Earlier quoted context omitted.
> Reliance on HD Mapping gets you to "robotaxis" quicker and easier, but it doesn't and likely cannot scale. If you can make the unit economics work for a large quantity of individual cars, mapping is a small fixed cost. I agree that it's not economical to map every city and road in the US, since you need to generate revenue from every mapped road and city. So you can think of HD maps as amounting to building roads.…
> That's simply untrue. All the hard stuff continues to be reliability and sensor gated. IR and thermal sensing are unnecessary if the bar is human level and neither is the lidar. The point is overused, but humans rely on two eyes in the driver seat. I don't see any evidence to suggest the modern model that Tesla has developed for their vision system is their limiting factor in the slightest to reach L4/L5. Dogs jump…
For one, frame rate and processing rate on human eyes is way higher than cameras. Dynamic range is another. Also, Cruise and Waymo are some of the only companies that have hard internal data / ability to simulate how well their safety drivers do, and in the very same scenario what their software driver will do. Without LiDAR you can't build that simulation, and once you have that data if you continue to use HD Maps and LiDAR there's probably a good reason.
> Dogs jump into the road in front of cars all the time and get killed, and kids get endangered at school bus crossings. That's a reality of life that robotaxis do not need to solve.
Robotaxis need to avoid any accident that a human would be able to avoid.
> IR and thermal sensing are unnecessary if the bar is human level
See, you could say this if you had some data that showed that incidents per X miles (when the vehicle is driving at night) is sufficiently low, + if the software passes some contrived scenarios to gut-check its ability to see in the dark with the necessary reliability. But you don't have that data, do you? Someone has it though :) and I'd argue regulators should have it too.