How is this relevant to self driving cars in 2016 and the following decades?
Even as a human, I get confused while driving on this stretch. The old lane markings aren't quite faded out enough to easily tell them apart. As I'm driving, I see every other car slowing down and "dead reckoning," too.
How will the run-of-the-mill self-driving car's lane following handle this corner case? If it's a Canny edge detector (like most self-driving cars), it's definitely going to fail and find false positives.
The algorithms for lane following are quite a bit more sophisticated than that though. Here's a paper from 2008, and there are other approaches as well.
http://www.vision.caltech.edu/malaa/publications/aly08realti...
Take a look at Figure 12 for an exemplary look at its failure cases -- cases that are much less forgiving than the aforementioned Palo Alto stretch 101 lane markings.
(But in this case, I'll add that HOG doesn't solve the problem of overlapping old/new road markings)
What if I drive 5x better and safer than the "average driver"? Doesn't that mean that these cars would now put me in more danger than I would normally be in with my own manual car?
Self-driving cars should be 10x better than the best (as in safest by number of incidents, say, per decade) drivers on Earth. Then I could begin trusting them ... if only there wasn't that pesky security issue, too, with self-driving cars getting hacked and then driving you off the highway at 70mph and killing you.
We see Teslas getting remotely hacked. If that happens with Tesla, a Silicon Valley car company with a lot of hired top tech talent, how can we ever trust a company like GM or Volkswagen to build safe self-driving cars?
Then don't use the system?
You are giving thresholds - 50% to 2x better, 10x better. Before what? Before we ban manual driving? "10x better than the best driver" might make sense. Before we allow it on the road? Why not "better than the worst drivers we allow on the road"?
The most relevant point for Musk is probably "before the marketing works out". The market of people who consider themselves "substantially below average" drivers is much smaller than the market of people who consider themselves "not all that much better than average".
Because you are unlikely always that.
Are you tired? Do you have a cold? Are you hungry? Are you playing with the radio? Are you having a conversation with a passenger?
The huge advantage that self-driving cars will have is integrated systemic control from multiple sensor sources and multiple transducer outputs--and they will never get distracted.
Human drivers have mostly 1 input: vision. Human drivers have mostly two outputs: hand and foot.
The lag in that system from input to output is >100ms even if you are perfect (I will grant you an exception if your name is Michael Schumacher).
Automated systems will have far more inputs. Multiple vision sources. Multiple radars. Temperature readings. RPM readings. etc.
Automated systems have far more outputs. Steering is the same. Brakes on individual tires is the big starter. With electric, individual suspension becomes feasible. Transmissions change form and become electrically controlled.
And the lag in the system is probably <10ms. That's huge. That's the difference in reacting in roughly 3 meters (2.7 meters) vs 1/3 of a meter at 100kph (9 feet vs 1 foot roughly for 60mph).
Finally, automated systems will take subtle preventative actions all the time. They will "see" the child on bicycle on the sidewalk (the idiot detector as Google called it) and "know" that they need to find him again when they attempt to turn right or slow down significantly. They will see the dude on a skateboard and know that they need to give him an extra couple feet if they can in order to deal with him falling. I know very few drivers that are that diligent.
Why wouldn't you want to make them better?
How do you know that you're actually 5x better than the average driver and not just deluding yourself?
I don't see why you give wetware more leeway than hardware.
My point is that basic lane following can be done quite trivially, but it's nowhere near something one should entrust with the safety of human beings. Your question implies that you think all modern systems being deployed involve some really sophisticated AI. You don't know that.
Nope. LIDAR is used to determine geometry when a camera system can't tell WTF it's looking at.
Yes, that would be a communication problem of mine. It's something I'm working on ;-) But I would counter that LIDAR isn't going to fully make up for the problems of the camera based system with the result being a simple sounding statement like "if they're using LIDAR it's not good enough", or grossly oversimplified to "LIDAR sucks".
I will admit that LIDAR could conceivably enhance a really good vision system by offering better depth perception, but I don't believe that's why people are using it today.