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