Waymo has lost its CEO and is still getting stymied by traffic cones

Anyone committed to self driving cars needs to be a road building company and own the road network that will manage these mostly-automated efficiency lanes, with car provision (more likely tech/compatability licensing) as a secondary income stream.

Sure it's EXTREMELY limited but that doesn't seem like an accurate description since they trust it enough to be liable for it to drive by itself or stop safely when it can't. Given the number of their cars going around SF lately I think they'll expand some soon too.

Try to jerk the wheel into the woods and it won't obey.

If you think this is sarcasm, it is not. That horse was clearly more reliable, adaptable and performant, not to mention safer, than anything Tesla or Wayomo is offering today.

I believe within the next few years we will see driverless long haul freight operations. Freeways are orders of magnitude easier than dynamic city streets, longer routes can be taken at little cost to avoid adverse conditions (a human rider isn't going to be ok with adding 10 hours to avoid a snow storm, a truck load of coffee beans doesn't care), and the cost of humans in this case is stupid high.

Once it is demonstrated in the real world that corporations stand to profit from eliminating drivers, you'll start to see pressure on the public sector to annotate the world. Stop signs will by law include an RF beacon, lanes will no longer be defined by paint but by transmitters in the pavement, federal law will mandate that personal vehicles transmit their location and dimensions to other nearby cars, etc.

Eventually once we have the infrastructure built, every new car will piggyback on it. Remember the Interstate Highway System was started in 1955 and completed in 1992 - progress just takes time.

If you stand or park on a railway track and get creamed, the pedestrian is going to be the target of blame.

We've come to the conclusion that the track belongs to the trains; at best the engineer can perform a limited, good-faith effort to stop and everyone knows that's not going to happen when you've got a kilometre-long, 10,000-tonne wad of physics rushing down slick metal rails at 60kph.

But if you walk into the middle of I-5 at rush hour, we still throw the legal and financial liability at drivers. Everyone is supposed to expect a rando suddenly stepping into the road and brake/steer around them. That's hard for humans and potentially harder for machines.

I could imagine a network of "autonomous only" roads which were much regulatorily much more like the rail infrastructure-- designed for minimum surprise (limited on/off ramps, limited turning points, predictable advance signing and marking, perhaps a block-control system to mitigate traffic flow) and limited recourse for pedestrians or human operators who enter the territory.

This problem has to be solved end to end. It can be done with just vision as humans can drive with just vision. It's literally just a software, machine learning and data problem. Just takes time

Because this approach has huge limitations, principally that you’re now optimizing against a cost function that isn’t the real world. RL has a place for sure, but limitations.

It’s like saying that you’d expect someone who’s played 10k hours of Call of Duty to be equivalent to a Navy Seal. They’re just really good at playing the simulation, not the real thing.

Seems like you could just get some data on that before declaring that "we're not even close". How do shipping Teslas do?

FWIW: my impression is that the things people think are hard aren't the problems that are actually hard. People here and elsewhere on the internet have spent years screaming about lidar vs. radar vs. vision. And... it turns out vision basically won. Something like half the Tesla fleet in ths US are vision only in the US now, and... the cars see stuff just fine. We're not having detection failures. It works.

If you watch all the FSD beta video being spread around youtube, much of it by drivers specifically looking for edge cases like this, most of the remaining problems are in pathing and decisionmaking, not detection. The cars see a busy intersection and then get paralyzed (there was an amusing clip from one guy of a car trying to make a left turn, giving up, and repathing a right turn that took it back in a loop only to fail at the same left turn repeatedly), or creep too slowly and annoy other drivers. Or they choose the wrong lane, or misread a multiple traffic light environment, or misread the need for detection (the one really dangerous video I remember had the car deciding to take a left turn across a broad street with a complicated blind corner instead of creeping out farther).

Those are bugs to fix, for sure. But they're not the bugs we thought we had to fix. Those bugs... got fixed.

So you can look at this as a pessimist and say "we'll never get there", or you can judge from previous experience that the hard problems won't turn out to be that hard in the end.

Personally, having been watching the progress in this space, my guess is that Tesla and Waymo (and maybe Mobileye -- no one else is close) get this basically fixed within a year or two.

At which point the debate will shift from "we'll never get there" to "we'll never be able to regulate this appropriately" or somesuch.

However, people do uses percentages metaphorically and we should try not to be so distracted by silly headlines.

Why are we ok with streets in such slapdash condition in the first place?

Yes I think self driving cars need to handle it, but I also think we aren't handling it.

Self driving cars have the potential to greatly reduce deaths due to accidents and improve accessibility for often ignored segments of our population. It is sad to see it so close, but held back by reasons like this.

Create small emergency landing areas all over...

The only ground based vehicles I care about being 99% auto would be long-haul trucking. With a station to pickup a local last-mile-human-driver for actual drop-offf etc.

But only IFF there is no external accident and no construction site.

If both would be handles truckers could sleep/nap while driving on the highways, which could have interesting effects tbh.

Handling construction sites could be made feasible.

But I have no idea how to handle accidents happening around/in-front of the truck in a good way.

Similar I would be worried about improvised marking of fresh accident sites before emergency responders arrive...

Human skill is extremely variable. A car that can drive to any road under any condition will be vastly superior to the average driver.

Reducing such a complex system to a single percentage may be silly, but the idea that a car might have partial coverage under certain conditions is quite reasonable and is reflective of how real human drivers work as well.

An unprotected left turn is probably a harder problem. They'll be expected to do it aggressively like humans, and also expected to do it safely. Those are incompatible directives.

I'm not sure how they can do better with far more stringent resources and requirements.

Not only are there different signs, different line marking & colours, & different widths. Cars are different: not all models are sold equally throughout the world. People are different: through their clothing, height and build. But the really big difference is that not everyone drives on the RHS...

The article lists left turns as a problem, whereas on a LHS road system, right hand turns will be the problem.

In NZ (a LHS system), I've heard that turning right across traffic has priority over oncoming traffic.

In Melbourne, VIC Australia (also LHS), right turns are made from the left most lane because of trams lines.

I'm sure there are loads of other issues specific to other geographies.

To me, this never ending self driving experiment screams out that the wrong solution is being pursued. (That doesn't imply that I know what they should be using as a solution)

I have yet to work with an automotive OEM that doesn't consistently mis-classify some speed limit signs in some common cases that are completely unambiguous. It leads one to wonder about the quality of classifier design and testing such that these end up in production vehicles. The cases that cause a classifier to fail are different across automotive OEMs too, it isn't intrinsic; other automotive OEMs will handle that specific case just fine.

On the other hand, when it works it often works surprisingly well. The good/bad news is that most of the problems I see are ultimately caused by poor model design and testing. These are all surmountable with better quality AI engineering.

There is more AI to self-driving cars than the classifiers that pull features out of their environmental sensors. However, the driving AIs are making decisions based on the output of those classifiers -- garbage in, garbage out.

These are the kinds of situations that will produce relentless incremental improvements over time, and there is still a lot of low-hanging fruit to improve on.

It doesn't matter how good your product is if you can't actually ship it.

Or do you have some specific definition of what qualifies as "here" that generally makes people unwilling to take this bet?

I don't know anyone from Arizona, but the Californians I've known adapted quickly.

What might make sense is limited deployment in areas where the problem can be constrained: dedicated bus routes, truck convoy lanes on an interstate, etc.

For the rest of it we should be focusing on how to get people out of cars since even BEVs pollute far more than buses, rail, bicycles, or walking.

One of the reasons tanks exist is to protect the operators. If you’re not going to have boots on the ground in the first place (autonomous tank), you can rethink the vehicle completely.

The product is being tested. Many things, including life changing drugs, are developed this way.

We both agree Waymo definitely doesn’t sell its half baked product calling it Full Self Driving before it’s ready.

And although it does occasionally have issues, it is remarkably reliable.