[simion314]

There are systems that can detect stationary objects, Tesla does not want to use those more reliable systems, so they use the programming methodology of tweaking tweaking the code when a bug appears and hope that was the last one.

Sure some AI gurus will claim that humans can detect this objects only with 2 eyes but they forget to mention that behind those 2 eyes is a brain an actual intelligence that is aware of the world and it's place in the world. So if you can't create an actual intelligence then at least put the effort in feeding correct data into your AI and remove the line of code "if static object ignore because too hard to detect if is a truck or a shadow/paper bag/sign"

[SerLava]

Yeah they want a low unit cost on the camera system, so they are trying to machine learn their way out of the problem. It's not going to work.

A self driving system needs to have a 3d understanding of it's environment. It's not acceptable to crash into paintings by Wile E. Coyote.

[simion314]

From what I understand there is also some code that is there to ignore static objects because maybe are signs or bridges and the AI is too stupid. So you have bad sensors with bad code combo.

[SerLava]

Yeah it's essentially impossible for the system to be good- the limitations force other limitations.

[amelius]

> tweaking the code when a bug appears and hope that was the last one

Tesla should also be prohibited from pushing updates. When the software is updated, the code should be tested for at least X thousand miles and X months before a new version may be pushed. Letting an authority do the pushing avoids the temptation of manufacturers to push updates prematurely. It also solves the problem of unexpected changes for the user at random times.

If safety issues are detected, the automobile (or at least the autopilot) should be disabled until the code has been fixed and fully tested.

[nilstycho]

> There are systems that can detect stationary objects, Tesla does not want to use those more reliable systems

What systems are you referring to? Lidar and radar systems can't reliably detect stationary objects as hazards, because most of the world is stationary and consequently gets filtered out.

[simion314]

Filtering out is the problem that develoeprs/engineers should solve right? I can't accept the idea that the car can hit a wall because "our devs are too incompetent or we are to cheap to use better hardware" , a wall or a truck does not look like a bridge or a shadow or a sign, if the AI is too stupid then is not ready, even if is better then a drunk teen that drives a 15 years old car in some very specific situations.

The lidar/radar detects the objects the AI should label them and decide, if it can't do it then throw more video cards at it and more training or find some competent people that could use more deterministic code to reduce the complexity before the AI attempts to run.

[cptskippy]

The problem is with the sensors, not the AI, and occurs across the industry and isn't exclusive to Tesla. Volvo's Pilot Assist has the same short comings.

https://www.wired.com/story/tesla-autopilot-why-crash-radar/

[simion314]

From my reading of your link you are wrong.

How a code that decides what to ignore or not is a sensor issue? Sensors tell you that there is something in front, sure maybe is a sudden thing and there is no velocity/acceleration vector for a few moments but the object is detected ...the software DECIDES what to ignore.

The example where a car changes slane and the code ignores any static object in front of that car seems a clear case of a crash waiting to happen, the car in front might change the lane to avoid something. (and the fact that some other tech that is honestly labeled lane assist has this issue does not excuse a self claimed autopilot to have same flaws."

Let me summarize and let me know where I am wrong:

"Because the software is bad and it triggers too many false positives the coders added a "clever" hack , we ignore most static objects."

[cptskippy]

> How a code that decides what to ignore or not is a sensor issue?

I guess "Sensor Module" would be a more accurate description.

Most automotive systems are designed as a series of modules that function independently but jointly form a system. They either broadcast or consume messages over the CAN BUS.

The Volvo V60 for example has a Forward Sensor Module, the radar, which outputs a handful parameters like Primary Target Range, Voltage, and Automatic Alignment Offset. It's the responsibility of other body modules to consume that data. The Closing Velocity Module might then broadcast Acceleration related messages which intern would be picked up by the Adaptive Cruise Control Module. Or it might broadcast Collision Warning Messages which the Stereo Module reads and responds by blaring a warning noise out the speakers and also the Brake Control Module receives and applies the brakes.

[nilstycho]

Yes, in principle there are systems that could detect stationary hazards. But as far as I'm aware the best lidar and radar approaches are currently no better than Tesla's RGB approach. It seems that the AI is much more important than the sensor.

[simion314]

The sensors could detect a solid object, the issue seems to be that the sensors will detect many things and the AI or the hardware is incapable to handle the amount of sensors data.

Though the Google car seems to have strong enough hardware to keep track of many vehicles and objects at a big enough distance to not be surprised if something appears or disappears for a frame.

Not sure what people want for a sensor, to detect and label the objects for you? or calculate velocities and predict the future? That seems to be the software developers job but you might need competent people and not throwing big data into a black box and retrain until it mostly works.

[camjohnson26]

No Waymo car has crashed into an emergency vehicle yet.

[nilstycho]

Waymo has driven 20 million miles. Autopilot has driven (about) 4 billion miles.