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GM Exec Says Elon Musk's Self-Driving Car Claims Are 'Full of Crap' (smh.com.au)
An anonymous reader quotes the Sydney Morning Herald:
Billionaire entrepreneur Elon Musk's claims about the self-driving capabilities of his upcoming Tesla vehicles are "full of crap", General Motors' self-driving Tsar says... "To think you can see everything you need for a level five autonomous car [full self-driving] with cameras and radar, I don't know how you do that"... GM's own solution involves several radar and Lidar sensors, as well as cameras and multiple redundancy systems. Each system costs hundreds of thousands of dollars, and GM are some way away from getting the cost low enough to be commercially viable. "The level of technology and knowing what it takes to do the mission, to say you can be a full level five with just cameras and radars is not physically possible," Mr Miller said.
Also, as to answer the question of how humans do it with "two cameras": logic. We don't have "stitching errors" in how we build up a model of the world around us from visual data because our brain constantly processes everything around us through the prism of "does that make sense?" But whether something "makes sense" or not is an AI-hard problem.
Building up 3d models with photogrammetry is an inherently error-prone process because a computer doesn't know if something makes sense. The approach is "Oh hey, these patterns from the left and right camera matched up - there's an object there at X distance based on how far the patterns had to be shifted to align". But what if the patterns happen to be different things that just happened to match up in patterning? Or what if, due to lighting / texturing / obstruction / material issues, the same thing didn't look exactly the same from different angles? Uncovering these problems is, as mentioned, AI-hard. I doubt anyone is even trying at this point; there's enough to work on just to get things to follow road lines correctly and not go chasing old tire tracks or poorly erased construction lines.
Ranging systems like LIDAR help let you just simply ignore the issue by telling you flat out, "I sent out a beam in this precise direction and got a reflection in precisely this length of time." But LIDAR has a number of problems, as described above.
"If there was an antonym to 'Elon Musk', it would be 'Richard Branson'."
Microsoft demonstrates the transition from a startup, growth oriented company to a mature, profit oriented one.
Jobs, by the way, hardly counts as an inventor. Visionary, sure, but that's not the same thing at all.
Post may contain irony: discontinue use if experiencing mood swings, nausea or elevated blood pressure.
According to Google (who's a big LIDAR proponent), it's still $7,5k per unit. It still messes up your aerodynamics and looks dorky. It still can't see in adverse weather conditions, meaning you have to have developed an optical / radar based world-modeling system anyway. And you have to have image processing regardless to read signs, road lines, identify objects, see brake lights, and so forth.
There's real hope for further improvements in LIDAR and its variants in the future, however. We'll see where it goes.
Good lidar systems see much, much better than camera based systems in adverse weather. I work on FMCW lidar systems and I recall driving to work one day where the fog was so bad that I couldn't even find the road to my office. Once I got work, I turned on the lidar system I was working on and it imaged a building 100 meters away without issue. Road lines are trivial to identify in a lidar system since they have much different reflectivity than the road surface. Objects are also easier to identify because you aren't trying to pull three dimensional information out of two dimensional images. On an FMCW lidar system, you also get doppler information for free. You don't have to try and decide if an object is moving towards or away from you by comparing subsequent images. Every single point in the point cloud includes a meters/second doppler value.
I have to assume your familiarity is with those awful spinning Velodyne systems. They are utter garbage. No self driving car company that I've interacted with is even vaguely entertaining the idea of using them in a production car. They don't even really like using them in their mule cars but, until very recently, they were the only real option available.
The real problem with lidar is that people aren't good at consuming lidar data yet. Once they start to get some experience with it, I have zero doubt that lidar will be the primary sensor on the car. It's the only way you can really build a model of your surroundings with high accuracy, high refresh rate and high tolerance to ambient conditions. So, I actually agree with the GM guy here: Tesla is full of shit. They aren't going to make a level 5 autonomous car with cameras and radar.