I don't understand why the paradigm isn't about full volumetric prediction .. is it because people were too tired of solving all other issues (surely possible at the time of DARPA challenge, but Tesla had time and money since); or hardware limits (like scanning a larger area would impede signal quality or make processing too heavy ..)
I'm not sure what you mean, precisely. The grand goal IS complete autonomous function, but it's wise to approach this with caution. Legal and moral grey area abound, new technology brings new technophobia, definite "completeness" would require rigorous proof and we're JUST getting autonomous vehicles into the wild.
But the kicker is that if you actually care about the safety of the public, then you have to care about whether or not the public will adopt the new technology that makes them safer-- and to do that you have to introduce it slowly and respond to criticism.
Other companies are being even more cautious; Ford isn't putting autonomy on the road until 2021.
In the meanwhile Tesla can sell products as Level 2, and perhaps should do so until roads are as safe as commercial aircraft.
I know and I don't care. If they want public approval they can run demonstration, and probably 392584 other marketing techniques to generate social interest. Crappy solutions suck; period.
Which one seems more likely? "We could absolutely do that, but meh...just ship it already, who cares" or "doing that would require a major redesign, more sensors and more gigaflops"? (Okay, in the current hw/sw development paradigm, the first one doesn't sound as unlikely as it ought to)
For a company like Tesla, I dearly hope they don't think this way. If so it would mean everything they talked about was marketing drivel (the safety of the car frame etc). So far Musk felt honest with most of his design claims. Unlike lone SDV hackers on github for instance.
