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leto78 t1_iudw7cu wrote

The problem is not the technology but rather a fundamentally flawed business strategy. Fortunately, there is a linear technological development roadmap between ADAS and full self driving. The correct approach would have been to bet on incremental improvements until FSD was achieved. Trying to leapfrog to FSD was too much of a gap and people underestimated the complexity of the problem, the maturity of the technology, and effort required to achieve the goals.

New technologies like solid state LIDAR systems, better Image Recognition systems, multispectral cameras, and other technologies are getting more mature and cheaper so that they will be easily integrated into a vehicle in an affordable manner. All these technologies will make ADAS systems better and better, up to a point that they will have full awareness of the environment, and be able to achieve FSD. On the IA front, there is still a lot of work to be done, especially in terms of sensor fusion, namely being able to integrate data from cameras, using multiple frequency bands, with LIDAR point maps, and ultrasonic sensors.

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mclark9 t1_iue1205 wrote

I disagree, there is not an ‘incremental improvements’ path from ADAS to FSD. From an engineering standpoint, they are two totally different problems.

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leto78 t1_iue93vy wrote

Personally, I don't think that they are completely different systems. From from ICE to BEV is definitely going from system to another completely different system, and hybrid systems are not really a transition path from a technological development. You cannot make ever greater improvements to ICE vehicles and get to BEV vehicles. You need a radical departure from one to the other.

As for ADAS and FSD, they rely on the same hardware, same technology, and same focus. The adaptive cruise control with lane keeping system is one narrow scope of the overall FSD. Of course, there is a huge technological leap that is required to reach FSD, but a progressive development is a direct path to FSD.

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mclark9 t1_iuebrjz wrote

Agree that there are technology overlaps, like sensing systems. But the difficult engineering problems like, mapping, decision making, stop and go interactions with other vehicles, etc. are not going to be solved by iterating ADAS technologies because they are not ADAS problems. Time will tell which of us is correct, I guess, because many of the ARGO people will be going to Ford to work on ADAS technologies.

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UrbanGhost114 t1_iufi6g8 wrote

The leap is really getting all that information from the various ADAS programs, and compiling them to make a correct decision with the AI (which doesn't even exist yet).

Right now, no system can make enough correct decisions with the information for anyone to feel like this is anywhere close to being ready for FSD at any stage, at least publicly (No idea what DARPA looks like with this kind of stuff).

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fibonacci16180 t1_iue7otj wrote

ADAS levels 2 to 5 require exponential levels of investment, not linear in any way. Even the L2+ systems are pretty disappointing. GM had to scan the entire highway network to get their system to work, and Tesla’s and Comma.AI don’t work that well at all. Mercedes has a L3 system for the easiest use case (stop and go traffic on the highway). Waymo’s L4 seems like it works, but the fact that it’s in a controlled environment and they haven’t scaled the service after years of operation is pretty telling about the state of the technology. We’ve been “18 months away” from the promised land for a decade. As it turns out, AI is way harder than anyone thought.

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keijikage t1_iufgi49 wrote

Thoughts on the mobile eye solution? They seemed pretty good, barring the hardware costs.

I actually run openpilot, and I think it's fantastic as an adas for the cost

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twowayhash t1_iugnenv wrote

Was one of the devs using Mobileye tech for a self driving car company. Never got it to work well. Traffic light detector was a 50:50 game. This was 4 years ago, not sure how good they are now!

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CarsVsHumans t1_iugb8yy wrote

What do you mean they haven't scaled? It looks to me like they are scaling exponentially. As is Cruise. Just come to SF and see how many AVs there are. The problem is we're still at the bottom of the S-curve, where you need to double several times over before it's noticeable at a macro level.

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fibonacci16180 t1_iugoino wrote

They’re testing. Rides are only open to the public in Phoenix, which has been the case since 2017. If the model was easily scalable, every city in the world would have it by now.

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defcon_penguin t1_iudz6l4 wrote

I assume that they are also doing that. Their cars have assisted driving systems, and they are going to continuously improve on them. I however doubt that with iterative improvement on those systems you are going to reach full self driving. Full self driving means that you are never going to need a steering wheel in the car, and the car can take you everywhere you could drive. That requires human level intelligence. You don't get there just by training your neural networks just a bit more

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Infamous_Yogurt2858 t1_iufgz2a wrote

Depends on how you mean. The problem isn't self-driving ability per se, but the standard of proficiency. The technology is already there to produce an FSD car, just not one capable of maintaining anything near the level of safety standard we'd require. It's entirely possible at some point, somewhere FSD cars will simply be declared "good enough" even if there are still a lot of bugs. (not saying that would necessarily be a good thing, but it's something I could see happening).

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DBDude t1_iuidqxr wrote

The question is when FSD is safer than humans. The problem is we as humans will ignore millions of accidents avoided by FSD that always has instant reaction times and doesn't get distracted, and we'll be scared of it because of rare edge cases where a human may have been able to do better.

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DeafHeretic t1_iue5ie2 wrote

>Trying to leapfrog to FSD was too much of a gap and people underestimated the complexity of the problem, the maturity of the technology, and effort required to achieve the goals.

It is a hard problem, one that as you infer, will take time and a lot of effort.

One of the harder problems I see, is driving on the kind of roads and in the kind of conditions that I have to deal with; a gravel road that is muddy or icy or covered in snow, with no easily discernable edges - especially during the night or when covered with snow - especially when covered with snow (often unplowed). Add in ruts in the snow after multiple vehicles have driven any snow covered road, and you have conditions that are hard for humans to drive thru, much less an AI.

I have 50+ years of driving experience and it isn't easy for me to navigate the roads to my house on a remote mountain. In another 10-15 years I will probably want/need a self-driving car, so I hope there is significant progress made, but while there has been significant progress made from 20 years ago, I think the developers are now hitting the hard problems and it will take more time than I have left.

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jrockwar t1_iueq24p wrote

That is the difference between L4 and L5. L4 is full self driving, unsupervised, on controlled environments. L5 is fully unsupervised, anywhere, anytime.

As someone working on this sector: I think we're about 50-100 years away from L5, if it ever happens. Getting an AI to work "anywhere, anytime" is almost an utopia.

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rcxdude t1_iug1bhg wrote

TBH, a lot of humans aren't at L5 by that standard.

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iheartjetman t1_iuewl2m wrote

Would it be easier if autonomous cars ran on train tracks (or something similar) instead of roads?

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lItsAutomaticl t1_iuexz3c wrote

If manufacturers could agree on a standard, they could start installing radio transmitters or some other sensor on roads that would keep vehicles in their lane.

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