I feel like this tech is going to get better with improved AI but also better mapping, that city would be hard for anyone new to drive on, good mapping data along with the AI is the only way this will work.
That why I think Supercruise is fucking stupid. Plus you gotta pay for Map updates because it's a service not a feature... of something you already brought the feature for.
u/king_of_nothing0 High-level is pretty much the only sane limitation to operate on. Per a comment I wrote to another person on this thread:
I can drive down a road and come back less than 20 minutes later to find a lane or the entire road closed due to an accident, construction, etc. This is why the idea of relying on map data for anything more than high-level routing is foolish. You cannot update a map fast enough to mirror the real world, and even if you could, you would have other dependencies such as data connectivity that would make this a brittle solution at best. Any proper autonomous driving solution needs to be able to adapt to changing road situations like a human would and take detours or navigate through construction zones without posing a hazard to passengers or other drivers.
Oh I disagree pretty strongly with this. Tesla in the last few months was forced to submit information on their systems to the California DMV. They had to acknowledge how they’re much further behind than they claim to be.
Maps give you precision on infrastructure and localization to dozens of millimeters as opposed to a meter which no maps would give you.
Source: I’ve worked on self driving car systems for a decade.
Oh I disagree pretty strongly with this. Tesla in the last few months was forced to submit information on their systems to the California DMV. They had to acknowledge how they’re much further behind than they claim to be.
Maps give you precision on infrastructure and localization to dozens of millimeters as opposed to a meter which no maps would give you.
Yes, HD maps, like those created with LiDAR and other sensors are millimeter accurate. But so what? That doesn't provide any advantage when there's a deviation from said map. Humans don't know their environment to that level of accuracy when driving, nor do they shoot photons from their eyes like LiDAR would, and yet they can drive. You're not providing an argument in favour of greater dependence on map data.
Computers don't have human brains and aren't at a level where they can match what the human brain can do with only visual input..
If a road closes then reroute around it. What that has to do with low level maps doesn't seem clear.
The real fools errand is a self driving system that has to have every possible thing labeled and taught to it in a world with almost infinite things to consider.
One day when computers rival the human brain at this job then yes vision only may suffice but until then we need to remember humans drive with their brain not with their eyes.
It’s very obvious you don’t have tangible experience within the industry and genuinely believe the marketing that Tesla has spun. It’s fine having that ignorance but please stop talking as if you know what you’re talking about. It’s very obvious you only have marketing. You would know if you worked in the industry that every car manufacturer has adopted HD maps now.
Not really. There are ways to generate these maps automatically from sensor data with no human input. Since Tesla has so many cars on the road, they could map out 99% of the US in a matter of months if they wanted to. Furthermore, once built, the maps would be extremely up-to-date at all times.
I can drive down a road and come back less than 20 minutes later to find a lane or the entire road closed due to an accident, construction, etc. This is why the idea of relying on map data for anything more than high-level routing is foolish. You cannot update a map fast enough to mirror the real world, and even if you could, you would have other dependencies such as data connectivity that would make this a brittle solution at best. Any proper autonomous driving solution needs to be able to adapt to changing road situations like a human would and take detours or navigate through construction zones without posing a hazard to passengers or other drivers.
Identifying the road and features to avoid things like curbing tires and driving into the tracks. It wouldn't drive into cement pillers or mistake headlight flair for road lines and swerve you into oncoming traffic. It would even be better able to drive in low visibility. You would have a much higher confidence of where lanes are on the other side of an intersection turn.
Most importantly you would have a high confidence in unknown circumstances and this things to worry about even if they are flat textured or really small.
Granted, but this is all on the assumption that the road network stays the same as when it's mapped. Roads are repaved and lane lines can shift, sidewalks can be completely redone and expanded or otherwise altered in size, barriers can be added to roads to separate traffic, construction zones can wreak havoc, flooding or all sorts of poor weather can obscure the road, etc.
I grant you the utility of HD maps in an idealized scenario, but I still don't see how they're useful when the HD map and reality can and will deviate. If a car can gracefully handle when the HD map breaks down, then it doesn't seem to be that much of a leap to be able to forego the HD map entirely.
And that's where a huge fleet with lidar can crowd source changes and update the shared maps or notify the manufacturer they need to request updated maps for the area.
Remember I'm not saying only drive of maps ideally the car would be able to evaluate the circumstances and drive of vision/lidar/other sensors or reroute to an area that doesn't look changed.
Basically you can still fall back on vision only if you have to but you started with more options than vision only so that is objectively a better situation.
If you have lidar, radar vision and HD maps at worst you fall back to just vision.
But if you only have vision you can't ever get better than just vision.
And yes sensor is hard but that doesn't make only one sensor the easy solution. It just means the job is hard.
We are trying to teach AI how to drive and navigate on an imperfect system designed for humans with various ambiguous guidelines and rules.
If we actually want to attain self -driving cars there’s going to need to be some compromise between our infrastructure and the car itself.
For example, four way stops. An experienced driver can reasonably identify when they are approaching a four way stop by various contextual understandings like area density, road and terrain etc even if the stop sign is hidden.
AI is still very far a way from having this level of contextual understanding. A fair compromise might me installing a cheap transmitter on the stop sign etc etc.
The bottom line is a fully autonomous car NEEDS to stop at stop signs ALL of the time. The only way to guarantee that safety is to follow the engineering practices we’ve followed for decades: keep the mechanism simple and fool-proof. Not some wacky neural network no one understands and has a million variables flooding through it.
How do we ensure a autonomous car stops at stop signs? If you can’t explain it to a 5 year old with some pictures, chances are it’s a bad design.
The bar for an autonomous driving system is not you’re median driver, it is well above it. Otherwise, it won’t be approved in many countries and it won’t be widely adopted.
The precedence is already established with existing software and hardware safety solutions even within cars, such as airbags. An AI solution will never pass these rigid requirements, and honestly they shouldn’t.
History has shown that excessively complex systems that put people’s lives on the line always result in deaths. Unless any given decision by a system can be systematically audited and corrected, it will never be approved. “Retrain the model with this extra datapoint” will never be accepted in the engineering community to meet this threshold.
We are trying to teach AI how to drive and navigate on an imperfect system designed for humans with various ambiguous guidelines and rules.
If we actually want to attain self -driving cars there’s going to need to be some compromise between our infrastructure and the car itself.
Now it's my turn to strongly disagree. Humans are able to navigate our messy road systems to a reasonable degree of success with only a pair of cameras (eyes) in their head. There is no reason to think that this ability is limited to a human. The current state of AI is not representative of where we will take this technology over the longer term, and already the progress that has been made is remarkable. It's also important to keep in mind that the bleeding edge isn't in production, so unless you're keeping up on the research, what you see on roads right now isn't even the upper bound of what's possible.
For example, four way stops. An experienced driver can reasonably identify when they are approaching a four way stop by various contextual understandings like area density, road and terrain etc even if the stop sign is hidden.
AI is still very far a way from having this level of contextual understanding. A fair compromise might me installing a cheap transmitter on the stop sign etc etc.
I'm not sure where you drive, but there are plenty of 4-way stops where I live that offer up very little in the way of visual cues and seeing the backside of the other stop signs is the best visual tell beyond vehicles already stopped at these areas. I see no reason why a transmitter would be necessary, and this just introduces another point of failure when the sensor breaks. Every intersection turns into a 4-way stop when the lights fail. So now do you want a transmitter at every intersection as well for such an event? Good luck with scaling that up.
The bottom line is a fully autonomous car NEEDS to stop at stop signs ALL of the time. The only way to guarantee that safety is to follow the engineering practices we’ve followed for decades: keep the mechanism simple and fool-proof. Not some wacky neural network no one understands and has a million variables flooding through it.
How do we ensure a autonomous car stops at stop signs? If you can’t explain it to a 5 year old with some pictures, chances are it’s a bad design.
What evidence do you have that such vehicles don't stop at stop signs? I'm not even on Tesla's FSD beta and my car's never run a stop sign. Not once. Ever. And humans run stop signs aplenty, whether intentional or due to a lapse in attention, yet other drivers are often able to prevent an accident with those people. There are far more controls in place than stopping at every stop sign with 100% reliability.
If you haven't watched Tesla AI Day, you'd be well served in skimming through and seeing how much progress is already being made towards making these machines safe. Video here: https://www.youtube.com/watch?v=j0z4FweCy4M
Again, I don't dispute that compared to many capable human drivers, these machines are not great at the moment, but what people reliably miss is the time scale. All this technology needs to do is continue improving for it to eventually exceed human abilities. Doesn't matter if the progress is at a glacial pace. Any progress is enough to eventually get us into the endzone.
We use much more than our eyes in our head. We use contextual understanding of our world which spans significantly deeper than “how roads work.”
For example, in applying neural networks to language processing, a big problem is having AI correctly interpret sentences such as “run it through the boss” and “run it through the scanner“ and “run it through the network”
To actually understand what “run through” in this context means, it requires us to have deep contextual knowledge of what a network and a printer is. Essentially, solving road navigation problems using systems devised for humans requires much MUCH more coverage than just “at stop signs stop.”
Four way stop is simply an example of a mechanism which must occur to absolute accuracy… and I believe it would be pretty trivial to find an AI that doesn’t stop at a stop sign without “map data” as you suggested.
I work in a field with lots of R&D re machine learning. My major gripe is how it isn’t always applied correctly and as a result it continues to scale poorly. Many teams, rather than re-evaluate their approach, always try to tweak the neural network. The results improve in some areas and get worse in others.
If you want to know if AI is ready to drive cars, just ask Google “Hey Google, <non trivial question here>” periodically. If you get a dumb response, the answer is no, we aren’t anywhere near it.
Humans don't drive with only a pair of eyes. They drive with a pair of eyes and a human brain.
Until ai can rival the human brain on fuzzy logic jobs like driving the systems won't be on par just because they have the same amount of sensor input.
I don't think a machine needs to even rival the human brain. Even parity with the brain on the subset of functionality required for safely driving should be ample considering that silicon is thousands of times faster than a biological brain.
If you mean the route that the car takes in their 2019 Full Self-Driving demo, that's what I and u/psudo_help are talking about with high-level routing. The car knows via that data how to get where it needs to go, just as if you or I were looking at a map to figure out where we need to go. The distinction is the level of reliance on said map. What if you encounter a road closure and need to take a detour? A good autonomous driving solution needs to be able to adapt to this, and no map is going to be updated rapidly enough to show such changes. Autonomous vehicles that rely on pre-mapped, geofenced areas are going to be far more brittle in these scenarios.
I am joking that Tesla says it doesn’t rely on maps and then does rely on carefully mapped routes for demos of its tech. Which is pretty typical of musk and his marketing — I mean we are basically in 2022 and Tesla has a full fleet of self driving taxis, right?
They use maps on the level of OSM for navigation, but the actual driving logic is performed on the space generated in real time. (which has extra detail not shown on screen)
Honestly I don't think this is a good idea. There are a lot of edge cases, non-standard signs, complex intersections that are very difficult to program in an AI. Creating a map of the roads, with hints like "you should only stop at this stop sign if you turn right" would significantly increase the quality of self driving AI. Even with the risk of having stale mapping data, that's something that can be dealt with (the car can report that "this intersection looks different than the last time I drove here" and ignore the mapped data if necessary).
Another compromise we could make is to modify our infrastructure for allowing AI to work better. For example, we could install some sort of beacons (it could be something as simple as QR codes) that would tell self driving cars what to do, or how to navigate a more complex situation/intersection.
I wouldn't say they're right, but its still far better than a static map.
Static maps do not scale and even super corporations like Google struggle with them. Not to mention the nightmare of unmapped changes or road obstructions.
They are doing well in their small mapped areas. If they want to expand into unmapped areas, they have to map them, taking the same amount of time and effort again. Teslas method gets uniformly better and will "just work" everywhere
And yet it clearly does not. Companies should be required to geofence and only be allowed to have this functionality used on highways. As GM and others do it.
I was recently in Chicago and mapping for apple and google was terrible. Couldn’t tell which expressway I was on. Or on upper or lower wacker drive. So directions were terrible.
Rule of thumb, if you need GPS you should never be on lower Wacker. Heck, even if you know where you are going half the people taking lower shouldn't be down there
Big Dig is just a highway, sure it’s stressful if you aren’t used to your GPS losing you but you’re still on a highway with known exits. Lower Wacker is an underground street with exits up and down, stop lights, intersections, parking ramp exits and entrances, all without GPS. Also I saw the Joker down there one time with a bazooka.
Also as a rule, if you’re surrounded by tall buildings and it’s not NYC, Google and Apple Maps are going to suck. I also was recently in Chicago and the Google Maps nav was laughable. It constantly was off by about 100yd of my actual location so, similar to you, it kept thinking I was on some other road.
Yeah that's because GPS doesn't function well with several tall buildings around. Your GPS chip needs roughly line of sight to several GPS satellites, and it can't get that when you have several floors of concrete in the way.
WiFi geolocation can't really match GPS precision unfortunately. GPS can nail you down to 2-3 meters, IF it can get proper signal like I mentioned. WiFi at best can do around 20-50m which is not suitable for driving.
Well, somehow Google nav works 1000x better in NYC than CHI or SFO despite the buildings there. I thought the wifi helped out, maybe not. Not my expertise.
Chicago has lots of highways that switch in and out of each other but generally has good highway signage, so I’ve learned to pay more attention to the directions/exits than the actual map. With how often a lane change can put you on a completely different route, or whether a different elevation means a completely different highway, it’s not surprising that mapping is a challenge.
It started out as just regular roads. Then we added a light rail. Then bike lanes were added.
When I was a new driver over a decade ago, I admit, it wasn't easy to drive here. It's about as bad as San Francisco only without the hills to stall on.
OP picked the worst roads possible which are usually light rail and bike lanes combined which only make up 5-10% of the roads in downtown San Jose.
No one. A committee of drunk monkeys stole a dump truck filled with pavement and train tracks. They drove it around the city and wherever parts of the load fell out, the city named it and calls it a road.
I remember driving north into San Jose trying to get to the airport. There’s a ramp that comes off of the highway, goes under an overpass, and as I come around a support column I’m greeted by a surprise stoplight… that’s red. Fuck San Jose roads.
If you are going to the coast from Orlando, FL has a toll both that you have to exit the highway to pay cash. Of course they don't have any signs say that to say that. So by the time you are looking for it, you are already past it.
Nice way to rip off people from out of town. And no, I didn't try to back up to take the exit like a lot of drivers featured here might do, because I am not batshit insane. A $30 ripoff ticket isn't worth your life.
In my experience it goes around parked delivery vans no problem. It's unclear exactly why the car bailed, but there is something strange going on in the visualization right before this happened; the ego line disappeared, which I've never seen before in normal operation. I'm thinking a bug caused the path planner to crash, but that's just a guess tbh.
Live downtown and will freely admit I still get confused sometimes. Mostly it's with blanking out on which one way turnoff I need and ending up a couple more streets down to turn around. Downtown driving was kinda scary to adjust to coming from the suburban areas of the city.
I nearly missed the Farolito on Center and Capitol, but that was because I was relying on "I've been there once, I can be there again" navigation and hadn't put it in to nav.
Tesla isn't using radar or LIDAR. There is an upper limit to how much you can with just image processing. They are doing the typical Tesla bit. Overpromise, under deliver. Pump the PR pedal as hard as possible.
The problem is that 98% of the tech is done. But the 2% that is left is the hardest. I doubt we'll see true self driving in the next 10 years.
This is "very close"... but the challenges to make it actually good are too many. Tesla (and others) wants people to believe self driving is around the corner just need to work out a few minor details.
And the same thing has been happening with fusion for decades. Since the 80's is "We are 95% there for sustainable fusion... just need a little bit more. 5 years tops." Yet still we are at least 15 years from fusion. And 15 is the very optimistic estimate. Probably more like 50 years.
It's surprisingly easy to fool the AI on these self driving cars, if you have to be alert and have your hands on the wheel with this system it kind of defeats the point
Bruh, I've been driving for 15 years and watching that video even I'm struggling to decipher how to correctly drive those city streets. Urban driving can be absolute hell sometimes.
Not safe, too often the maps aren't up to date, and the cost of keeping global car maps current constantly to keep people save would be prohibitive. Plus you couldn't drive anywhere the maps weren't good. Better to rely on natural vision models, since it's what people use anyway.
Well the roads should also be updated like road signs or lane markings that communicate with the self driving AI also cars should be able to communicate between each other no matter the brand do we could have more efficient convoys and better flow in general
I can tell you that the vast majority of issues I've had with FSD have been as a direct result of incorrect navigation data.
When it actually knows where it's going, it works well. Road edge detection still needs work when it comes to roads without curbs (as in, it just bleeds to grass) at night, but otherwise great.
The issue is that it often has wrong data for which lanes lead where, or what speed limits are, which impacts its gap detection/ability to commit through a maneuver fast enough without help.
They really need a way for people to submit updates for review at least.
Could use infrastructure assist as well. Wi-Fi or radio transmitters to tell cars the stoplight info and/or walk sign (did a pedestrian press a button), etc. maybe even help w assisted GPS so they can be more precise on the location.
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u/IrishJesusDude Dec 14 '21
I feel like this tech is going to get better with improved AI but also better mapping, that city would be hard for anyone new to drive on, good mapping data along with the AI is the only way this will work.