The autonomous super-size dump trucks drive along carefully pre-programmed routes using GPS.
We're still a long ways away from practical and safe self-driving cars. AI and computer vision just isn't there yet.
5 years is a fantasy.
Continued exponential increases in device computing power is by no means guaranteed now that chips are at the 14nm feature size.
And the recent progress in AI can only be partially attributed to improved computing power - much of it was from improved approaches to training neural networks. We could stumble into another AI winter and have to wait another 30 years for the next round of big algorithmic AI breakthroughs.
I guarantee you that self-driving cars will not be the mainstream even in 15 years. Probably more.
Want to make a Long Bet on that? I'm willing to bet up to $1000 USD, loser pays winner's choice of 501(c)(3) US charity org, that self-driving cars will be mainstream in under 10 years.
But something I can summon with an app and take a nap? 50 years may be too soon.
I don't live in the United States where every CS graduate gets a Ferrari as a signing bonus (maybe a self-driving Ferrari one day). $USD1000 is clearly a lot more money to me than it is to you.
But if you'd like to take your own side of the bet and choose your own charity, please feel free.
Moreover, I'd like to know what the terms of that bet that you'd be making with yourself. Is it for a generally available car that can drive reasonably anywhere? In San Fransisco but also in small towns without super-accurate cm-scale mapping data (which will never be both everywhere and up-to-date)? Do we consider it a success if self-driving cars blindly drive into construction sites that haven't been mapped? Or crash into newly erected barricades? Because I don't, and that's exactly where we'll be in 15 years.
Autonomous vehicles are quickly approaching what I will acknowledge is probably an 80% solution. In nice weather, when their mapping is perfect in a perfectly-mapped area, and they have a good GPS signal, autonomous cars will work well (and currently are working well in testing).
That's not the standard that's expected. No one lives in a city without road work or construction going on. No one lives in a city where temporary or make-shift signs aren't being erected, or where there are never detours, or where there isn't ad-hoc communication going on between pedestrians and drivers, or where weather doesn't block LIDAR, or, ...whatever.
We will be nowhere near level 4 autonomous vehicles in 10 years time. And not in 15 years, either.
No one in this field is confident of that anymore. Not even Google is making the same bold claims that they were 3 years ago. Their own researchers are publicly hedging now (http://gizmodo.com/how-to-teach-an-autonomous-car-to-drive-1...) and backing away from their most ambitious claims.
The only other group that I'm aware of that's still claiming that we're anywhere near having generally-useful self-driving cars are the established car makers, none of whom have traditionally been serious AI and computer vision research contributors.
"The usual touchstone, whether that which someone asserts is merely his persuasion -- or at least his subjective conviction, that is, his firm belief -- is betting. It often happens that someone propounds his views with such positive and uncompromising assurance that he seems to have entirely set aside all thought of possible error. A bet disconcerts him. Sometimes it turns out that he has a conviction which can be estimated at a value of one ducat, but not of ten. For he is very willing to venture one ducat, but when it is a question of ten he becomes aware, as he had not previously been, that it may very well be that he is in error. If, in a given case, we represent ourselves as staking the happiness of our whole life, the triumphant tone of our judgment is greatly abated; we become extremely diffident, and discover for the first time that our belief does not reach so far. Thus pragmatic belief always exists in some specific degree, which, according to differences in the interests at stake, may be large or may be small." - Immanuel Kant
This time, the ongoing AI/ML renaissance is funded by private industry, and the value they are extracting from it far outstrips the costs of keeping their in-house R&D labs operating. Even if there's a contraction in the market, I can't envision any possible world where Google/Facebook/etc stop working on AI, and they have the money to keep it up as long as they want.