Velodyne Lidar Inc. baffled by Uber crash

https://www.bloomberg.com/news/articles/2018-03-23/sensor-supplier-to-self-driving-uber-defends-tech-after-fatality

by neom • 8 years ago

64 106 8 years ago

bloomberg.com

Piskvorrr4• 8 years ago

Aaand here comes the CYA storm, with everyone declaring they had absolutely nothing to do with the crash.

Declanomous• 8 years ago

I mean, it is pretty baffling that people are defending the self-driving car when it has LIDAR.

mateuszf• 8 years ago

Really? Isn't LIDAR just some input device, whose data is interpreted in software?

lima2• 8 years ago

It certainly shows why Google/Waymo are so cautious. They could have brought their product to market much sooner.

Move fast and break things...?

colordrops2• 8 years ago

To be fair it probably wasn't caused by a lidar failure.

lima2• 8 years ago

Even if the Lidar did fail, the software would need to handle it gracefully.

riffic• 8 years ago

https://usa.streetsblog.org/2016/04/04/associated-press-caut...

adamson• 8 years ago

This seems exceptional for Velodyne to come out with a statement like this directly from a spokesperson. I would expect a supplier to be more restrained before throwing a large (and growing) customer under the bus like this.

05• 8 years ago

Uber already tried getting their hands on a better LiDAR unit, we all know how it went. If they could switch to a better in-house sensor, they would have done so already, and Velodyne is the best of what’s commercially available now. What are they going to do, switch to an inferior model at a time their software can’t even avoid a collision using state of the art LiDAR?

Roritharr• 8 years ago

Well the question of "why didn't the lidar see the pedestrian?" was on everyones mind in the industry, so openly going out and declaring: "it surely must have seen it, the lidar's are fine" is an attempt at reassuring everyone who is now questioning if Lidars are not reliable enough.

This is not exactly throwing Uber under the Bus as they themselves have an interest in being able to tell that story later on: "Our analysis concluded that our algorithms didn't put enough weight on the data coming from the lidar, which worked as intended and should have been weighted higher in these specific circumstances, we will adjust our efforts accordingly and will Donate $largeSum to CarsAgainstHumanity to bribe everyone into forgetting how bad we fucked up."

gowld• 8 years ago

Why is it OK for the LIDAR company to make a blanket statement of innocence without proof, but not OK for Uber to do the same?

dmix3• 8 years ago

It's entirely possible that Velodyne worded it far more softly, as to not directly attack Uber - as this article somewhat comes off as them doing.

Who knows what other greater context the particular statements were in. After this past election I never trust these types of one-line quotes taken from a larger interview.

The headline could easily have been:

- Uber's Lidar manufacturer just as "baffled" why pedestrian not detected before crash

treis• 8 years ago

It's hard to overstate how bad of a failure this was on Uber's part. This is autonomous driving 101. Don't run over the human in the road.

ggg99902• 8 years ago

I don’t know how hard it is to not run over a human autonomously but I do know that it’s easy to refuse to let your cars on the road until they’re capable of it.

ggg99902• 8 years ago

Uber is poison and everyone knows it. Everyone in the ecosystem is trying to throw them under the bus because they deserve it. The world will be a better place if Uber (not ride”sharing”) is destroyed.

jlarocco• 8 years ago

I'm not sure Uber is a very large customer of Velodyne's. They're also suppliers for Google, Ford, and Caterpillar, as well as a bunch of others.

If they're sure it's not their fault it's a good idea to get that information out before people start questioning LIDAR technology. If Uber leaves they'll lose sales in the short term. If everybody else gets scared away then they're toast.

mortenjorck• 8 years ago

I've seen less technical friends on social media responding to the dashcam video saying "of course it hit her; it's way too dark to see!" without understanding that LIDAR doesn't use available light. People may not understand exactly what Velodyne does, but so long as the company supplies "the eyes for self-driving cars" they have a clear risk of the public thinking this was a sensor failure.

chrismcb3• 8 years ago

They should also understand that they video is not an accurate representation of what a human eye can see... Let alone some high tech sensors.

Piskvorrr4• 8 years ago

More and more, I am convinced that the video released comes from scapegoat cameras, as someone named them here on HN: "post crappiest video available, have the public believe there's nothing you could have done." It works (tm)

SteveCoast• 8 years ago

It reminds me of when an airliner crashes (a rare thing now).

The airline, the manufacturer, the engine manufacturer, the part(s) suppliers, the pilots... will all point at each other. Usually the pilots lose because they don't have any money whether they were at fault or not.

You have to wonder why everyone isn't pointing at the safety driver in this case.

Here's an example of everyone blaming everyone else, and the manufacturer lost despite it not actually being their fault:

https://en.wikipedia.org/wiki/American_Airlines_Flight_191

eumenides1• 8 years ago

Uber being poison and it's easy to poop on Uber aside.

I think it makes sense to for Velodyne to get a head of the message before any client throw Velodyne under the bus. If Velodyne takes the hit, all their suppliers have leverage over them. Staying ahead keeps the clients confident in Velodyne products.

Also scale-wise, the market is tiny at this point. Nobody cares the sales from quarter to quarter because whenever self-driving cars hit mainstream, all previous numbers will be scribbles in the margin.

Velodyne has a finger in practically every major self driving car pie slice. It's pretty much heads you lose, tails I win for them (Assumption:nobody can bring a better laser to market).

danvoell• 8 years ago

“Certainly, our Lidar is capable of clearly imaging Elaine and her bicycle in this situation. However, our Lidar doesn’t make the decision to put on the brakes or get out of her way.” - Would be very interesting, in the name of transparency, to see the log. Whatever malfunctioned has to be there. Hopefully some sort of mechanism to prevent future crashes arises from this. Instead of just a few lawsuits, payoffs and coverups

candiodari3• 8 years ago

There are 2 problems with this way of reasoning is what you see in the aviation industry.

One, you're comparing this incident with an idealized human. Everybody thinks pilots and drivers are magical beings that don't make mistakes. And then 90 people die because one engine catches fire, pilot turns off the other engine and then banks the aircraft for make a quick emergency landing, obviously the plane loses lift immediately, drilled itself into a bridge, taking a taxi with it into the river below. No survivors, almost a hundred dead [1]. And I get it, the pilot needed to rapidly make a series of decisions under ridiculous levels of stress, that's the real cause. But when things go wrong close to the ground at 150km/h in an object that weighs 50 tons, they go wrong quickly, so you need to respond quickly. Needless to say, nothing prevents reoccurence. Quite simply, a plane will crash if you do this. There's nothing that can technically be done to prevent it. As for cars, over 10.000 people die every year because humans can't be bothered to wait until they sober up to drive [2]. Those are the human pilots that we should measure against.

Frankly, I don't understand how humans are allowed to drive cars or fly planes at all. We pass signals in our brain, they can cross from neuron to neuron in about 10ms. That means that in a second, a signal can affect, at most, a ball with radius 2cm in our brain. To spread out over the brain requires 7-8 seconds minimum in theory and in practice minutes is the more common scenario. That means, it's your spinal column that's driving the car/flying the plane and it gets updates "from upstairs" that are 2-5s old by the time they reach the control loops. Our brain is very good at predicting events so it doesn't look like that's the case, but it is.

Compare self-driving or other autopilots against realistic humans, who make these sorts of mistakes. An average autopilot needs to do better than a decent human driver. It should not need to outperform a magical how-we-imagine-ourselves perfect human driver.

That said, I do agree that we need some basic rules. Tesla's car did NOT stop after crashing into a truck after a lidar mistake (and a serious mistake by the truck driver that it was attempting to compensate for I might add), but not stopping, that's utterly unforgivable. Same here, obviously the car was obviously either driving with the lidar turned off or ignoring it's output. That's like a human driving with their eyes closed.

But certification must be functional. It can't be on the quality of individual components. It can't be on code review. It must be functional. We should have test tracks where autopilots get confronted with dozens of situations, preferably combining 5-6 individual problems at the same time. And then it needs to navigate it safely, under constant decision pressure. And then it needs to end with 5 cars being sacrificed to test their reactions when something heavy drops on them, when they drop off a cliff, when they get mechanically blocked, and when catastrophic mechanical failure occurs ... (so they don't put the pedal to the metal causing 10x the damage to others when they do have an accident).

But it needs to be a functional, practical test. Not the madness we currently have for aviation.

[1] https://www.youtube.com/watch?v=jKNREZ_u8E8&t=31s

[2] https://www.cdc.gov/motorvehiclesafety/impaired_driving/impa...

_dps2• 8 years ago

We pass signals in our brain, they can cross from neuron to neuron in about 10ms

Could you clarify this point for a non-biologist? I understand the neuron-to-neuron transmission is not going to happen at the full electrical conductivity rate (something like 100 m/s) but this seems so much slower as to be hard to understand as a lay person.

oh_sigh• 8 years ago

Someone in a previous thread mentioned that Uber had disabled LiDAR input because they were testing visual-light-only navigation. Was that just speculation/rumor?

Qworg2• 8 years ago

That would be so incredibly risky as to be insane, especially with non-technical staff in the monitoring seat.

I've not heard anything of it before you brought it up.

tjoff• 8 years ago

You don't have to disable it to test that, just run two systems in parallel and detect large deviations.

I refuse to believe that they would just disable it on public roads to see if it could manage.

gmueckl• 8 years ago

I hate to say it, but never underestimated the human potential for stupidity. To make matters worse, this is amplified in organizations. But in this specific case, this is all speculation until the data gets analyzed.

tetrep• 8 years ago

Someone in a previous thread mentioned that Uber had disabled LiDAR input because they were testing visual-light-only navigation.

That smells like BS. I can't imagine any serious players in the self-driving field that can't replay all their sensor inputs into models offline to see how things behave. If they wanted to test without LiDAR, they would run this simulations without LiDAR input. No reason to disable it when there's actual consequences.

That being said, I suppose it's possible that Uber have done what I already said, so much so that they were confident it would work and were willing to deploy it. But it still smells funny to me because I would sincerely hope the LiDAR (and other non-visible light sensor input) would be used as a failsafe.

My very limited understanding of autonomous car implementations is that you mix in all your input together to determine your surrounding environment (and all your "what do I do" logic deals with information derived from this input aggregation), so in order to safely test a new model with less input in your car, you'd need at least 2 models (one with all input, one with reduced) running at the same time.

It still seems like it'd be viable to me, and something you'd certainly want to do to avoid situations exactly like this. If you've got 2 models running, it seems like it'd be pretty straightforward to have the "all input" model assume control if it's trying to avoid an immediate collision, basically having it perform a similar role to that of a human behind the wheel during "disengagements".

TillE2• 8 years ago

That rumor originated from Robert Scoble. I've never taken him very seriously, though he is the type of person who probably does have contacts within Uber.

A software bug is still the most plausible explanation, given the evidence we have.

whoisjuan• 8 years ago

Of course the Lidar wasn't at fault. That's like blaming your laptop for the bugs of your own shitty code.

rconti• 8 years ago

Well, it COULD be at fault, if the sampling rate was too low to see a human walking across the road, or if it couldn't see the materials of the bike or human, etc etc. But we all know none of these things are true.

nomel• 8 years ago

No, that still wouldn’t be the Lidars fault. That would be a fault in safely setting the specification for the Lidar sample rate, and not catching the design flaw in testing.

cmpolis• 8 years ago

Hardware is not faultless.

The analogy doesn't stand up - there's a non-trivial chance that a memory module or your hard drive in your laptop will fail over the lifetime of the device.

Furthermore, a LIDAR unit is complex and has firmware and lower-level software embedded that may be at fault.

kuber_harbinger• 8 years ago

Yes, I've even seen this first hand where it was, in fact, the laptop as the issue source. Not that I'm taking Uber's side at all, just saying it is a possibility and we should wait for official evidence of the fault before jumping to conclusions.

tzs2• 8 years ago

If the software is well written, any of those types of failures should raise an alarm to alert the safety driver to take over, and then shut down the self-driving system.

chrismcb3• 8 years ago

It isn't anything like blaming your laptop. Lidar is a crucial sensor that allows the car to "see." If the lidar couldn't "see" the person, it doesn't matter how good your software is.

saurabp• 8 years ago

So if the LIDAR did not fail, it was probably the neural network that takes in LIDAR data and makes the decision to brake. Would love to see NTSB releasing the data for us to analyze.

jefft2552• 8 years ago

Just to be clear, neural networks typically aren't used to work with lidar in self driving cars. NN for point clouds are still at the research stage.

stevew20• 8 years ago

I was really hoping I wouldn't need to be the first person to point this out! Thanks Jeff

adrianmonk• 8 years ago

Does this mean this is just a research project that Uber doesn't actually use in their cars yet?

From https://eng.uber.com/sbnet/

"By applying convolutional neural networks (CNNs) and other deep learning techniques, researchers at Uber ATG Toronto are committed to developing technologies that power safer and more reliable transportation solutions."

"CNNs are widely used for analyzing visual imagery and data from LiDAR sensors. In autonomous driving, CNNs allow self-driving vehicles to see other cars and pedestrians"

blensor6• 8 years ago

I don't know how the system is integrated into the self driving logic as a whole. But a few years ago when we were working on a self driving train, LIDAR was used as a system that reports back a list of obstacles (position, size, maybe a simple shape descriptor) or as an obstacle map that is laid out in a grid and shows which cells are occupied and how high the thi g occupying the cell is.

If your system that processes the pointcloud and creates this data does not detect faulty (or missing) data from the sensor the higher level logic will happily hum along believing that nothing is amiss.

And some LIDARs even have the option to do the processing on the device itself (i.e. IBEO). In which case you can theoretically work with only a list of obstacles reported back by the sensor.

rtfs• 8 years ago

this is quiet interesting. two days ago the main stream media here in germany said that the accident would have happened anyways, regardless of the self-driving technology built into the vehicle.

Looking at the video, the quality of the current self-driving technology is really questionable, especially if i recall also the other non-fatal road traffic offences publicized so far.

cjbprime• 8 years ago

That claim by the media sounds obviously untrue.

And alongside being untrue, it ignores the differing severity of collisions. Even if the car had to use its normal video camera instead of Lidar for some reason, the second or two of applying the brakes that would provide can easily -- and will likely -- turn a fatal collision into a non-fatal collision.

9080872• 8 years ago

Velodyne clearly have no clue what they're talking about. They should consult with the "futurologists" on reddit who only needed 5 seconds and a video to conclude that "it was too dark out".

nugi• 8 years ago

Forgot your (/s) tag buddy.

9080872• 8 years ago

Was kind of hoping it was obvious enough that it didn't need one.

peterwwillis3• 8 years ago

I haven't been following this closely, but how was the car able to go over the speed limit? If a speed governor was turned off, or was able to be overriden, isn't it possible that multiple systems in the car were turned off, such as systems that regulate gas and brake?

teraflop• 8 years ago

From what I remember reading, the car was going 40mph in a 45mph zone.

EDIT: https://www.nytimes.com/interactive/2018/03/20/us/self-drivi...

peterwwillis3• 8 years ago

Oh, thanks for that correction, I thought I read it had been going 51 in a 45.

edit: Errr..... http://money.cnn.com/2018/03/20/news/companies/self-driving-...

"the car was going approximately 40 mph in a 35 mph zone, according to Tempe Police Detective Lily Duran."

So... was it 40 in a 45, or 40 in a 35? It would seem this is critical information.

tobltobs• 8 years ago

Depending on the sources the speed limit in the area was 35 mph.

https://www.azcentral.com/story/news/local/tempe-breaking/20...

jessaustin2• 8 years ago

Please, let us cling to the myth that urban speed limits aren't way too high!

notananthem• 8 years ago

Can I ask a dumb non-engineer question? Backup cameras in areas with basically any road debris/weather get covered with dirt. I'm in the Seattle area now, and I often lick my thumb and wipe off the camera, because its a vision system I rely on so I don't kill people.

Could lidar/cameras/etc on the vehicle be obscured by road debris or worse, things being bumped/moved, smudged, or even foul play?

nikanj• 8 years ago

I think any dirt on a sensor would register as additional objects in the scenery, not missing objects. Humans are great at autocorrecting, but from a straight-up sensor data point of view, no light on these pixels=something is between sensor and light source.

lisper3• 8 years ago

Yes, that's possible. But in such a situation the data from the LIDAR looks very different than it does under normal conditions. You can easily tell when a backup camera is covered with dirt by looking at the image. Uber's self-driving software should have been able to detect a LIDAR failure in much the same way.

hnaccy• 8 years ago

You would have Lidar wipers[1] and the software should hopefully be able to detect obscured or failing sensor and alert driver or stop.

[1] https://i.imgur.com/2QTHjij.gifv

aprao• 8 years ago

That's an informative but unsatisfying gif. What if the residue on the top leaks down?

skybrian2• 8 years ago

It's easy to check for and would show up in recordings. I would be very surprised if they don't already check for this.

colordrops2• 8 years ago

There should be an alert of some sort and the car refusing to drive if the LIDAR is obstructed.

haZard_OS• 8 years ago

From my perspective, the first question should be, "Given the same circumstances, would a human driver have performed better?".

After viewing the video of the incident, I strongly believe that human driver would NOT have done better.

Therefore, I believe that any attempt to blame or spread mistrust in these technologies because of this incident is (at best) misguided and (at worst) alarmist.

iancarroll• 8 years ago

Regardless of whether or not a human driver could have done it, the vehicle had a pretty critical sensor onboard that should have been able to see the pedestrian. It’s important to figure out how this collision managed to happen.

hcknwscommenter2• 8 years ago

You are being manipulated. Your strong belief is based on a hugely misleading video.

https://arstechnica.com/cars/2018/03/police-chief-said-uber-...

InclinedPlane• 8 years ago

Nighttime dashcam videos typically do a very poor job of representing what a scene looks like to the human eyes. Here is a phone camera video of the same stretch of road as the accident took place on, at night: https://youtu.be/1XOVxSCG8u0?t=26

From this you can see how good the visibility is. We know that the visibility on this stretch of road was pretty good for nighttime driving. We know that the pedestrian that got hit had crossed an entire (empty) lane of traffic before entering the Uber vehicle's lane. I would say that any competent driver who was paying attention and who was driving a car with working headlights (or perhaps even without) would have spotted the pedestrian well in advance and been able to avoid the collision fairly easily.

The fact that the Uber vehicle did not do so despite having an abundance of opportunity and despite having not only visible light data but also lidar and radar is almost certainly a massive failure on its part. Almost certainly this is due to a failure to integrate sensor data properly or to fail to categorize a pedestrian correctly.

I have no faith that the local PD will do a good job here, but I do have faith that the NTSB will be exquisitely thorough, and I would bet hard-earned dollars that they are going to tear Uber's self-driving technology up one side and down the other.

chrismcb3• 8 years ago

The entire point if self driving cars is they are supposed to be better than humans. So the first question should NOT be if a human could do it better. Of course in this situation a human probably could have done better. The real question here is why we they allowed to test an unproven car on the unsuspecting population?

aecs99• 8 years ago

I lean towards what Velodyne is saying in this situation. I have been working with LiDAR systems for over 4 years of which the last 1.5 years have been towards building autonomous driving vehicles. When I saw the videos, I was truly baffled by how a LiDAR can miss that. I worked with different types of LiDARs (from different manufacturers) and there is a very high chance that the LiDAR point cloud contains all the information corresponding to the person and the bicycle to make a decision.

What we need to keep in mind is that sensing an object is different from deciding whether or not to take an action (e.g., hitting brakes, raising alarms, swerving, etc.).

Most LiDAR/RADAR/Camera manufacturers only provide input data. It's like saying "hey, I see this". It's up to the perception software to decide whether or not to make a decision.

In most cars, relatively simpler decisions are made by the car's perception software (e.g., adaptive cruise control, lane change warning, automatic braking, etc.).

Self-driving companies override such systems, and rewire the car such that it is their perception software that makes the decision. So the onus is completely on the self-driving company's software. In this case, it is the perception software developed by Uber to be critiqued - not Velodyne, not Volvo, not the camera manufacturer.

It looks like the engineers at Velodyne feel confident that they should (and would have) sensed the person, and hence their statement. I wouldn't doubt them much as they have been in the LiDAR game since DARPA days when self driving was considered experimental.

From a different angle, Velodyne may not have much to loose by throwing Uber under the bus - especially when compared to how much their reputation is at stake. This is because Velodyne has several big customers (e.g., Waymo, and almost every other self-driving, mapping company that is serious about getting big).

NTSB should and will get access to the point clouds. Uber has a choice of releasing the point clouds to the public - but I highly doubt they will.

blensor6• 8 years ago

I don't understand why everyone is focusing so heavily on LIDAR being at fault or not at fault. The car does have a RADAR as well, which would not help detecting the pedestrian but most certainly the bike she was moving along. I don't know the field of view of the radar but that should have caused an emergency brake as well, shouldn't it?

mturmon2• 8 years ago

From a recent publication in an IEEE conference related to intelligent vehicles:

"Radar is robust against bad weather, rain and fog; it can measure speed and distance of an object, but it does not provide enough data points to detect obstacle boundaries, and experimental results show that radar is not reliable to detect small obstacles like pedestrians."

This would be because the wavelength of lidar is in the micron range while that of vehicle-detection radar is in the mm-cm range. You won't be able to reliably get radar reflections off of mm/cm-scale objects or object elements, or accurately (<1cm) localize object boundaries. Good navigation would require tighter localization.

Radars are really good, though, for detection of objects, including identifying moving objects, close up -- canonical examples being walls and other vehicles. Radar sensors are rather cheap (having been in mass production for a long time) so it's common to have one on every bumper or corner.

TillE2• 8 years ago

an emergency break

I think half the people commenting on this incident have misspelled "brake". It's odd, because that's not something I've observed as a common error before.

codedokode• 8 years ago

If you worked with LIDARs, maybe you know how much noise do they give in the output? Could not it be that Uber software filtered pedestrian image out as a noise, for example because there was no matching object on a camera or because reflections from the bike looked like a random noise?

mturmon2• 8 years ago

Both effects you mention (sensor fusion problem between camera/lidar; spotty lidar reflections from bike) are possible.

These problems probably should not have prevented detecting this obstacle, though. But, a lot depends on factors like the range of the pedestrian/bike, the particular Velodyne unit used, and the mode it was used in.

One key thing is that lidar reflections off the bike would have been spotty, but lidar off the pedestrian's body should have been pretty good. That's a perhaps 50-cm wide solid object, which is pretty large by these standards. But the number of lidar "footprints" on the target depends on range.

You'd have to estimate the range of the target (15m?) and compute the angle subtended by the target (0.5m/15m ~= 0.03 radian ~= 2 degrees), and then compare this to the angular resolution of the Velodyne unit to get a number of footprints-on-target.

Perhaps a half dozen, across a couple of left-to-right scan lines. Again, depending on the scan pattern of the particular Velodyne unit in use. The unit should make more than one pass in the time it took to intersect the pedestrian.

This should be enough to detect something, if the world-modeling and decision-making software was operating correctly, hence the puzzlement.

laythea• 8 years ago

It is not possible for the algorithm looking at the LIDAR input data to have the same level of discrimination as humans, so this would be a possibly in my opinion.

blensor6• 8 years ago

They do have noise, but we are talking about milimeter to centimeter scale (accuracy is < 2cm). So a grown up person is roughly 2 orders of magnitude bigger than the accuracy of the scanner.

To give an example how big (or small) this noise would have been in this situation I did a very simple virtual scan of a person with a bicycle at a distance of 15 meters [1]

It was scanned with a virtual scanner inside our sensor simulation software, so this is not the real data and should be taken with a grain of salt.

[1] http://www.blensor.org/blog_entry_20180323.html

omgwtfbyobbq• 8 years ago

Would a bunch of plastic bags filled with stuff (plastic bottles, clothes, etc..) tied to a bike be something the LiDAR would see as part of the roadway rather than a set of distinct objects?

FabHK• 8 years ago

After the Tesla fatal accident, there was some discussion about the difficulty of stationary obstacles. Apparently, there are so many false positives, that they're quite readily discarded (otherwise the car would stop all the time).

See discussion here, "Why Tesla's autopilot can't see a stopped firetruck": https://news.ycombinator.com/item?id=16239010

As the victim was traveling perpendicular to the movement of the vehicle, I wonder whether that had anything to do with it. If so, quite a severe limitation.

candiodari3• 8 years ago

If you look at how lidar's work this does indeed make no sense. Lidars will see vertical poles that stick up high, like pedestrians. That's exactly what they're good at. For a lidar with even bad resolution to have missed this pedestrian ... it's technically not impossible, but it'd be one-in-a-trillion streak of extremely bad luck. It seems much, much more likely that the car was somehow ignoring the output of the lidar.

Lidar's see everything in a specific plane that's originated at their sensor. This situation is exactly what lidars are made for ...

Remember the Tesla accident ? A lidar was scanning planes in front of the Tesla and there was a large truck in front of it. A truck hangs low at the front and at the back, and the tesla autopilot saw both of them. Presumably because it was using lidar it decided that the front of the truck was a car, and that the rear of the truck was a car, and then when the truck changed direction it compensated by doing a high speed maneuver directing the car beteen the front and the read wheels of the truck. Needless to say, results were less than optimal (and then came the unforgivable: after the crash the autopilot was still in control, but it did NOT stop until it was mechanically blocked from going on). That's the sort of mistake you'd expect a lidar to make : it misses objects that are very close to the ground, or "far" off the ground. It sees things starting at 50cm high until 1m30 or so (also depends on the distance to the sensor. The closer the sensor, the narrower the range), no more. That's the weakness of lidars.

That unfortunately means what they do miss is ... well, let's put it this way : you can't mount it low in the car, because at that height it'll think large pebbles are telephone poles (plus mud will splatter up and block the sensor). So you don't do that. You can also mount it high but that means those detection planes don't get very close to the ground. And that means, what it'll miss is anything that's close to the ground. Dogs. Children. Parking poles. Stairs (or any kind of abyss). That's where you'd expect mistakes.

An adult crossing the street ... there's no way.

Velodyne Lidar Inc. baffled by Uber crash

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