The system is absolutely AI based today. There is no hardcoding like this. Hardware 3 in Tesla cars is an ASIC meant to run neural nets (https://en.wikipedia.org/wiki/Tesla_Autopilot#Hardware_3). Why are you so confidently stating things you don't know about?
At this level, the car can act autonomously but requires the driver to be prepared to take control at a moment's notice.[103][104] HW1 is suitable only on limited-access highways, and sometimes will fail to detect lane markings and disengage itself. In urban driving the system will not read traffic signals or obey stop signs. This system also does not detect pedestrians or cyclists,[105] and while AP1 detects motorcycles,[106] there has been two instances of AP rear-ending motorcycles.[107]
Because each individual car is not truly autonomous when it comes to learning and improving diving based on it's specific geo location. I am not talking specifically about Tesla, this goes for all automated cars...
We have to be able to admit that we aren't ready to launch thousands of these cars out on streets at this point. They have NOT been perfect.
There are tons of issues beyond just the quality of the AI. Software development and updates, vehicle maintenance, planned obsolescence of models, Legality, ethics, ownership... tons of other issues not hashed out. The combination of all of those issues makes autonomous vehicles near impossible any time soon, unless we ALL want to give up our right to own personal property and submit our safety to being test subjects. I'm not willing to do that at this point as a development manager myself.
I'm not really sure what the hardware link you provided has to do with anything but plenty of rule-based heuristics are used in state of the art autonomous driving systems. Machine learning systems have taken over the image processing and classification parts, semantic segmentation, object recognition and so on but traffic rules or emergency behaviour or hard speed limits are not learned.
the OP is wrong though in somehow classifying this as 'not AI'. Just because ML has become an important part of the equation doesn't mean we have thrown control theory and logical constraints out of the window.
The current AI is running rudimentary calculations based on what is truly required for flawless operation... The type of processing that is necessary to operate like a GOOD human driver is nowhere near what currently exists... Sure there are bad drivers out there, and that's why autonomous vehicles would need to be EXCEPTIONALLY good... Not just good enough for a few demos on youtube.
If a company's test cycles were good enough to warrant reliability and safety promises, the window on the CyberTruck would have never broken.... This is how companies work, they over promise and under-deliver, this time it affects everyone's safety, including safety of those who don't buy them.
I'm not saying the strides aren't impressive, I'm saying I wouldn't feel safe having this experimental technology forced upon me knowing the potential for historically complex human factors.
At this level, the car can act autonomously but requires the driver to be prepared to take control at a moment's notice.[103][104] HW1 is suitable only on limited-access highways, and sometimes will fail to detect lane markings and disengage itself. In urban driving the system will not read traffic signals or obey stop signs. This system also does not detect pedestrians or cyclists,[105] and while AP1 detects motorcycles,[106] there has been two instances of AP rear-ending motorcycles.[107]
https://en.wikipedia.org/wiki/Tesla_Autopilot#Hardware_3