I get what you’re referencing (lack of radar, lidar etc.), but objectively a camera is a sensor in the exact same way as the others, that’s not even up for discussion.
It’s a sensor relying on image recognition, which is only as reliable as the image recognition software. The more clever software tries to be, the more potential failure states that exist.
Yes that is true all sensor input is only as good as the algorithm interpreting it. But that doesn’t change the fact that a camera is just as much a sensor as a lidar or radar, which is what I stated.
Yes, a camera is technically a sensor. Just not one that can tell you a distance to an object. And that capability is pretty useful to not have a car drive through a solid garage door.
It is possible, but it is not error-free. For example, there is no way to tell a distance to a featureless wall that takes up the entire field of vision.
But Teslas don’t even have stereoscopic vision. The moment you start using neural networks and monoscopic vision, you get affected by all the visual illusions that humans get. And that is in addition to the system not being as good as humans at processing visual information.
To have steroscopic vision you need two cameras with the same optics. Tesla has three front facing cameras, each with a different field of view. And they are too close together.
But they never claimed to have stereo vision. You don’t need that on the road - all the cars are roughly the same size, so it is easy to “guess” the distance to them.
I just wouldn’t trust it with anything when off the road.
Which was all I stated, but somehow people disagree with facts here.
Edit: and you actually easily can measure distance quite accurately with cameras in a stereoscopic setup, but of course this is not what Tesla does, despite having several forward-facing cameras.
No it adds precision and accuracy to the words used. These things matter when it comes to forming specific meanings in a purely text-based environment where people share little (or none at all) common understanding or biases.
In your initial response, you acknowledged that you understood what was meant by “sensors” in the context of the comment, but then the rest of your response was dismissive in tone, and implied that you believe their statement to be incorrect despite your previous acknowledgement. Your follow-up responses are doubling-down on this.
As others have pointed out, arguing about the canonical definition of the word “sensor” is not adding anything to the discussion around the potential cause of the collision.
The ones with actual sensors can, anyway.
They still have ultrasound sensors for slow speeds like parking. Either they failed or he was at roadway speed when he entered the driveway.
I get what you’re referencing (lack of radar, lidar etc.), but objectively a camera is a sensor in the exact same way as the others, that’s not even up for discussion.
It’s a sensor relying on image recognition, which is only as reliable as the image recognition software. The more clever software tries to be, the more potential failure states that exist.
Yes that is true all sensor input is only as good as the algorithm interpreting it. But that doesn’t change the fact that a camera is just as much a sensor as a lidar or radar, which is what I stated.
Yes, a camera is technically a sensor. Just not one that can tell you a distance to an object. And that capability is pretty useful to not have a car drive through a solid garage door.
You can absolutely tell the distance to an object with cameras if you use more than one. Our eyes do it all the time.
It is possible, but it is not error-free. For example, there is no way to tell a distance to a featureless wall that takes up the entire field of vision. But Teslas don’t even have stereoscopic vision. The moment you start using neural networks and monoscopic vision, you get affected by all the visual illusions that humans get. And that is in addition to the system not being as good as humans at processing visual information.
They actually have three cameras in the main front-facing unit as of 2020. Before that, I believe they did still have 2.
To have steroscopic vision you need two cameras with the same optics. Tesla has three front facing cameras, each with a different field of view. And they are too close together. But they never claimed to have stereo vision. You don’t need that on the road - all the cars are roughly the same size, so it is easy to “guess” the distance to them. I just wouldn’t trust it with anything when off the road.
Which was all I stated, but somehow people disagree with facts here.
Edit: and you actually easily can measure distance quite accurately with cameras in a stereoscopic setup, but of course this is not what Tesla does, despite having several forward-facing cameras.
It’s because it adds nothing to the discussion.
No it adds precision and accuracy to the words used. These things matter when it comes to forming specific meanings in a purely text-based environment where people share little (or none at all) common understanding or biases.
In your initial response, you acknowledged that you understood what was meant by “sensors” in the context of the comment, but then the rest of your response was dismissive in tone, and implied that you believe their statement to be incorrect despite your previous acknowledgement. Your follow-up responses are doubling-down on this.
As others have pointed out, arguing about the canonical definition of the word “sensor” is not adding anything to the discussion around the potential cause of the collision.
My read was “The ones with actually good sensors can, anyway.”
(good for the purpose)
Nice to be technically correct, but of course (best kind of correct!)
edit: elaborated