Re: Not an IT problem
I'm with you up to a point but it's also management's call on what's a long dead system. The system you might want to get rid of might be the one that does the work that brings in the money that pays IT's wages.
40470 publicly visible posts • joined 16 Jun 2014
"they used to produce good quality printers. Adding a scanner on top really should have been easy for them"
They did that. My HP all-in-one works just fine. And keeps on working. Unfortunately for HP it means I'll never need to buy another. They don't like that so the later ones are cheaper to build and you will need to buy another. That seems to be the thinking. It back-fired. I wanted to buy a colour one. Having seen more recent HP printers I didn't buy my colour one from them. Maybe it does work overall because there do seem to be places where nobody ever got fired for buying from HP.
"which IIRC contains 23 separate needles for the strains"
It's a long time ago but IIRC the multiple needle thing was the test which was supposed to come up and leave a scab if it was positive. The scab could leave a permanent scar. You used to see people with one or even two scars the size of an old halfpenny on their upper arm. My test? Not the slightest reaction so I got the jab with a singe needle.
There's no excuse for this inability to handle classification errors: had it been able to see "something" was moving on a fixed course, things probably wouldn't have come to this.
There may be no excuse in terms of letting the thing loose on the road but there's a likely reason. If there's more than one unclassified object in view then from one sample to the next it can't link up these to "know" that one was on a fixed course because it can't keep close enough track on them because it can only do things sequentially.
"most objects will be static"
Unless the vehicle's stationary they're all dynamic because they're being observed from the viewpoint of the vehicle Parallax will ensure that even objects static relative to each other will have the angles between them change from the PoV of the vehicle..
"Unfortunately, deleting the movement history every 1/10th of a second isn't going to help get it right!"
The movement history is simply the tracking of what's recognised as the same object in 1/10th of a second intervals. If you can't reconcile some of the objects with the objects in the next sample you either have to discontinue your movement history or accept that there are N possible continuations based on the number of possible options to identify the unclassified objects with their candidates in the previous sample. Unless you can successfully identify objects from one sampling of a scene to the next you have a combinatorial explosion of possible trajectories to consider.
"Chucking movement history away when a thing appears to be something else."
This is the fundamental problem.
If tracking is only achieved by joining up intermittent sightings of what is recognised to be the same object there is no movement history to be chucked away of the object can't be recognised consistently. Any unclassified object in a given sampling might be any unclassified object in a previous sampling.
If we have objects at positions A and B and then a second later we have objects at positions C and D then we may have something that's moved from A to C and something else that's moved from B to D but we might equally well have something that's moved from A to D and something else that moved from B to C. If there's insufficient processing power to handle that - and there are probably a good deal many unclassified objects than just two (and all moving relative to the vehicle due to the vehicle's movement if nothing else) then the system cannot establish any trajectories.
Unless there's sufficient processing power to track objects continuously the system will fail and that's the problem with doing things in code: you're trying to use a few cores to do what the eye* and brain does with massive parallelism.
* Processing starts in the eye before the brain even gets involved.
I'm not sure precision is a big factor. I think our inherited mechanisms as humans are more to do with predicting trajectories, including our own, and whether they're likely to intersect at roughly the same time. Roughly because we'll apply a safety factor which obviates the need for precision.
It's not so much object position that matters, not even relative position, because its position to ourselves is constantly changing whilst we're in motion.
"Humans are far from perfect drivers. Just have a look at the US fatality figures - 40,000pa, and that excludes injuries."
That needs to be set against vehicle miles. I don't know how your figure compares to vehicle miles in the US but in the UK it's a huge number of miles per fatality. I doubt autonomous vehicles have got anywhere near it.
"My point was voice recognition isn't 'perfect' but for many people it would be no surprise anymore if a system sat there and could recognise 99% of what you said."
Sometimes I can't avoid TVs in public places sitting there with the sound turned off and subtitles of attempted automated transcription. That the transcription can be attempted is admirable but the results are pretty dire. You certainly couldn't rely on them if your life depended on it - which is the case for autonomous cars.
And until it can draw the distinction reliably or fail safe it shouldn't be on the road.
That should just be a basic requirement. I know "let's do a rough build and then let the users find the bugs" might be a fashionable development process right now but moving fast and breaking things isn't good enough when the things are human beings. There needs to be a constraint and not running down pedestrians is a good place to start.
"The processing capability can fit into a car. But you have to do the right processing."
The right processing applies to every object in the visual field. I agree movement must be tracked but there needs to be some sort of classification of the objects to evaluate the probability of static objects starting to move and of moving objects changing speed and/or direction.
That processing capability can certainly fit into a driver's head; the despised "wetware". Whether the required hardware can when it's only weakly parallelised is a different matter.
"Distracted includes looking at phone, sat nav, pretty lady on the pavement etc."
1. We're expected to keep the speedo under sufficient observation to adhere to arbitrary indications. If that's not a greater distraction than the sat nav I don't know what is.
2. The pretty lady might move from the pavement into the road and requires the same degree of observation as the ugly gent.
"the market's inherently unstable and can't really be satisfied"
Stuff the market. These are lives we're dealing with.
If it were a human driver we may be looking at sentencing them to imprisonment for dangerous driving. Perhaps the appropriate way to deal with this is to imprison the CEO or a board member instead.
"Unless it starts doing it a hundred times an hour and you end up late to that important meeting."
And there's the problem. Self-driving is competing with massively parallel processing and yet its proponents claim it can do it better. And in any case it's better to end up late for a meeting than just end up.
"There's my (currrently) 3 massive bugs in the system."
There's really one fundamental bug: the absence of the massive processing power of the brain. And not just the human brain. It's a common animal trait to judge trajectories, both of self and other objects. It helps predators hunt down prey and prey to avoid predators. There are millions of years of evolution behind the mechanism of the brain; "training" is just the commissioning process.
"a vehicle or bike would usually stay in its lane"
There are a couple of problems with that built-in assumption.
One is that the only possible objects are vehicles and bikes; it doesn't allow for walkers, animals or even mobile parts of the environment (think landslip or large wave, e.g. https://www.bbc.co.uk/news/av/uk-england-hampshire-50266218/isle-of-wight-waves-almost-drag-man-and-child-into-sea).
The other is that word "usually". I think most of us rate the probability as usually small but greater than zero and keep reassessing it on the basis of observation whilst the object is in view.
"So if we see a human on the side of the road we look for subtle clues in body language"
Not just humans. The same needs to be applied to other animals. In fact, if the animal is proceeding along the road it's as well to allow for an unexpected change of direction and avoid alarming it. Yes I do live where there are a number of horsey folk around - hazards on the road but useful of you grow veg.
"We don't have ranging devices"
But most of us have two ranging mechanisms.
Binocular vision enables the brain to triangulate objects. That only requires that the two images of an object are recognised as the same thing, it's not necessary to recognise what the object is.
A second mechanism, for which one eye suffices, depends on recognising what the object is, knowing its size and working out how far it is from the angular size it presents.
"Virtual desktops have been available in Windows 10, macOS and Linux for some time so Google is catching up with these established operating systems."
I don't know about macOS but, depending on the desktop manager used, Linux and the BSDs have had multiple desktops available for a long time. Windows 10 was a catch-up for Microsoft.
"A simple version would be to make large numbers of Google and Amazon searches for tea strainers and scented candles. I am sure with a bit more thought it could be made far more sophisticated. Hand warmers and electric toothbrushes anyone?"
I like the idea. Do we make carefully tuned searches for widely disparate pairs of terms or simply randomise them? Quicklime and carpets?
Maybe lots of searches for combinations of horse, battery and staple would result in that cartoon coming to the top of a Google search for any one of them. Intriguing possibilities there.