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.
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.