I was using Rev E because it's the data sheet I had handy. Mostly I was trying to point out that LIDAR is not some magic thing that always sees everything and there's limitations.

  Frame	Distance	Angular Size of Target	Pixel Size 
  0.00	400.00	0.29	1.10
  1.00	396.09	0.29	1.11
  2.00	388.27	0.30	1.14
  3.00	376.53	0.30	1.17
  4.00	360.89	0.32	1.22
  5.00	341.33	0.34	1.29
  6.00	317.87	0.36	1.39
  7.00	290.49	0.39	1.52
  8.00	259.20	0.44	1.70
  9.00	224.00	0.51	1.97
  10.00	184.89	0.62	2.38
  11.00	141.87	0.81	3.11
  12.00	94.93	1.21	4.64
  13.00	44.09	2.60	10.00

There's with your .26 angular resolution @ 15hz. (I just have a spreadsheet that spits all these out for me.)

These are NOT big targets, they could easily have been mistaken for noise and filtered out. All of the LIDAR data I've ever seen has been fairly noisy and did require filtering to get usable information from it. And given the number of frames they get maybe their filtering was just too aggressive.

Yes, I agree with you that we can't assume that the car could have noticed the woman from 120 meters from LIDAR data alone. Maybe with some kind of sensor fusion with IR-cameras.

But, as it got closer and what the computer though was noise was on about the same place a sane obstacle finder should have given a posetive match. Maybe at 30 - 40 m worst case?

At 142 feet the woman probably had (assuming she was 5.5'):

asind(5.5/142) = 2.21* => 2.21/0.4 = 5.5

So between 5 and 6 "scanlines" going from left to right over her.

Assuming she was 2' wide that's 0.8 degrees which would be 2 to 3 pixels in breadth according to your spread sheet.

That's between 10 and 18 pixels (voxels?) that stand out clearly from the flat road around it, exluding the bike.

If you wan't to get an idea of how LIDAR data looks Velodyne has free samples and a viewer for less resolution models.

http://velodynelidar.com/downloads.html

It pretty hard to identify obstacles far off, but you will still see there is something there. It's especially easy to identify obstacles that are vertical.

As she got closer, she would eventually show up clearly on the LIDAR data. But since the car never slowed down or went left, it didn't notice her at all even at point blanc (or did see her but failed to do anything about it).

A buddy of mine has a lower end LIDAR on a robot, working with them on SLAM on it, trying to get a similar hardware set up locally over the summer. (I have weird hobbies)

Yeah, I'm willing to accept SOMETHING bad happened here, as I said I really just wanna dissuade people from the notion that LIDARs will see all obstacles all of the time. Not going to say the car acted perfectly and it was sensor failure, but definitely willing to say that the LIDAR probably COULD see her but not as well as people would assume.

Really, I think this was a case of the car over driving their effective sensor range, same as what happens when you're on a dark road and a deer runs into the middle of the road, you simply can't react fast enough by the time you realize the danger is there. Computers are fast but they aren't perfect.

What I'd be particularly interested in was if the computer saw her and if it did the calculation - I can't stop safely in this distance, and decided to just hit the obstacle because it was "safer". At that point we start getting into ethics and this problem gets a lot murkier.

It's not safe to hit an obstacle at full speed. It should slow down to lower the damages to the obstacle, the car and the passengers.