I'm not sure what to say when the code I recently turned in (and passed) for the path planning project of term 3 in Udacity's Self-Driving Car Engineer works better at changing lanes than Tesla's system:
Then again, it does have a failure mode where occasionally, for some reason, it will direct the car to change lanes into the path of a much faster moving vehicle in the lane being changed to. Most of this is because it only runs the behavior planner every second or so in the simulation, and probably does get everything perfectly correct in the prediction part (I honestly am not sure where the problem lies, though).
The problem Tesla has is that their system only has ~ 40 meters visibility to back or front.
That means if you're on the Autobahn, at say 130km/h in the right lane, and a Porsche is coming from behind at 300km/h, the Tesla will not be able to see it, and consider the lane free.
It’s quite interesting, because obviously an entirely different class of issues becomes apparent when the speed between two lanes on a highway can differ by a factor of 4.
This is what you get when the speed limit actually is "unlimited".
https://github.com/andrew-ayers/udacity-sdc/blob/master/Term...
Then again, it does have a failure mode where occasionally, for some reason, it will direct the car to change lanes into the path of a much faster moving vehicle in the lane being changed to. Most of this is because it only runs the behavior planner every second or so in the simulation, and probably does get everything perfectly correct in the prediction part (I honestly am not sure where the problem lies, though).