What you posted looks pretty cool, I don't know enough about it to understand what I should be prioritizing focus on, but we can chalk that up to ignorance. The benefit that driver-view footage has is that it is a viewpoint all of us are familiar with. If you ask me to watch dashcam footage to assess some kind of traffic thing, there's a general expectation of where I keep my eyes and what I notice.
This normal-human-view mode is probably going to be necessary in AV cases in which we determine whether the car's AI did the right thing. Presumably, as AV becomes mainstream and extremely safe, these accidents will involve edge cases and outliers which are poorly interpreted by sensors/non-human-vision. Seeing the scene as a human driver does might be a necessary starting place?
But the Uber case in AZ, IMO, proves your point. The Tempe police quickly made a judgement call based on what seems to be inadequate video. Everyone who can now view the video will also be inclined to think how impossible it would be to avoid hitting the victim, even if the actual scene in-person has much more light. And of course, we don't want to judge AV solely on whether it performs as well as normal humans.
You don't think performing as well as normal humans should be sufficient to allow them on the road?
Or are you saying they should be allowed even if their performance is worse than human? (...as long as some other criterion is met?)
Even if the camera was brighter uber isn't at fault anyway....
However, as a society and civilization, and even more so, as engineers and scientists, we are going to expect that the autonomous car matches or exceeds human-level performance in critical situations like this.
Therefore the time spent on investigating, understanding, and discussing the root causes of the accident is worth understanding. Accidents like these generally do not happen due to a single factor. It is necessary to understand all the necessary factors if we want to make autonomous driving systems more reliable.
At the very least we need to understand whether the pedestrian appeared in the other sensors that a human could have identified by looking at the sensor data, and if yes, whether the autonomous system matched or exceeded human-level performance by detecting the pedestrian, and if the pedestrian was indeed detected, why the autonomous driving system failed to respond to the situation.
However, most auto liability insurance covers whoever you permit to drive the vehicle, so the owners policy does typically cover the fender bender on the way to the grocery store.
I would be very interested to learn whether or not the car's autonomous system identified a bicycle at any point prior to the collision.
car didn't see it at all even in those last moments.
But this was a pedestrian, not a cyclist.
Personally, while riding at night, I look like a Christmas tree. $10 on EBay goes far these days in the reflective tape and bike light department:
What is surprising is that the bike didn't seem to have Tire reflectors like these:
https://www.wired.com/2011/11/fiks-reflective-rim-strips-for...
They are mandatory in lots of countries, to the point that it's impossible to buy tires without them. All brands come with them.
Maybe the outcome will be that thermal infrared will be mandated on all sensor packs?
I just watch the road in front of me.
My idea is that the car has been behaving well for a long time and consequently the driver lowered is vigilance. Big mistake.
Unlike many others, sadly - even when they don't have any self-driving tech at all
Waymo cars are capable of sensing vehicles and pedestrians at least half a block away in every directions. I was reserving any judgement on wether this collision could have been prevented, but seeing the video tells me that 1) a human driver might have hit the victim regardless, and 2) I'm very surprised that the LIDAR sensor didn't cause the car to stop to a halt much, much earlier. This is exactly the kind of situation that I would expect self-driving cars to be better than human drivers.