You either detect a full-stopping-distance's worth of clear road through reliable (non visual) ranging with dense enough samples to preclude wheel-catching voids ... or you will continue to run into "objects" which slipped through your classifier.

I can accept reduction in this margin (e.g. in dense traffic flow) when it is first shown to work with margin.

Or maybe that's just a fox that's lying down there - and depending on road, speed, etc - you take more risk dodging, breaking and car SHOULD just go.

Just one example I immediately thought of.

I just don't think autonomous cars is a problem worth working on if the requirement is that they need to work on existing road infrastructure. We are going to get half baked, not-really-autonomous vehicles and the manufacturers are going to shift blame to the drivers because they should have known better than to use their vehicle's advertised autonomy in (x) specific circumstances, where x is the infinitely variable realities of the outside world.

With that in mind, is this really a question of context? The presence of an entity that reflects LIDAR should be enough of a reason for the system to brake.

Yes, this would imply lower threshold of what would be a situation that warrants braking, and hence on many ordinary streets autopilot may become unusable or car movement could be perceptually too slow.

To your point about rail network, autonomous rail lines do exist—I’ve used the new light rail system in Macau, and trains are entirely driverless. (From my observation of their behavior, they do not appear to be controlled remotely either.) I imagine some factors that impede innovation in this space do apply to cars (e.g., track security), but others don’t (guaranteeing stopping distance for long trains with heavy cargo, keeping people employed, arguably less flexible infrastructure).

My point is if the best we can do is a LIDAR detection auto-stop then that's not full autonomy, and I question how close we'll actually get to contextually aware autonomy.

> To your point about rail network, there are autonomous rail lines—I’ve used the new light rail system in Macau, and trains are entirely driverless.

That is actually really cool to hear. I know I come across as a Luddite by having a pessimistic view on car autonomy, but I will be happy if we can crack it.

If there is rain and/or your payload is heavy, that increases your braking distance, so accordingly detection should either work further ahead or your speed would have to be reduced to allow for safe braking.

> is the object moving toward me

This is a very valid point. If not all vehicles are autonomous, even on a well-protected highway it is possible to have a cascading accident caused by human mistake. This would even be an issue if all vehicles are autonomous, since some could be hijacked by owners.

In my view this type of “dumb” object detection for emergency braking purposes should work together with contextually aware AI-based overall autonomy, not instead of it. Upthread I wrote “an autopilot should not be entrusted to decide further”, which was perhaps ambiguous—meant that in context of an anomaly ahead.

> An autopilot should not be entrusted to decide further, beyond anomaly detection sufficiently far ahead to allow for braking.

This isn't possible. Not just technical but theoretical. Situations in streets can change way to fast. Both through external factors and other cars. Even on a straight highway with fences on the side to prevent anything from going on it this would still but work. Once it happens an intermediate decision is needed which can not be reached on time by delegation to the driver (as the driver want driving you can't except a good reaction speed even if that person had the eyes on the road).

Then drive slower. It's a speed limit not a speed minimum.

When I was training for my drivers license (in Denmark) my instructor told me to never drive so fast that I wouldn't be able to break to a complete stop within the current visible distance.

On highways, enough clearance from the sides of the road and wide enough detection beam cone may be able to help. Yes, I imagine in such a case high-speed motorways would warrant security measures similar to those around high-speed train tracks.

On denser city streets where restricting pedestrian access is not feasible nor desirable[0], appropriate (yes, probably pretty low) speed limits could reduce braking distance and hence the chance of a tragic accident to below what currently happens with human drivers.

[0] This concerns existing streets. For new areas, infrastructure that separates car and pedestrian traffic with tunnels/bridges and accessible over-/underpasses could address that naturally.

Your suggested scheme for driving offers zero protection from cross traffic cutting in front of the autonomous vehicle, whether at a stoplight or otherwise.

Moreover, not all non-driveable space is created equal, so if the vehicle has to swerve to avoid a collision, it should be able to identify the difference between, say, a clearing, a pedestrian, and a pond.

These are totally basic principles with which any driver (and especially any motorcyclist) would have no trouble. The problem with your imperative statement is that it produces a pointlessly elegant, practically bad solution.

I'll go further. To avoid clearings, ponds, and pedestrians, Self-driving cars should be highway-daytime only until proven reliable. Starting with the edge cases and building back to the easy ones is ridiculous engineering policy.

But they still hadn't figured out how to differentiate between a crumpled paper bag and a rock, or a pothole filled with water vs a smooth surface. Otherwise, it was really impressive.

Found it on YouTube: https://www.youtube.com/watch?v=3KPYIaks1UY

I feel like Level 4 or 5 Autonomous Driving will be the same -- there are just some problems that will never be solved well enough to make it work acceptably.

This could exist now, but we have set sights on Level 5 at the expense of pragmatism.

If you turn up the forward looking anomaly detection and safety factor too much... well, among other things, the non-linear controller is going to emergency brake for no good reason (Tesla owners have already reported this). Spurious emergency braking is extremely dangerous for traffic behind a vehicle and the danger increases at higher speeds where the controller will be even more touchy.

In my opinion, autonomous driving should be highway only, daytime only until proven effective in mass produced vehicles. The hype about rushing to level 5 is marketing, not a feasible technology roadmap.

And even if: are its breaks strong enough to prevent it from crossing your way? (Or the other way round: What is likely its maximum acceleration?)

Please note that all of the above can happen even without any adversarial intentions.

Deploy self-driving on marked single-lane AI-only highways. Maybe let self-driving cars use bus lanes. But that's it for now, until we can certify and understand limitations of a system. It's only fair to the public to have slow rollouts that require mostly-attentive driving.

However one big problem with deploying systems using this approach today is that it happens to be very hard to do this with enough nines that your car isn't slowing down or emergency braking for spurious inputs. Floating plastic bag / leaf - trash on the road - asphalt line that looks wrong - camera glare - a puddle with a reflection - giant sticker of a photo of a traffic cone - etc. etc. etc. State of the art would probably be undriveably cautious today.

Most things that don't look like road, between lane markers on a highway, are still drivable space. Probably 99%.

That doesn't mean it's the right approach. Just that the alternative isn't really deployable today.

This should immediately preclude any approach to self driving cars that has pedestrians, bags of trash, debris, cross traffic, etc. Highway (and probably daytime) only. I don't understand the obsession with starting with corner cases and working back to the very real good that self-driving autonomy can do on highways at speed. Build back with lessons learned, rather than solving the whole problem in one shot. That seems like fundamental engineering, but the marketing team is in charge, not the engineers.

The cliché example is when people tried to build a tank classifier. Since they took the pictures of the different tank types on different days, the AI learned to detect the weather conditions instead.

So to determine if your AI is detecting the roads absence, you would first need a lot of testing images that look realistic in general, but with absent road. As far as I know, such a dataset does not publicly exist yet.

So yes, that commenters approach seems new to me.

To understand how their AI reached decisions, Müller and his team developed an inspection program known as Layerwise Relevance Propagation, or LRP. It can take an AI’s decision and work backwards through the program’s neural network to reveal how a decision was made.

In a simple test, Müller’s team used LRP to work out how two top-performing AIs recognised horses in a vast library of images used by computer vision scientists. While one AI focused rightly on the animal’s features, the other based its decision wholly on a bunch of pixels at the bottom left corner of each horse image. The pixels turned out to contain a copyright tag for the horse pictures. The AI worked perfectly for entirely spurious reasons. “This is why opening the black box is important,” says Müller. “We have to make sure we get the right answers for the right reasons.”

https://www.theguardian.com/science/2017/nov/05/computer-say...

There is, in general, a great deal of work on explaining the decisions of neural net. Explainable AI is a thing, with much funding and research activity and there's books and papers etc, e.g. https://link.springer.com/book/10.1007/978-3-030-28954-6.

And all this is becaue, quite regardless of whether that tank story is real or not, figuring out what a neural network has actually learned is very, very difficult.

One might even say that it is completely, er, irrelevant, whether the tank story really happened or not, because it certainly captures the reality of working with neural networks very precisely.

Incidentally, (human) kids should never be allowed to hug sheep or goats like that. They can easily catch something nasty (enterotoxic E. coli, mostly). See e.g.:

https://www.bbc.co.uk/news/uk-england-lancashire-35039878

Juliette Martin, of Clitheroe, took her daughter Annabelle, 7, to the 'Lambing Live' event at Easter last year.

The youngster, who had bottle-fed a lamb, suffered kidney failure and needed three operations, three blood transfusions and 11 days of dialysis.

This is probably the reason why this story has been repeated so many times (and with so many variations): beause it rings true to anyone who has ever trained a neural net, or interacted with a neural net for any significant amount of time. Unfortunately, the article you cite chooses to suggest otherwise.

In any case, if the tank story is an urban legend it has its roots firmly in reality.

I'm happy to accept my mistake if I have misunderstood Plyphon_'s comment.

Cars used to weigh /less/. The weight is the price of all of our drastically improved safety systems. Either way, you're stuck with a lot of that infrastructure if you want to move food and other goods between cities. All of that is the price of flexibility in our logistics.

The great wonder of our time is that we can do all of that _and_ start the long process of deprecating using fossil fuels. Now, if we can build the cars to last much longer than we currently do, we're really starting to win.

> and better/more public transportation.

I feel like there's a hidden trade off here as well. I think the "better" and "more available" you make public transportation, the less dense your ridership gets on certain lines, and the less likely you are to truly gain any efficiency across the system.

Urban sprawl is part of the problem and should be addressed at the same time.

I say this because having a solid model of these terms is required when making "intuitive conjecture" about what is and isn't feasibly possible. Driving is NP-Hard? It would hint that humans have brains capable of computation more powerful than a turing machine. Which... suffice it to say we probably don't. I'm not aware of any proven algorithms that humans can compute which computers cannot.

In images free of distortion and noise, computers were outperforming humans in image recognition 2 years ago! [0]. Since then, with advances in GANs (which specifically addresses the noise/distortion issue), I suspect we are close to achieving super-human image recognition. The last missing piece is "context" or prior knowledge. If you only see a whisp of hair sticking out from behind an object, you have prior knowledge that hair grows on humans, and that there's probably a person there. This last piece is being addressed by multi-modal networks [1].

If you have any doubt of the power of computer vision, my last hope is to link you to this paper from 2017, look at the "regions-hierarchical" results:

https://cs.stanford.edu/people/ranjaykrishna/im2p/index.html

[0] https://arxiv.org/pdf/1706.06969.pdf [1] https://www.themtank.org/multi-modal-methods

I think there's a good gap in the market to be made by E-Bikes, but it needs regulatory help (Bike lans with barricades) to make people feel safe enough to commute.

My reasonably old and frail father has an E-Bike and he zips around town on it. The hill assist is great (Though i did enjoy the slightest bit of schadenfreude when he's battery died before the return uphill to his house on day) But he lives in a town with a lot of bike paths, so he's not really on the road.

I think if you can break open that market you could make driving safer and make biking safer. It's just right now driving is a wealthy gabmit. Rich people drive tesla's and value signal with them it's not a new issue but getting people onto bicycles would be great for everyone on the road.

Roads, human lives, traffic congestion, etc are much larger issues than energy. Over 20% of NYC is devoted to cars and they don’t even come close to covering the cities transportation needs.

ICE cars lose a lot of the energy stored in gasoline to waste heat, especially in city driving.

That's to say nothing of the challenge of generating gasoline from solar energy.

[1] https://www.tesla.com/ns_videos/tesla-impact-report-2019.pdf , page 16

[2] https://ir.tesla.com/news-releases/news-release-details/tesl...

[3] https://www.eia.gov/tools/faqs/faq.php?id=74&t=11

The parent seemed to be talking about cars in general, so I wasn't referring to Teslas in particular.

I can try this again using some different sources and methods.

- GDP of $1000 equates to about 1540 pounds CO2.[1]

- Each pound of CO2 implies about a kWh based on average power generation intensity.[2]

- Therefore, a $30K car implies 30 x 1540 or about 46,200 kWh.

- Divided by 15 years and by 365 days gives about 8.5 kWh per day.

So, I was probably off by a lot, and may still be off, but I feel like my point is intact, because 8.5 kWh still almost doubles the energy requirement originally stated. It's not negligible.

[1]https://en.wikipedia.org/wiki/Emission_intensity

[2]https://www.eia.gov/tools/faqs/faq.php?id=74&t=11

However you look at it, Tesla or not, 10 kWh leaves out a lot which was my original point.

Secondly, GDP to CO2 figures are a poor fit. Agriculture for example is directly 10% of US CO2 emissions but only 5.4% of GDP.

First thing that comes up when I Google:

"While an average lifespan of vehicles is not given in the IHS report, a 2014 Automotive News article stated that, at that time, the peak lifespan or “scrapping age” of a vehicle was 13 to 17 years old"

From 2014: https://www.nbcnews.com/business/autos/old-clunkers-rule-roa...

How many of these "pre-'99" models are still around? 53.3 million.

https://blogs.nicholas.duke.edu/citizenscientist/embodied-en...

The average car is a smidge under 12 years old, which is about 17kWh/day.

I think few are willing to accept autopilots that are only as bad as (or as good as) humans. They must be significantly better than human drivers, simply because we don't accept their errors like we do human errors.

This is completely irrational when looked at purely from a safety point of view (Who doesn't want safer roads?), but this obstacle is very real.

Worse: that autonomous cars are better in many scenarios or aspects (they don't get sleepy, they are never drunk) doesn't mean we accept that they are ever worse in any other aspect, despite the total safety being better.

That is: autonomous vehicles must not just be as good as human drivers, they must be significantly better (or at least safer) than human drivers. And not only that, they must be significatly better in every aspect of driving, for them to gain acceptance.

Humans might have a judgment failure every so often, but they might realize how unsafe they are and change their behavior, or drive less, or get their license taken away. A machine consistently crashing cars has no self correction protocol, and will consistently make the same mistake over and over.

Moreover, trucks sometimes contain hazardous or flammable materials.

So the answer to your question is a resounding no, in my view.

The machine ought to be an error handler for specific failures of an active human driver (sudden braking of lead vehicle, lane straying, etc). This is the only way to get both machine and human to pay full attention. A person in a co-pilot role will struggle to react quickly enough to handle errors of the machine auto-pilot.

No kidding.

https://www.cdc.gov/niosh/docs/2001-128/pdfs/2001-128.pdf?id...: The two most dangerous things in road work, accounting for half of all of the industry's fatalities, are industrial vehicles working on the site and passenger vehicles passing it.

So, yeah, you're right - there aren't any alternative systems that manage to avoid this problem. Even humans suck at it. And if even humans can't handle construction areas safely, how can you possibly expect computers to be perfect?

* Hitting a worker is very different from hitting a truck.

* Many of those fatalities are not in clear daylight.

1. Technology should not make mind-bogglingly stupid mistakes like this, regardless of how rare they are in the grand scheme of things.

2. Because these systems use neural nets, they're black boxes and it's impossible to conduct a proper engineering analysis on them to find out when they will fail. Fuzzing the system with live humans is not engineering; it's callous disregard for human life and anybody who practices it should lose the right to call themselves an engineer.

In general a car that doesn't see a pedestrian isn't a major accident unless the pedestrian also doesn't see the car. If not for that there would be a whole lot more fatalities with human drivers as well. A self-driving car obviously shouldn't do that, but neither should a human, and they do. Which makes it less hard for the computer to do it at least as well.

You can also expect the computers to improve over time by learning from each others' mistakes, which human drivers generally don't.

It's already the case that pedestrian/car collisions are usually written off as the pedestrian's fault until proven otherwise--the Uber self-driving car that killed a pedestrian is a great example of that in action.

It all has to go wrong at once. Mistakes are common but most mistakes aren't fatal.

And by choosing to drive a car, you are dramatically raising the odds that any mistake you make is fatal (not necessarily to you).

While my personal experience on the matter is thankfully limited, I strongly suspect that the vast majority of vehicular-pedestrian accidents are mostly (or entirely) the fault of the driver, where the pedestrian started an action where it was safe to do so and the driver rapidly caused it to become unsafe before the pedestrian could react.

https://aaafoundation.org/rates-motor-vehicle-crashes-injuri...

Greater incentive for any sort of bike or small/low-tech personal vehicle, imo

What you need is to get rid of zoning density restrictions. That's the only way for more people to live close enough to things for walking and mass transit to be viable.

> What you need is to get rid of zoning density restrictions.

Most of those places were built for and are still dominated by the votes of people who don't want more density and transit options, for a variety of reasons, some reasonable, and others based in the nation's sordid racial history.

I don't agree with those people, but until the settled, voting population inhabiting those vast swathes gets significantly younger and more pro-transit and density, I don't see what you call for happening soon.

In the US, mostly the only 'good' bus service is geared for 9-5 workers in big offices in big cities. Anything outside of that tends to run across the economic divide that: people who take the bus _have_ to take the bus, while taking the car is a luxury in time, freedom, and isolation from possibly literally unwashed masses (who might also literally be taking the bus in the summer for a place to have some AC and safety with a seat).

The issue is very much related to classism and a lack of social safety nets and inclusion.

In the sort of place I'm used to, an urban area of about a million people, taking the bus is not logical if you have a car anyway. You don't get an economic benefit if you own and insure a car at all. And you pay a big penalty in time and flexibility.

That's what creates the class divide, not something arbitrary in peoples' heads. The people who ride the bus because it's economically rational are inherently the people who have no choice.

Talking about general social problems as the source of the issue is misguided, in my opinion.

And a good transit system can beat many car trips, even for people that do have cars. Especially if parking spaces stop being subsidized.

I suspect that only applies to the cores of European cities - most have got much larger since the car was invented and the newer areas were definitely designed with cars in mind.

e.g. Maps of Edinburgh over a few centuries:

https://maps.nls.uk/towns/edinburgh-city.html

Even in the 1920s Edinburgh was pretty small compared to its current extent.

I lived in SF for a period. I was lucky enough to be able to walk to work, but my roommate had to take two busses both ways. At least once/week one of those would go offline and they’d have to walk.

So there are multiple factors at play. Short of a massive change in the way American cities are designed or some innovation that greatly reduces the cost of building public transportation, cars will continue to be something Americans absolutely need for surviving.

If "noisy and infrequent" doesn't mean "not good" to you, what does?

Taking a bus would add anywhere from 15-45 minutes to my ~5mi commute, with the uncertainty mainly due to the infrequency. That's not good.

It's inconvenient / not ideal. I took a loud, full, public transport bus to school in my home town every day. It was not always on time. It got me to the destination every day though.

It was not great, but it was good enough. Sure, a car would be better, but if everyone did that everyone would be even later and busses would be even more infrequent.

In addition to the risk of violence, there are also the annoyances. Smelly homeless people. People smoking. People blasting music. (The buskers are the worst.) In a car I have none of those issues. I don't even have to listen to someone loudly talking on their phone. It's quiet. It's clean. It leaves when I'm ready. It's far less stressful.

Nowadays there are only a couple of commuter bus lines that I'll take. Though with the lockdowns and the curfews, it's been months since I've used them.

Here are some examples.

This guy has been arrested, charged, and released on his own recognizance five separate times. None of the cases have been closed yet: https://twitter.com/SFPDTenderloin/status/123955010416546611...

This guy was arrested, charged, and released without bail several times before he hacked someone up with a machete: https://twitter.com/SFPDTenderloin/status/122409012050613452...

This guy has been breaking into cars for over a year. He was caught multiple times and released on his own recognizance: https://twitter.com/SFPDTenderloin/status/121391498699874713...

Most of the bay area is like this and criminals know it. It's hard to describe just how bad property crime is here. Everyone I know has given up reporting when their bike is stolen or when their car has its windows smashed. They know the police won't do anything.

It is weird that most of the world seems to manage that just fine. At least in Germany they also have no issue with calling the police on misbehaving passengers.

[0]: https://old.reddit.com/r/TwoXChromosomes/comments/f92kp7/pub...

Then you have to go places the bus doesn't go often enough that you need a car, and once you've already paid for a car and taxes and insurance, it costs more to take the bus than the incremental cost of driving everywhere.

I agree and mentioned this in my other comment, but I'd also add that in my experience there are arbitrary* gaps in what routes are available.

Nearly all the buses in the city where I live go west to east, from a certain midpoint to down town. But I live about 10 minutes south of a point on the western side and there are really no routes that go north-south here. And I work for a major employer.

*Seemingly arbitrary to me, but of course they might rationally determine there's not enough riders.

I wonder if someone can comment on the relevant advances on giving AI the proper human-designed boundaries that may help?

Well, I mean, according to some philosophers, our existence is proof that it can at least be done in the physical world...

I'm not sure why you think so. At some point the dimensions will get diminishing returns. Maybe you need only 100x the data at this point (or maybe not). But assuming it's both without knowing the current configuration / limits is just a random guess.

100% agreed. Unfortunately improving transportation and mobility is pretty much orthogonal to profiting off the ai/ml hype cycle.

Reportedly it can't.

https://www.wired.com/story/tesla-autopilot-why-crash-radar/

How often are willing to have your car perform an emergency stop for an overhead sign? How safe is it to have your car brake aggressively in a middle of the highway for nothing?

But we definitely do.

https://www.cbsnews.com/news/automatic-emergency-braking-in-...

The price we pay for having relatively few false positives is a high false negative rate. For example, a Tesla won't stop for an overturned truck or the pedestrian standing next to it.

The way these work is by tracking other moving objects around you rather than stationary objects you are approaching.

It'll track another car to see if it emergency brakes or changes lane too close to you, but it won't track a parked car on the road that you side swipe or head into etc.