In NYC, where I live now, the de facto rule seems to be if you hesitate at all then the other person just goes, rules be damned. In the rural south, where I'm from, there's a lot of "no no, you go first" waving/gesturing/light flashing, which I'm curious if/how a self driving car would handle. (Do we need to give the self driving cars hands to gesture with?!)
Also the feeling of "how long" is too long to wait changes a lot when you are in more of a passenger mindset.
I think we're quite a ways away from that though - hopefully not as far away as the flying car thing :)
This has been my experience pretty much everywhere I've driven, which includes a half dozen or so European countries and about as many U.S. states. Notably though I've never driven in New York, state or city.
My experience is that in larger cities, and cities with a lot of tourists, this "aggressiveness" seems to be the norm. I put that in scare quotes because I'm not sure I'd call it aggressive, I just feel it's the pragmatic way to break the tie.
Maybe that's why this is my experience everywhere – I'm that guy! (My apologies to all my fellow drivers out there!)
Lawyers will define what the rules are for a manufacturers self driving cars. After all, any accident at a 4-way stop will immediately result in blaming and then suing the manufacturer. And what are they gonna have for a defense? "Sorry, your honor, we use machine learning to decide how our car drives--as a result there is no real way to truly understand how our car will react to every situation it encounters".
“A discrete decision based upon an input having a continuous range of values cannot be made within a bounded length of time.”
The paper is available from:
http://lamport.azurewebsites.net/pubs/buridan.pdf
It shows that under very general assumptions, a decision cannot be made in bounded time, leading to starvation (metaphorically and also literally). An example is a 4-way stop with other cars arriving at various times.
The paper's history is also very interesting:
> continuous
(The paper implicitly assumes non-discrete continuity) Differential-equation based hysical models are continuous. Computational systems are discrete, as long as the clock is slower than the . Lamport surely knows this, the transition duration. He waves away the empirical disproof of his claim by arguing that reality is merely a finite approximation where low probabilities runs down to zero.
He even mentions this stuff in the paper, making the paper quite weird.
My only guess is that he fell into the trap of forgetting that infinitesimal objects ate idealized mathematical models not physical realities.
I find it is usually pretty efficient and have yet to notice someone doing the same to me at the same time.
When I was road tripping in the US, I also attempted to prevent unclear situations at 4-way stops by intentionally slowing down just a bit so it is clear that I'm not first to drive. Since I couldn't prevent the stop anyway I was usually much more comfortable with letting other people drive first, or at least with having a clear order and knowing about my position in that order.
It gets messy when people try to be polite or don't understand the rules correctly, but otherwise it's pretty easy.
It might depend on your jurisdiction, though.
Assuming cars are already at the intersection, I wait until each of them goes and then take my turn, unless it's someone's turn who wouldn't cause a conflict with me and nobody else could go at the same time and would cause a conflict with me.
When I arrive at the intersection at nearly the exact same time as someone else then some more complicated heuristics come into play (I'm not sure how you handle it when the timing is close enough to be in question). The person on a significantly larger road has priority over smaller road. People going straight have priority over right turners, which have priority over left turners, and if all else is equal, the right-most person should go first.
I guess I could sum it up as "if you can go safely, and nobody who was there before you can go safely, then go. Otherwise wait your turn", but with a lot more nuance around tie-breaking.
I guess one additional trick I use is to intentionally avoid conflicts: if it looks like I'm going to arrive at the same time as another car, I slow down a bit before arriving at the stop, then clearly stop AFTER they did, so it's clear that it's their turn to go. It works pretty well.
/shrug
People gunna peep.
But what's "simultaneous"? If I show up 0.1 seconds before the person on my right, he could think it is simultaneous and go...
There's also the direction that is 'claimed'. If there's a dedicated left turn lane or it is obvious that the person across from you is going straight, and you want to go straight, you should go too.
In the end, multiagent arbitration of a shared resource is hard.
In the late 70's in Connecticut, I was taught the first person to arrive goes first, followed by the person to their right and so on.
But there are so many holes with that heuristic itself! And putting aside guilt and anxieties of humans that prevent them from being assertive or committing--it's just a cluster fuck.*
However, I have noticed that people are becoming more comfortable with zipper merging in major cities on both coasts, so if we could arrive at some consistent 4-way stop rule that's 1) succinct, and 2) easy to remember, I have hope. :)
[* I'm referring to San Fran and the South Bay... but still better than my experiences driving through Italy and in Bengaluru!]
In practice we live in a world of (very illegal) rolling stops, people beckoning at each other to go first, people inching forward, etc.
That's not even considering some very stupidly designed four-way stops here in Illinois with two lanes on each side -- how the heck is one supposed to even figure these things out? It ends up being a game of chicken.
What if two cars arrive simultaneously at opposite sides of the 4-way and are both turning left? This could easily deadlock two self-driving cars if not considered.
Traffic signals with good sensors are more space efficient, and usually more time efficient when there's congestion, and more pedestrian friendly. Proper sensor design means no or little waiting during low traffic times too. Traffic circles can help with akward intersections though, where there's more than 4 entrances or exits, and some three way intersections work well too.
I should be able to broadcast somehow (using a voice message?) to nearby cars that "I'm going now, don't go".
In other words, if you 'hear' "don't go", you don't go. But if you don't hear anything, it still doesn't mean it's safe to go, so you'll have to rely on something else. And if you are doing that anyway, is the added complexity worth it?
This, in the long run, is a selling point that seems to be missing from most discussions in this comment section.
I can't communicate "telepathically" with fellow human drivers.
You'd have to ask all kinds of wild questions too like:
"What if kids played a prank and re-painted road lanes on a highway at 50MPH?"
"What if a sand storm happened?"
"What would the car do if a tire blows out at 55MPH?"
"Could the car detect a Tsunami is coming and abandon a trip assignment?"
And that's just a tiny tiny sample of scenarios necessary.
Some AI elements may exist within the network, but I'm pretty sure they are only running on the back end in terms of maps. The computing power to really permit the car to run autonomously, and to "adapt and learn" about driving only comes with experience and it also takes a lot more computing power and storage than your home computer can handle, much less the components in Tesla cars.
Launching Self Driving Cars so close to their infancy is pretty reckless if you ask me. People are being paid off and buried online by paid staff online to keep quiet about all the accidents and issues with them.
To make self riding cars reliable at this point in time, they pretty much need perfect circumstances, and they need to operate on fixed, predictable, and well maintained paths... Kind of like a train. They should really work on this technology in mass transit, shipping, big industry and on planes before pushing out thousands of smaller vehicles with it.
There is plenty of proof that development teams aren't and may never be flawlessness enough to make error free updates, if you don't believe that, then just ask Boeing.
I'm not really sure what this dichotomy is that you're describing. It certainly looks like they're using computer vision to detect the bounding boxes of cars, and the field of computer vision is widely described as being either a subset of artificial intelligence or a cross-disciplinary approach combining artificial intelligence with a handful of other fields.
> You'd have to ask all kinds of wild questions too like:
> "What if kids played a prank and re-painted road lanes on a highway at 50MPH?"
This sort of thing actually happens with real humans, and the legal system has to (and does) handle it. In the 1990s three people removed a stop sign as a prank and were sentenced to 15 years in prison after a human driver drove into the intersection and hit another vehicle, killing three teenagers. https://www.nytimes.com/1997/06/21/us/3-are-sentenced-to-15-.... The fact that it's possible for humans to illegally modify road markings and end up killing people is a challenge and a tragedy, but it's not anything new or particularly game-changing for self-driving cars.
> "What if a sand storm happened?"
That sounds like one of the easiest possible problems. What do humans do when they suddenly have nearly zero visibility on a road? In most places I assume they are supposed to (and do) pull over to the side of the road and stop. I've been in rain that is so heavy that all the nearby cars on the highway had to pull over.
> "What would the car do if a tire blows out at 55MPH?"
Again, that's another thing that happens a lot, and probably causes a lot of injuries and deaths. Again, I'm not minimizing that loss, but it's not some huge "gotcha" for self-driving cars. In this particular example, I would expect self-driving cars to be vastly better than most human drivers in this situation at maintaining control while pulling over and stopping.
They cause gigantic pile-ups, because humans are unbelievably bad at driving.
https://abcnews.go.com/US/50-people-injured-69-vehicle-pileu...
Cars today are vastly better at maintaining control in this situation even without self-driving. If the car has traction control, as long as the driver doesn't panic they will have a much greater chance of keeping control of their vehicle, compared to cars without a computer assisting them.
While most interest/discussion in self-driving surrounds the interpretation of the environment viz other road users, road markings and signage, I am following the (too slowly developing) Roborace, Stanford's MARTY and similar efforts to automate expert car control including handling the loss of control.
I look forward to the day when passengers can be confident that they are safer than with even the best human driver. And not just statistically safer, but demonstrably so.
There are no simple answers to the above questions, but if a driver causes the accident, they are accountable. Companies want to launch this tech but not own accountability for accidents when it could well be faulty logic and or code that contributes to deadly incidents. In a ship... less of a risk... In a car, surrounded by 4-10 other cars, the risk is much higher.
Profit making should not drive this blatant hubris... We forget how history reminds us of an over-reliance on technology and intelligent design.
try
{
while (true)
{
if (IsScenarioOutsideOfUnderstanding())
{
throw NotUnderstoodException()
}
}
}
catch (NotUnderstoodException)
{
SlowDownAndStopLikeAnyoneElseWould();
} Patch for car stopping way too often:
catch (NotUnderstoodException)
{
- SlowDownAndStopLikeAnyoneElseWould();
+ // FIXME TODO let the safety driver handle it for now
+ // SlowDownAndStopLikeAnyoneElseWould();
}Specifically, he shows an orders-of-magnitude chart, each point accompanied by a picture of a car presented at that magnitude of occurrence. At one extreme is "car" as they appear with most common frequency (in front of you, rear visible). At other extreme is "car" in an extremely unlikely occurrence (airborne, bottom view prominent). The system Tesla implements addresses such a broad range of information & occurrences.
Tesla has upwards of a million "full self driving" vehicles on the road now, all gathering video, all processing that data, all feeding what they learn & experience back to Tesla. The computers, even if not actually driving, are constantly observing situations, categorizing, and comparing to what humans do as a response. Extreme situations (crashes etc) are flagged and routed to Tesla for incident analysis; the AI is corrected & taught to handle the situations, and all vehicles updated accordingly in short order.
Upshot: Tesla DOES have a system for addressing, learning, encoding, and improving the "thousands of other" scenarios. By the time "full self driving" is unleashed, the Tesla AI system will already be trained to extremes by a million "trained, experienced, and attentive drivers"; insofar as some cases may be insufficiently covered, they will be statistically less common & dangerous than the baseline error rate of human drivers (distracted, drunk, debilitated, dumb).
As far as accountability, Tesla is working hard to build a decisive system & case that if bad happens, it is a statistical anomaly which is still better than the alternative of not using self-driving tech. There is a legal principle whereby one may violate the law when obeying it would cause greater harm; autonomous vehicles are close to crossing that line for the better.
And yes, great profit is due those who improve humanity via technology.
I'm curious how you square this with the fact that humans learn to drive with intermittent sensory input from only two cameras plus some auxiliary sensors. Clearly, humans can extrapolate from very limited input. Why can't Tesla demonstrate object permanence after years of development?
Ehm a recent Tesla has very powerful specialized hardware, developed in-house, which is much more powerful than a commodity home PC with expensive GPUs. You might want to do some basic research before you make such claims...
> The system isn't AI based... It's currently based on static programming
A large neural network is used to make many of the decisions, as well as to run the perception of the sensors/cameras. Unclear what you mean by "AI", but neural networks are usually covered in the "AI" term by researchers and engineers in this field.
> may never be flawlessness enough to make error free updates
It seems that you are new in this argument, because this point has been rebutted so many times in the past, but here goes: it does not have to be flawless, it just has to statistically cause fewer accidents per kilometer/year than what human drivers cause in a similar situation (which is already non-zero, and in some countries actually quite high).
Even though it logically makes sense, there are some nuances to it, most prominent of which is: When human drivers cause accidents, they are held responsible by the legal system. Who's responsible when your car made the decision? Is it Tesla? Is it the driver? Society is probably not going to accept a small improvement over humans while all the legal burden goes up in the air. It may demand a much higher improvement to compensate.
Any time a Tesla is involved in an accident, it seems like the company is more than happy to throw out reams of log data "proving" that it isn't their fault. But yet at the same time they maintain marketing material claiming their "auto pilot" feature is (or will be) so awesome that the human driver is only there to make the lawyers happy.
Yes, but they need a process in place to insure that that is true, and a process in place that insures that is true with each new update. They are remarkably cagey with statistics about AutoPilot.
Elon claims that Autopilot is currently much safer than human driving, yet the only statistics released are biased comparisons between Autopilot miles, which are almost exclusively on highways, and general auto statistics (where crashes occur most frequently off highways). If Elon really wanted to show the software effectiveness of current Autopilot, he could release the crash statistics of customers who purchased Autopilot and customers who did not, as many people have requested of him. He has thus far refused to.
I was referring to AI that operates independently of a network connection. There are multiple scenarios in which a network connection can become unavailable.
I'm not here to disparage Tesla, I really don't care what company creates self driving cars. Most people are acting like Tesla are the only ones.
https://ww.electrek.co/2019/04/22/tesla-full-self-driving-co...
Says who?
The fact that you state this so confidently demonstrates a lack of understanding of both human nature and politics.
https://cleantechnica.com/2020/01/31/timestamped-guide-to-pa...
At this level, the car can act autonomously but requires the driver to be prepared to take control at a moment's notice.[103][104] HW1 is suitable only on limited-access highways, and sometimes will fail to detect lane markings and disengage itself. In urban driving the system will not read traffic signals or obey stop signs. This system also does not detect pedestrians or cyclists,[105] and while AP1 detects motorcycles,[106] there has been two instances of AP rear-ending motorcycles.[107]
We have to be able to admit that we aren't ready to launch thousands of these cars out on streets at this point. They have NOT been perfect.
There are tons of issues beyond just the quality of the AI. Software development and updates, vehicle maintenance, planned obsolescence of models, Legality, ethics, ownership... tons of other issues not hashed out. The combination of all of those issues makes autonomous vehicles near impossible any time soon, unless we ALL want to give up our right to own personal property and submit our safety to being test subjects. I'm not willing to do that at this point as a development manager myself.
the OP is wrong though in somehow classifying this as 'not AI'. Just because ML has become an important part of the equation doesn't mean we have thrown control theory and logical constraints out of the window.
If a company's test cycles were good enough to warrant reliability and safety promises, the window on the CyberTruck would have never broken.... This is how companies work, they over promise and under-deliver, this time it affects everyone's safety, including safety of those who don't buy them.
I'm not saying the strides aren't impressive, I'm saying I wouldn't feel safe having this experimental technology forced upon me knowing the potential for historically complex human factors.
Not that I ever had any doubt into how complicated real-time video analysis could be, this just makes my appreciation of the complexity of the problem that much more qualified.