Still way more (no pun intended!) than Waymo, which has had 1 Waymo involved in a 6 car crash that killed someone in one of the other cars. Besides the human fatality a dog was also killed, and 5 other people were injured, some seriously. The Waymo was empty at the time.
Ironically this crash was due to a Tesla.
The Waymo and the other cars were all waiting at a red light when the Tesla rear ended them at 98 mph.
The driver of the Tesla was not impaired at the time of the crash. He says he tried to stop but the brakes were not responding.
The driver was from Hawaii, and it was later discovered that there is someone in Hawaii with the same full name, Jia Lin Zheng, with a record of around 20 traffic crimes over the last 20 years, including excessive speeding and running red lights.
I don't know if it had been determined if the Jia Lin Zheng visiting from Hawaii who caused the San Francisco crash is the same Jia Lin Zheng as the Hawaiian Jia Lin Zheng who has the long record of unsafe driving.
I'm not familiar with the naming conventions of whatever country/culture that name comes from. Is Jia Lin Zheng the kind of name that probably many people have in Hawaii or is it one that is likely rare?
That is not a useful metric for Tesla. They disengage FSD when they detect a potential accident.
Even if that were true, any accident where FSD was disengaged up to 30 seconds prior is counted as being engaged. And 30 seconds is long enough in driving that if FSD disengaged that long ago, there's no possible way any accident at that point was related to it.
source?
Autopilot shuts down when it can't handle the situation it's in. This doesn't help it "avoid blame" at all. Because Tesla considers Autopilot implicated in any crash that happened within 5 seconds from Autopilot being disengaged.
> To ensure our statistics are conservative, we count any crash in which Autopilot was deactivated within 5 seconds before impact, and we count all crashes in which the incident alert indicated an airbag or other active restraint deployed.
NHSTA's reporting requirements are even more conservative:
> Level 2 ADAS: Entities named in the General Order must report a crash if Level 2 ADAS was in use at any time within 30 seconds of the crash and the crash involved a vulnerable road user being struck or resulted in a fatality, an air bag deployment, or any individual being transported to a hospital for medical treatment.
Is it "counted" if FSD was engaged within a certain time frame prior to a crash? If so, do you know what time frame?
Or only if it was disabled automatically due to detecting a potential crash?
The latter would still be problematic, as a human driver noticing a problem just prior to the FSD disabling itself would potentially be missed (right?).
Do you know who does the counting and who makes the rules in this regard?
Asking as you seem to have more knowledge here than me.
The data is collected in all of these incidents, and most people have seen the clips of FSD avoiding otherwise potentially lethal accidents, so "They disengage FSD when they detect a potential accident" is also just patently untrue.
https://www.reuters.com/legal/government/musks-tesla-seeks-g...
Waymo publishes tons of safety metrics on their website. Here's an analysis/summary:
And the links don't even touch on things that are comparable lol. Waymo might keep all the data themselves as they own the cars, while with Teslas, the drivers can and will just grab the camera data themselves, many post it YouTube.
Why would you trust a word they say when Elon has lied out of his teeth at every single investor meeting for the last decade.
I say this as an owner of a Tesla myself.
Some of them were due to the use of cameras as opposed to LiDAR for example: The May 7, 2016 crash near Williston, Florida, in which a Tesla Model S operating with Autopilot struck the side of a tractor-trailer making a left turn across the car’s path. In this incident, both the car’s camera system and the driver did not detect the white side of the tractor-trailer against a brightly lit sky, which resulted in the Tesla passing under the trailer and causing a fatality.
I'm layman regardin this but this would have been my vote in a quizz :)
For example, in the US John Smith and Scott Baker are both typical US names, but John Smiths are way more common than Scott Bakers.
He was simply looking at his phone in reality.
I remember this incident. It happened a couple of blocks away. Unreasonable that they let him go.
And from that information alone, you can get the gist of what that data says!
(inb4 you post the accidents per mile chart which is very obviously useless and designed to mislead midwits, as it is not controlled for age of automobile or driving conditions)
Traveling south here on Land Park Dr there are two lanes, some people from the right lane veer left and the left lane veer right through the middle of the intersection. There aren’t dotted lines to help.
https://maps.app.goo.gl/?link=https://www.google.com/maps/@3...
I wonder how something like that is represented to the waymo or reasoned about.
LIDAR/LADAR based systems are not perfect, but do offer mm precision for guidance systems. SLAM based LIDAR systems can be very good, but are also not perfect when forced to guess where a platform is located.
Cheers, =3
How so? Honestly asking.-
Most guidance platforms would use LIDAR/SLAM to describe the local road surface, and overlap camera vision data to extrapolate distant surfaces and objects. Note distant objects also have lower resolution, unknown non-distinctive features (speed bump, or open man-hole cover etc.), and increasing sparse data as velocity effectively lowers world-state sampling rates.
The world-state is constantly changing at every intersection, sampling constraints add latency, and the navigation way-point goals may reach contradiction with immediate path-planning due to ambiguous/expired information.
Cheers =3
> you know a dog hidden behind a car doesn't actually vanish nor remain stationary.
Computers can do that, too. It's not that different ... guessing missing words.
I think it was two years ago that Tesla told the public that they could do that.
I suspect a Amish horse buggy is more practical. =3
Lol, really? They either developed superman x-ray vision, or just tracked object occlusion with a common re-acquisition mitigation (so worthless when physical inertia carries a vehicle into an object collision.)
>So, it doesn't "grow exponentially",
The further the object... the more possible choices will need to be made in the guidance system. Note, guidance and navigation are related, but different problem domains. Roughly, the possible choices (and errors) if I recall grew by:
((m cars) * (k lanes ) * (r occlusions) * (s sign laws) * (1 + world_sate_delta_error(t)) ) ^ (n intersections + w way-points) = 1/hype_correction
...but that doesn't even cover the projected future risk(t). =3
Using vision for driving is something that has worked for as long as cars have existed. Trying to push some "millimeter precision" solution with unproven feature set and prohibitive hardware accessibility is just asking for no real safety improvements and just more lives lost.
Cheers.
Cheers =3
In any case. Trying to argue against vision even if LIDAR hypothetically was better (it isn't) would just lead to more deaths, maybe at best shielding the rich driving in cities. FSD's stats don't lie :|
Many high-end multi-beam lidar also embed things like basic Bicycle and Pedestrian object detection in the sensor front end. Things have improved significantly with sensors, but the risk is never 0.
The rate of death doesn't really override an expectation of product safety, and humans understanding other humans intent.
Have a wonderful day =3
Trying to claim some entirely different stack in some third party LIDAR tower's own processing is somehow "beneficial" sounds like a project manager who thinks adding engineers equates to linearly faster progress.
Just no. On a slight tangent though, I recommend reading about Tesla's vertical integration. It's not something any other company has managed to get implemented so deep in automotive, which makes it quite incomparable in some aspects where others can't adapt even if they wanted to.
Let me know if you have trouble finding the projects. =3
It might make you headstrong in believing against something that'd be easier to see the core sensibility of if you weren't so invested in just a specific corner/angle though.
I've avoided working a work project involving LIDAR scanning before, even back then the hellishness of the hardware was a large factor. I wouldn't mind playing around with a Jetson Nano though.
That is why I don't really like ROS. lol =3
>doesn't make you better evaluating how a vision-only ML model
In general, the monocular SLAM algorithms rely on salient feature extraction, and several calibrated assumptions about the camera platform. How you interpret that output is another set of issues, as the power budget is going to take the hit.
For machine vision, I'd skip the proprietary Jetson Nano... and get a cheap gaming "parts" laptop with a broken LCD and several USB ports (RTX4090 or RTX4080 is a trophy.)
No one wants to fork over $30k for an outdoor lidar, but using only cameras is a fools errand. The best platforms I've seen commercially use camera + lidar + radar.
For student projects, one can get small radars and TOF sensors for under $20 off sparkfun (similar to the one in iPhone Pro 11/12/13). We live in the future... =3
Also, vision-only systems work great… if they’re backed by strong intelligence.
>fun fact: most car accidents do not happen in places where FSD is commonly used
How is that even supposed to in any way be relevant when talking exactly about cases where FSD and similar are used. Sigh.
>Also, vision-only systems work great… if they’re backed by strong intelligence.
Yes. And I do recognize that "Best, with custom in-house NN hw" might not still be "Strong" on all aspiratory statistics. But its already much above human capability, and regardless if you want to try to say the stats are 2x 3x, even 4x exaggerated, they'd still blow the alternative safety standard out of the water.
And now you link that debunked Mark Rober video that literally doesn't even have FSD turned on, while giving the most ridiculous free wins to LIDAR. Talk about writing the tests for the exact limits of a specific system. https://www.youtube.com/watch?v=QhX_fgekpk0
You're really running out of steam :D
https://www.cnn.com/2025/01/07/business/nhtsa-tesla-smart-su...
Best of luck =3
And one fatality with the most dangerous general form of transportation we have?
And an article about a fancy pants 5 miles a hour park retrieval feature bending a few posts as if it was relevant?
Dude I don't need luck, I could roll ten D12 ones in a row and win
I'd rather not have drivers playing dice while driving. =3
ok
more at 5
You do not have the data necessary[0] to substantiate this claim.
[0] Accidents per mile controlled for at least vintage of car and driving conditions
[0] https://insideevs.com/news/720730/tesla-autopilot-crash-data...
2. Autopilot, being a typical ASAD, is used exclusively on highways and in conditions where typical ASADs work reliably
Weird to brag about being unwilling to apply even first order criticality to a press release but you do you.
Thank you for reaffirming that in fact you do not have the data required to substantiate your claim.
By the way, it’s a “binocular” system. “Bicameral” refers to a design for institutions like legislatures.
for waymo itself, you can overfit on 100% of the situations that will be encountered. 49 square miles isnt that large. its the real world outside that which im concerned about its efficacy in. i think if you put a waymo in a small town that no alphabet engineer has ever even heard of, then youll see it fail badly as well.
FSD is a reinforcement learning problem, and we have no good way of training non-simulation algos for that. and a real dynamical driving environment cant be simulated accurately enough
Which is why it is a non-goal for Waymo. It should be a non-goal for Tesla too, given the state of the art.
This could very well be true, but if you’re looking at it from a perspective of someone who lives in a rural area with real winters, for driving purposes, those all look like pretty much equivalent large American cities without a winter.
Waymo is not claiming to work in small towns.
Tesla is. Soon™.
My FSD (v13.2) has driven unmapped roads, including gravel roads, hills, narrow roads, and switchbacks, in the backwoods of Tennessee. From watching the display, it clearly identifies the road features and navigates them.
FYI. FSD is safer than human drivers on large datasets. Accidents cause deaths of thousands every year. Arguing against FSD for "safety" has The Grim Reaper cackling.
Waymo is SLS compared to Starship. So, not comparable and could never fit the shoes Robotaxi has been planned to fill since the initiation of the FSD project. I.E. SLS = a few academic missions. Starship: Mars colony. Waymo is as good for safety as doing nothing with its inability to scale.
Waymo costs as much per ride as one with a driver. Robotaxi is technologically fundamentally close to starting its shift after you arrive home and get out of your car. Earning you part of the profit btw. And with no growing pains, with FSD working on novel, untested roads.
Mapping is expensive, but not really in a per-mile-driven basis. There are 4M miles of public roads which get over 3.2T miles of total driving, or ~800k vehicle-miles per road-mile. You could have pretty high mapping costs per mile and still have very low per-mile-traveled costs for mapping. And there's every reason to think the cost of mapping and updating maps on a per-road-mile basis will go down over time, not up.
Waymo is scaling pretty rapidly, and the rate of expansion is accelerating. They've been proving out the technology, and are only now starting to commission special purpose vehicles as they move out of the research phase and into deployment.
Perhaps Tesla will catch up, but for now we know Waymo's are at least ~6x safer than humans in diverse independent conditions, while FSD according to publicly available information is 50-100x less safe (with critical interventions every few hundred miles).
>Growing pains
Robotaxi has been in testing for less than like 1/50 the time Waymo has been out, and has already once surpassed coverage in their starting city.
You know who also had growing pains? Hulk. Growing that quick.
Elon can literally draw and balls a dick on top of Waymo's long-amassed support area. Even if they want to check these starting areas a bit better with some basic mapping setups in advance, it's obvious their stack isn't hindered by requirement of hard, slow HD mapping and cars that look like they're growing mushrooms with the ugly LIDAR sensors on them.