolt on 150k more to get it to work as a prototype?
All of these questions are outside the context of my argument. It challenges why we are even having the argument. It makes no sense whatsoever, unless of course, you are smarter than the collective knowledge at Google
Or perhaps it might be a tad bit more complicated than what you make it out to be.
Put another way....either Google should hire you....or you are wrong. And if you can’t march up to their headquarters, and bang on their door with a million dollar salary demand, I am right.
Disagree? Point out where my logic falls apart.
I used to think like you. That the whole self driving car thing would require a massive overhaul to our infrastructure, be hugely expensive, and probably would never happen. Then 3 things happened:
1 - GPS
2 - OnStar
3 - self parking
Each of these added a very important piece of the puzzle. With GPS the car gained the ability to know where it is in the world and relate that to a rendition of the world. OnStar gave the car interactive communication with servers allowing that rendition of the world to be updated. And self parking gave cars situational awareness without having to talk to a central server AND the ability to react to stimuli. Those 3 ingredients together are the basis for the self driving car.
Now there’s still a lot that needs to be added, especially on the situational awareness side, to be able to self drive cars will need to be able to “see” half a mile at least as well people, which means seeing a LOT of stuff. But that’s primarily heuristics and sensors. Not that tough, you can mostly solve that by throwing hardware at it. And if there’s one thing we have plenty of is hardware, that smart phone in your pocket has more computing power than the entire planet had when we landed a man on the moon. Think about the implications of that, the ENTIRE Apollo program, Houston, the capsule AND the lander (which didn’t have enough memory to run both radars at the same time), can be an app now (and you’ll be able to run both radars). All those problems you outline are solvable software problems, a lot of them are solved even, they’re just solved on hardware that’s too big for cars. At least for now.
Google is barking up the wrong tree, at least in the short term. They’re still trying to solve the problem the old way. Which makes sense for them, they are a central server farm oriented company, that’s how they think. Their business is structured around the idea that you get your device to talk to Google and let Google handle it. Which is fine for what they do, and eventually could work for the old sci-fi model of smart roads driving cars for everybody. Which is how we all thought this problem would have to be solved. But it isn’t. The DARPA challenge (which oddly enough Google participates heavily in) is how this problem will be solved, it’s the path the car companies are taking, though I’m not even sure they all realize it.
I’m not smarter than Google, I’m seeing the puzzle differently. Who knows, eventually we may go to their path. There are certain long term advantages to a server run system, it’s great for dealing with traffic jams, and can interact directly with various DOT traffic control programs. But the big punchline is we can get to self driving BEFORE that system is in place, and we ARE getting to it. Whether you’re willing to admit it or not, we’re constantly adding more situational awareness to our cars, and more ability for them to react.
“BEfore I explain all this, do you understand how celestial terrestrial and LAN based GPS operate?”
How is it supposed to use “LAN based GPS” when it’s outside the LAN GPS property range? Kinda hard to make it to the destination when it’s navigation is fluctuating 100s of meters off the route.
I’m not sure why you believe Google’s is a ‘server run system’ any more than anything else that is out there. As far as I can tell, the only thing ‘server run’ is maps, which would be downloaded.
I’m not sure you know what LIDAR is. LIDAR is what Google says they are using. It is not a server system - its a rangefinding and mapping system. LIDAR sends out tens of thousands of laser beams every minute, and receives them as they bounce off of a target. Its a laser range finder on steroids. This creates an enormous number of points. Each point will have a PNEZ (point number, northing, easting, elevation). Now this is where the software comes in. It has algorithms that detect ‘that’s a car’ from a cloud of points, for instance. We use a version of this algorithm every day, and a LIDAR scan of a busy city street will somewhat magically erase the cars from a point cloud, for example.
But this is where is gets more advanced. Rather than deal with the ten thousand points that make up a ‘car’, the software creates a ‘block’ that represents a car. And the programmers have to spend endless hours programming in what a car ‘block’ should usually do. I hope you can see how very different this is than an accident avoidance system that senses ‘yes, there is a large object in front of me’. Google software has to know speed, direction, 85th percentile driver behavior, etc., so it can know how to act next to this car - not just in an accident avoidance situation, but all the time. As in be smart enough to not ride in somebody’s blind spot, as in ‘read’ what a driver that is merging is doing, to let him into traffic more smoothly, as in calculate whether or not it has time to pass a slow car, before exiting the freeway...and adjust that if the car ‘block’ moves or changes speed.
And Google now has the nearly insurmountable task of anticipating every possible situation a driver may encounter. BTW, LIDAR can usually read paint on the pavement - I honestly don’t even understand how, but it must deal with the paint absorbing more of the laser beams than the surrounding pavement. Reflective signs are the same way. So I imagine it will rely to some extent on OCR to read signs. Every LIDAR scanner I have ever used is also equipped with a high resolution camera.
Nothing I have read has indicated this is anything but ‘on board’. That makes sense, since LIDAR files are so large.
Anyway, this is how Google is doing it. There is no ‘smart road’ or ‘system’, any further than having a good ‘system’ of maps of the area. The really important inputs are the real time world around the car. IOW, you are considering the task of ‘navigation’, vs the much harder task of ‘driving’.
This is quantum leaps above what you are envisioning - and it has to be. Is it possible? To an extent - similar to most other software, there would be constant ‘patches’ to download, as real world use produced situations that Google had not anticipated. LIDAR has revolutionized the survey industry - cutting field time to a fraction of what it once was. But we still have to do ‘data extraction’...as in go through the piles of data points, and assign a ‘D’ to the PNEZ...making it PNEZD. Its very time consuming...now we do have computers that help, with algorithms that erase cars, and interpret the ground line vs vegetation - very powerful software. What Google is attempting to do is similar, but no longer in a static world, and infinitely more complicated, and nearly instantaneously. Possible - yes. But a huge mountain.
Is it worth it? I doubt it. I don’t think the cost will be justified, especially in light of maintenance tasks (just putting fuel in a truck for instance) that can’t be done automatically. And I really do believe this stuff will be too delicate for commercial use....GPS won’t work well in a storm, sensors blocked by ice, RADAR ineffective in dusty conditions, etc.
Its an absolute non-starter for personally owned vehicles. The cost is too high, and the computers probably take up the back seat.
And we haven’t even begun to discuss how people will try to hack these vehicles. Another fear is that more and more components will become ‘drive by wire’, in order to be easily automated - brakes, steering, throttle. This stuff does break, and it can go terribly wrong....and it can be hacked.
Anyway, this is the world Google is operating in. A car driving down the road is a dynamic computer problem, with thousands of computations being done every second, with advanced algorithms ‘thinking’ like a driver would.
The accident avoidance system - its the beam that keeps the elevator door from slamming on my hand.
We’ve already resolved this in airlines, shipping and military.
Once the asset is within range of property the local GPS, a separate system from celestial GPS, will guide the vehicle exactly where it needs to be.
Drones go pretty much where ever we need them and right through a bedroom window when required.
This will be trivial to prove in court because the robot car will be storing video from all cameras, as well as its debug log, in some sort of a "black box." As you, the owner, are not required to pay attention to driving, it will be one machine (the car) vs. another (the government.) If the car could not see the signs, it will be clearly a fault of the government because the robot is an objective judge of what is visible and what isn't, down to the last pixel.
I would rather prefer this scenario because it would be unfair when an LEO accuses the driver of not following the rules when those rules are poorly presented or missing entirely. As a human, you cannot present evidence of what you saw. As a robot, the car can do that. After a short while the police will switch from hunting the drivers to "programming" the cars by maintaining the signage. A passenger in a robot car, just like in a human-operated bus, won't be responsible for following the rules of the road. This will remove a considerable percentage of abuse of power by LEO, as they won't have as much power anymore over the occupants of the vehicle.
It is not technologically challenging to deliver a large machine from Auckland, NZ to Paris. However this is work that has to be done by someone - by many people, using many different vehicles. Google is implementing something that theoretically has a solution. But not every mathematical solution can be easily and accurately used in practice - see Navier–Stokes equations, for example. (They are solved by CFD methods.) This is the work that takes time and money.
My question was not whether the robot car could win in court. My question was, how will they know to pull over? I guarantee you that at some point in some radar trap town, there will be a cop who wants to pull them over. And if sirens can make them pull over on a desolate roadway somewhere, that would be a real cool way to hijack an expensive shipment of electronics.
Ah, sorry. The answer to that is even simpler. If the camera can see a traffic light several hundred yards away, it probably can see bright blue and red flashes ten yards behind. The pattern is unique, and it's trivial for a computer to figure out. (By the way, the same applies to other emergency vehicles.)
And if sirens can make them pull over on a desolate roadway somewhere, that would be a real cool way to hijack an expensive shipment of electronics.
You don't need a siren. Just park your own car across the road. The robot vehicle will stop. It will not make a U-turn and run away. However... this very method also applies to human-driven vehicles. I heard that gangs in Florida did this. The vast majority of drivers will not escape this trap - and those who escape are probably too dangerous as victims anyway. The criminals do not need a 100% result.
IMO, a gang that stops vehicles and steals stuff is not overly concerned about health and safety of the driver. If there is a human in the vehicle, he will be killed, or knocked out and left in a ditch. Perhaps there are gangs who are not willing to kill but willing to steal... but the robot will "dial 911" in its own way, and the thieves will be racing against time to unload that trailer without forklifts or a dock. If they simply steal the whole rig, they will be tracked by radio - the trailer is too large, and it offers many places for concealement of a small cell phone.
I’m not in the hijacking business, but I would think a truck on a lonely stretch of road is a better candidate for theft if there is no driver. No witness, and the crime is a much lower priority for cops if there is no dead or injured driver. Have you invested in the robot technology by chance? I’m not against it, but I can see that there will be lots of problems, some of which have not been foreseen.
There would be no cops at all if the rig is human-driven. It is possible to stop the vehicle without alerting the driver - and then it's too late. For example, park two of your cars so that they look like crashed one into another (and block the road.) The trucker will stop and exit the cab to see what's up. If he doesn't, an accomplice with a handgun may jump onto the tractor and point a gun at him. No dialing 911 in this situation. But a robot would send the signal to the HQ, gun or no gun.
Have you invested in the robot technology by chance?'
I have exactly zero investments into stock market. I am not a gambler. I have some bonds, though. I am not working on robots myself, but I work with similar equipment and have a rough idea what robot builders are up to. Sure there are problems... but what would you say in the year 1880 if someone tells you that soon people will be riding in horseless carriages, ten times as fast as a horse can run, and hundred times as far? A journey of a thousand miles begins with a single step.
Celestial GPS may be accurate enough for aircraft beyond their takeoff/landing however it is not accurate enough for over the road trucking. One has a margin of error of thousands of feet while the other is less than 10 feet.
What’s the margin of error for flying something through a 2’ x 3’ window?
What LIDAR is is more power than what they need for the problem. That’s Google Segwaying the problem. You simply don’t need that level of detail to drive a car. People don’t have anywhere near that level of spacial analysis and we’ve been mostly successfully driving for a long time.
It’s 2 quantum leaps more intense than they need the system to be. People don’t work that hard at driving. I read an article in a motorcycling magazine in the 90s about how many “driving actions” the average driver takes. I forget the numbers but they were stunningly low with drivers of automatics doing the least, then sticks, then motorcyclists. The simple reality is that we DON’T make thousands of calculations a second while driving, heck we don’t even makes dozens a minute, and a computer won’t have to.
Google is over engineering the problem, and you’re criticisms show exactly why. You’re right in why that system will not work. Which is also why that is not the way self driving cars ARE happening right now.
‘Flying something through a 2 x 3 foot window’ is a margin of error much less than GPS. The films of ordinance going through windows are using laser, electro-optical and command guidance terminal homing, not GPS.
If you want to consider the accuracy of GPS-guided munitions you should look at the JDAMs. JDAMs have a CEP of 10m -and that’s with military-band GPS, under ideal conditions.
Commercial GPS is completely unsuitable for auto-piloted trucking. They’ll need something local to the vehicle such as radar, radio triangulation, etc. to true the GPS.
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