Welcome to Tesla Motors Club
Discuss Tesla's Model S, Model 3, Model X, Model Y, Cybertruck, Roadster and More.
Register

Autonomous Car Progress

This site may earn commission on affiliate links.
There is a lot of AV-centered attention for cars operating within a complex environment such as inner city traffic. But you can also start by looking at the environment firstly. Toyota is sort of looking through the cracks of FSD, and is building a 'woven city', reportedly to test AVs, but IMO it all feels more like a sort of grid control.

"For the full adoption of autonomous cars, cities need to be fully wired to funnel massive amounts of data to the vehicles. Sensors and cameras scattered throughout roads, traffic lights, and buildings can supply that data to cars, including everything from weather patterns to cyclist behaviors. Once autonomous cars have that data, they can process it and use it to safely navigate the city. Right now, modern-day cities aren't set up this way – and that's why Toyota is building its sensor-laden Woven City from the ground up."
 
The problem with such a test is that "gaming" the test would almost certainly be rampant unless the test had sufficient variability to stop makers hard-wiring knowledge of the test as a special-case into the car (think how computer makers try to rig benchmark test results in various dubious ways). And if its not standardized then you are open to all sorts of accusations of favoritism. Not saying I'm against the idea, it makes a lot of sense .. it's just going to be tough to get it right (and fair).

The good news is that we do know WHAT we want to test for. Agencies like SAE and NHTSA have put together a list of elemental behavior competencies:
  • Maintain a lane
  • Changing lanes
  • Navigating intersections
  • Navigating unstructured roadways, entering/exiting unstructured roadways
  • Navigating pick-up and drop off zones and parking structures
  • Responding to vulnerable road users
  • Responding to other vehicles
  • Responding to special purpose vehicles (ie emergency vehicles etc)
  • Responding to lane obstructions and obstacles (static, dynamic, including animals)
  • Responding to confined road structures (tunnels, bridges, parking garages etc)
  • Responding to work zones (including workers)
  • Responding to DDT performance relevant system failures
  • Responding to relevant dynamic traffic signs and signals
So the question becomes HOW do we test for these competencies. I don't think it would be too difficult to devise a set of scenarios that test all these competencies. But you are right that ensuring that the tests are right and fair could be tricky. we could construct those "fake cities", with intersections, construction areas, parking lots, fake pedestrians that pop out, cars that cut in etc... and have the AVs complete a random route through the fake city. I would also propose doing the test on different days to cover good weather and bad weather. You could even create fake fog to test for that as well. Obviously, AV companies could still try to adjust their system to pass the test. I would suggest that AVs would need to complete this test without premapping so that they can't just premap the course and pass it that way. Companies could still use HD maps to improve performance in the real world when they deploy but this would test that the AVs have the basic competencies if there was no HD map. Since everyone would take the test in the same "fake city", I think that would ensure fairness. To address the issue of just rigging the system to pass the test, I think there would need to be other parts of the validation process. Just taking an AV driving test would not be enough IMO.

I propose a 3 step process the get certification for deploying an AV:

Step 1: Documentation
The AV company would need to provide documentation on how their AV works, how it was built, what processes were used to develop and test the AV, what redundancies exist for critical safety issues, what the ODD is, what processes exists to enforce the ODD, and what processes exist after deployment to quickly fix an issue. The last part is key because AV accidents will inevitably happen no matter what. So it is important to have a "recall" process in place to quickly address and fix a problem. The purpose of this step would be to ensure that regulators are knowledgeable about how the AV works, provide evidence that the AV company did their due diligence in building and testing their AV and give regulators an opportunity to provide feedback if regulators feel that the AV company missed something critical.

Step 2: Testing behavior competencies
This would be the on-road test that I talked about above that would test for basic driving competencies. This purpose of this step would be to make sure that the AV has the basic driving skills needed.

Step 3: Safety Data
In this final step, the AV company would need to show safety data from x million of miles of autonomous driving with a safety driver in the ODD that they want to deploy in that shows the overall safety is good enough. The data would need to meet some criteria of x safety critical failures per million miles. Safety critical failures would be actual accidents + near misses that almost resulted in a collision. The purpose of this final step would be show overall safety is good enough.

I think if we did all 3 steps that would be good enough to certify AVs for deployment. All three steps could be standardized to ensure fairness. And all three steps together would provide a more complete validation process. Step 1 ensures the company meets the requirements in developing the AV, step 2 tests for basic driving skills, and step 3 checks for overall safety with statistically significant data. Again, this would not guarantee that AVs never crash but I think it would set the bar high enough that the public could trust AVs.
 
Last edited:
No standardization in sight. How is the NHTSA supposed to deal with this? Trial and error, hope for the best, take in consideration failures will happen. The one UBER got into in Arizona, caused the company to halt all testing and sell the AV division to Aurora. What's a learning curve gonna be? I already made the comparison with different mobile operating systems. But with smartphones we don't risk human lives. Any chance that one system will prevail? What does it mean that one system will let's say score 99% on the 'Turing test for AVs' and other 97%. Does that mean that others may have to comply?

Uber%2BVolvo.jpg
 
No standardization in sight. How is the NHTSA supposed to deal with this? Trial and error, hope for the best, take in consideration failures will happen. The one UBER got into in Arizona, caused the company to halt all testing and sell the AV division to Aurora. What's a learning curve gonna be? I already made the comparison with different mobile operating systems. But with smartphones we don't risk human lives. Any chance that one system will prevail? What does it mean that one system will let's say score 99% on the 'Turing test for AVs' and other 97%. Does that mean that others may have to comply?

Uber%2BVolvo.jpg
The Uber collision was a test vehicle with a safety driver so that's an issue with AV testing not deployment.
The NHTSA is letting the states regulate AVs for now. I think the only way to test AVs is to drive many millions of miles with a safety driver and then try to extrapolate the severe accident rate from that. That's what Waymo did in Chandler, AZ in order to deploy robotaxis there (here's the report:https://storage.googleapis.com/sdc-...Waymo-Public-Road-Safety-Performance-Data.pdf)
For example Tesla has about 20,000 FSD beta testers. If each of them drive 5,000 miles using the system they can cover 100 million miles. Tesla can then look at every disengagement and simulate the counterfactual to see if a collision would have occurred. If the collision data meets their goal of 2-3x the safety of the average human driver they can allow the system to be used without a driver.
 
The Uber collision was a test vehicle with a safety driver so that's an issue with AV testing not deployment.
The NHTSA is letting the states regulate AVs for now. I think the only way to test AVs is to drive many millions of miles with a safety driver and then try to extrapolate the severe accident rate from that. That's what Waymo did in Chandler, AZ in order to deploy robotaxis there (here's the report:https://storage.googleapis.com/sdc-...Waymo-Public-Road-Safety-Performance-Data.pdf)
For example Tesla has about 20,000 FSD beta testers. If each of them drive 5,000 miles using the system they can cover 100 million miles. Tesla can then look at every disengagement and simulate the counterfactual to see if a collision would have occurred. If the collision data meets their goal of 2-3x the safety of the average human driver they can allow the system to be used without a driver.
I am doing my best with my two FSD Beta cars to help rack up those 100 million miles of data! It would be interesting to know whether any of my data is actually used. I still punch the camera icon every time the car performs incorrectly — and that basically means several occasions almost every time I take a drive — but stopped sending audio clips.

Many of my disengagements are preventative as I learn where the car really fumbles the ball. Obviously that doesn’t help Tesla but my safety and my car’s pristine sheet metal matter more to me than my testing contribution to Tesla.

I know it is popular to bash Tesla’s progress to full autonomy, but I am actually somewhat optimistic. As an early FSD purchaser (12/2016 S) it was annoying to wait almost five years to even be a beta tester when the sales pitch in 2016 suggested FSD would be doing great things within a year if only regulators allowed it! That was a joke but I do see a lot to be optimistic about. Yet I too wonder if the current vision solution will ever be sufficient in bad weather and to handle certain everyday challenges, especially unprotected lefts. My cars are both on 10.8.1 and still scared to death to make a smooth unprotected turn.

I have no technical background but really enjoy reading the opinions of those of you who obviously have a technical understanding of the challenges and achievements!
 
Last edited:
  • Informative
  • Like
Reactions: daktari and voyager
I am doing my best with my two FSD Beta cars to help rack up those 100 million miles of data! It would be interesting to know whether any of my data is actually used. I still punch the camera icon every time the car performs incorrectly — and that basically means several occasions almost every time I take a drive — but stopped sending audio clips.

FWIW, you never sent audio clips.

The "bug report" voice command doesn't go anywhere. it sets a local bookmark in the log files for use by a service center if you open a service ticket with them. Otherwise nobody ever sees it and it doesn't leave the car.

The FSDBeta camera icon reports DO get sent to Tesla though.
 
For example Tesla has about 20,000 FSD beta testers. If each of them drive 5,000 miles using the system they can cover 100 million miles. Tesla can then look at every disengagement and simulate the counterfactual to see if a collision would have occurred.
I very much doubt testers will reach 5000 miles each, more like 500 (I suspect many testers played with FSD as a toy and then stopped using it). However, even 10 millions miles is a respectable dataset.

The problem here is its very hard to judge the counterfactual, since you have to essentially speculate about what would have happened had the car behaved differently .. and any other cars involved also behaved differently. No doubt in some cases this is easy, but when you get FSD in the Tesla and a human in another car, figuring out alternatives is very tricky indeed.

In fact, this is an intrinsic problem in all accident avoidance/mitigation systems. By definition, if the system is working well, the only indication you have is that, over some statistically large enough sample set, you can show that the accident rate+severity is reduced. This is why, like it or not, claims that stuff like FSD beta should be much more restricted until it is "safe" are meaningless, because you cannot know if it is safe until it is deployed on a reasonably large scale. (Very much like drug testing, which, at the end of the day, has to be tested on humans.)
 
I very much doubt testers will reach 5000 miles each, more like 500 (I suspect many testers played with FSD as a toy and then stopped using it). However, even 10 millions miles is a respectable dataset.

The problem here is its very hard to judge the counterfactual, since you have to essentially speculate about what would have happened had the car behaved differently .. and any other cars involved also behaved differently. No doubt in some cases this is easy, but when you get FSD in the Tesla and a human in another car, figuring out alternatives is very tricky indeed.

In fact, this is an intrinsic problem in all accident avoidance/mitigation systems. By definition, if the system is working well, the only indication you have is that, over some statistically large enough sample set, you can show that the accident rate+severity is reduced. This is why, like it or not, claims that stuff like FSD beta should be much more restricted until it is "safe" are meaningless, because you cannot know if it is safe until it is deployed on a reasonably large scale. (Very much like drug testing, which, at the end of the day, has to be tested on humans.)
I suspect it's not as hard as you think to determine counterfactuals. You don't really have to speculate what the car itself would do because you have the exact state of the software and all the sensor inputs at the time of disengagement. I agree that predicting what other drivers will do in response to counterfactual actions is tricky but I'm guessing that safety disengagements happen a very short time before potential or real collisions so the range of possibilities isn't that high. You can take the situation and simulate all plausible actions by the other drivers and make sure your system behaves optimally for all of them.
You can read more about this in Waymo's safety analysis (https://storage.googleapis.com/sdc-...Waymo-Public-Road-Safety-Performance-Data.pdf)

Ultimately you do have to get rid of safety driver and see what happens but FSD Beta is pretty far from that point.
The safety of FSD Beta has almost nothing to do with the performance of the system itself, it's mostly about how human interact with it. FSD Beta getting more advanced could very well make it less safe if humans don't monitor it as carefully.
 
These companies have been saying for a few years now that autonomous vehicles will end car ownership. It will wisk you away while you sleep. You will be able to do work while the car drives you around. Tesla is the only company that drivers can see how well the car operates in all kinds of weather and even then it messes up. Even a vehicle that is level 4 may find itself having to operate in level 5 conditions for a while.
 
  • Funny
Reactions: Daniel in SD
Even a vehicle that is level 4 may find itself having to operate in level 5 conditions for a while.

No. By definition, L4 is not allowed to operate outside its ODD. So it is not possible for L4 to operate in "L5 conditions". L4 will pull over and wait for the driver to take over if it encounters conditions outside its ODD.
 
  • Like
Reactions: S4WRXTTCS
No. By definition, L4 is not allowed to operate outside its ODD. So it is not possible for L4 to operate in "L5 conditions". L4 will pull over and wait for the driver to take over if it encounters conditions outside its ODD.

By definition this is correct, but what I wonder what real life will look like.

Pulling over on the freeway is really, really unsafe for passengers along with other vehicles on the road. There are too many people who don't pay attention while driving, and hit stopped vehicles on the side of the road.

I think we'll see two ODD's.

One ODD is an engagement ODD, and one ODD is the disengagement ODD.

That engagement ODD always looks at where you're going, and the expected weather on the route.

The disengagement ODD is where it determines that it needs to find a spot to get off the road.

Where the engagement ODD is more restrictive than the disengagement ODD.

This is one of the reasons why I think we need more partnership between governments, and autonomous vehicle companies to come up with better strategies on how to handle autonomous cars. Things like adding safe pull out points where there is some protection offered to passengers in the vehicle while the issue is being resolved by fleet management.
 
These companies have been saying for a few years now that autonomous vehicles will end car ownership. It will wisk you away while you sleep. You will be able to do work while the car drives you around. Tesla is the only company that drivers can see how well the car operates in all kinds of weather and even then it messes up. Even a vehicle that is level 4 may find itself having to operate in level 5 conditions for a while.
It won't end it, but it definitely will erode it in metro locations where L4 fleet vehicles are operational.

In a way it will be like EV's where in the beginning an EV allowed a two ICE car family to switch one of them to EV. Only it will be switched with an autonomous subscription.

Where families will do the math on it, and they'll see that it will cost less and offer more.

The neat thing about any L4 vehicle is when they mess up it will likely happen while you're not in the car. That it will be statistically unlikely, and each time it messes up the statistical likelihood of it happening again goes down as things are improved. In fact during the beginning phases you don't even want to own the vehicle because of the constant need to change things at some level (SW/HW/Infrastructure/regulatory).

We're a long way away from sleeping in an L4 vehicle unless it's some quick nap for a city dweller to go from one side of the city to the other in a fleet vehicle.

Fleet vehicle companies will have to provide solutions for people that want different things. I'll probably pay for a higher offering as I want an experience that's more like an ownership experience. Where I can do things like leaving my belongings in the car while I go about my business in the city. I want a nice clean vehicle and not one messed up by some idiot. Obviously I would by my own if that was an option, but I don't see that being an option other than the make believe Tesla one.
 
By definition this is correct, but what I wonder what real life will look like.

Pulling over on the freeway is really, really unsafe for passengers along with other vehicles on the road. There are too many people who don't pay attention while driving, and hit stopped vehicles on the side of the road.

I think we'll see two ODD's.

One ODD is an engagement ODD, and one ODD is the disengagement ODD.

That engagement ODD always looks at where you're going, and the expected weather on the route.

The disengagement ODD is where it determines that it needs to find a spot to get off the road.

Where the engagement ODD is more restrictive than the disengagement ODD.

This is one of the reasons why I think we need more partnership between governments, and autonomous vehicle companies to come up with better strategies on how to handle autonomous cars. Things like adding safe pull out points where there is some protection offered to passengers in the vehicle while the issue is being resolved by fleet management.

I don't think 2 ODDs are necessary. Instead, I think AVs will have 1 ODD but developers will basically do 3 things to minimize unsafe pull-overs:
1) Restrict the ODD to try to exclude problems the AV might have. So if the AV can't handle something, you try to design the ODD to exclude that thing. For example, if your AV is not very good on highways, don't let it drive on highways. That way, the AV won't operate in conditions that are known to cause the AV to pull over a lot. This will reduce the number of pull-overs.
2) Design your autonomous driving to be as reliable as possible inside the ODD to minimize situations where it would need to pull over inside the ODD. You do this by solving edge cases inside the ODD to make your autonomous driving as reliable as possible.
3) You try to design the autonomous driving to know when a pullover would be unsafe and to pull over only when it is safe to do so. This way, in those (hopefully) rare instances where the AV does need to pull over, it does it as safely as possible.

If you look at AVs like Waymo and Cruise, I think that is what we are seeing. That is why they geofence their AVs and working to make their AVs as reliable as possible. And they only deploy their robotaxis in geofenced areas when they are confident the AVs are reliable enough. It's why companies like Waymo and Cruise are taking a lot of time to deploy their AVs.
 
Last edited:
I suspect it's not as hard as you think to determine counterfactuals. You don't really have to speculate what the car itself would do because you have the exact state of the software and all the sensor inputs at the time of disengagement. I agree that predicting what other drivers will do in response to counterfactual actions is tricky but I'm guessing that safety disengagements happen a very short time before potential or real collisions so the range of possibilities isn't that high. You can take the situation and simulate all plausible actions by the other drivers and make sure your system behaves optimally for all of them.
You can read more about this in Waymo's safety analysis (https://storage.googleapis.com/sdc-...Waymo-Public-Road-Safety-Performance-Data.pdf)

Ultimately you do have to get rid of safety driver and see what happens but FSD Beta is pretty far from that point.
The safety of FSD Beta has almost nothing to do with the performance of the system itself, it's mostly about how human interact with it. FSD Beta getting more advanced could very well make it less safe if humans don't monitor it as carefully.

As FSD Beta gets better it absolutely will get more dangerous before it gets less dangerous. The usage will go up, and trust in it will go up. But, there will still be a lot of cases for mistakes to happen.

One thing I've seen time and time again with FSD Beta is my safety threshold is one thing, and the cars is different.

Too close to the curb = disengagement, but the teenager (the cars computer) is probably telling me "it was fine".
Too fast in a residential area = disengagement, but the teenager is telling me "you told me to go the speed limit" and has no understanding that I want to do 5 under in tight residential areas.
Too slow during a maneuver = take over, but the elder (the cars computer) is telling me to have patience for its old bones.

There is so much of this it's really impossible to test it in any meaningful way. It's like a very preliminary beginning you don't have much to work with as much of it doesn't work.

If someone is behind me I don't bother testing it as its usually too slow to do anything.
 
  • Like
Reactions: Doggydogworld
By definition this is correct, but what I wonder what real life will look like.

Pulling over on the freeway is really, really unsafe for passengers along with other vehicles on the road. There are too many people who don't pay attention while driving, and hit stopped vehicles on the side of the road.

I think we'll see two ODD's.

One ODD is an engagement ODD, and one ODD is the disengagement ODD.

That engagement ODD always looks at where you're going, and the expected weather on the route.

The disengagement ODD is where it determines that it needs to find a spot to get off the road.

Where the engagement ODD is more restrictive than the disengagement ODD.

This is one of the reasons why I think we need more partnership between governments, and autonomous vehicle companies to come up with better strategies on how to handle autonomous cars. Things like adding safe pull out points where there is some protection offered to passengers in the vehicle while the issue is being resolved by fleet management.
Note even pulling to a stop in a traffic lane is an acceptable fallback according to SAE, and pulling into the side is definitely considered acceptable (in the same way it is when a human is driving). I don't think there will be a different engagement or disengagement ODD. Weather predictions unfortunately may not be reliable (as many found out this winter), so the car still needs to be designed to disengage "safely" when things fall out of ODD.
 
Last edited: