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Tesla doesn't have this problem. I think the approach of progressively autonomous non-geofenced driver assist software is better than geofenced driverless. Tes

Tesla doesn't have this problem. I think the approach of progressively autonomous non-geofenced driver assist software is better than geofenced driverless. Tesla has a fleet of millions of cars, collecting 1m+ miles per day of real-world data. When Cruise encounters a novel situation, it halts traffic. When a Tesla running FSD does, the human takes over, it gets reported as an edge case, edge cases are labeled and bucketed by frequency and tackled in that order, failing unit tests are written, the entire fleet is queried for data on similar situations, the models are trained, the edge case is fixed, and an update is pushed to the entire fleet over the air.

warning26 3y ago
Or, the Tesla simply just plows into a barrier at highway speeds, which also solves the problem! Progress!
- mwint 3y ago
  You’re not engaging in good faith.
  - simfree 3y ago
    Tesla isn't engaging with the express lane barriers on I-5 in good faith. This is a multi-year, life threatening issue that Tesla doesn't appear to care to resolve.
    - warning26 3y ago
      Yup; the fact that humans can't be expected to be ready to intervene at a moment's notice is a well-known problem in human factors engineering. GP's assertion that Tesla's strategy is good is consequently laughable.
blamazon 3y ago
If I take it as axiomatic that Tesla's approach carries a higher level of mortal risk, and I boil this down in a reductive way, I interpret you as saying: it's better to increase the loss of life and limb than slow auto traffic. How do you square that ethically?
mikestew 3y ago
Tesla doesn't have this problem. Not this particular problem, no. Tesla has other problems, like trying to drive into pedestrians, or semi-truck trailers, or fire engines... But at least Teslas don't slow down traffic! In seriousness, though, it would appear that Tesla's handling of edge cases isn't quite as neat and clean as your comment implies. That might be the spec, but the implementation appears to this outside observer to be a fair bit different.
AlotOfReading 3y ago
You're basically describing one way AV companies already deal with issues. I'll describe a typical pipeline based on broad public information: When an autonomous vehicle encounters a situation, it will initially attempt to resolve it automatically. Sometimes that fails, so it will fall back to asking a human for guidance. Depending on the company and the vehicle there may or may not be a local safety driver available as a secondary backup. In either case, that situation will be flagged. The amount of detail varies depending on whether there's a human taking notes. One major difference from Tesla here that all of the high resolution cameras, the LIDARs, the radars, etc will be recorded and made available, alongside the full logging data for the ride. Depending on the car and the software it's running, stack tracing data may also be available. Some of the consumers of this data collect these incidents into buckets to identify issues. This is used to determine things like rollout success (any particular company will have multiple "fleets" running the equivalent of canary/beta/stable) and for finding edge cases. Once one is identified (say through a news story), they'll search for similar events. From there, they can generate simulated test cases based on real incidents or do things more manually. There are multiple kinds of test cases as well. All subsequent updates will run against those test cases. Updates will be deployed to the vehicles when they're not on road. The exact frequency varies, but it's typically higher than Tesla's update cadence.

warning26 3y ago

Or, the Tesla simply just plows into a barrier at highway speeds, which also solves the problem! Progress!

mwint 3y ago
You’re not engaging in good faith.
- simfree 3y ago
  Tesla isn't engaging with the express lane barriers on I-5 in good faith. This is a multi-year, life threatening issue that Tesla doesn't appear to care to resolve.
  - warning26 3y ago
    Yup; the fact that humans can't be expected to be ready to intervene at a moment's notice is a well-known problem in human factors engineering. GP's assertion that Tesla's strategy is good is consequently laughable.

blamazon 3y ago

If I take it as axiomatic that Tesla's approach carries a higher level of mortal risk, and I boil this down in a reductive way, I interpret you as saying: it's better to increase the loss of life and limb than slow auto traffic. How do you square that ethically?

mikestew 3y ago

Tesla doesn't have this problem. Not this particular problem, no. Tesla has other problems, like trying to drive into pedestrians, or semi-truck trailers, or fire engines... But at least Teslas don't slow down traffic! In seriousness, though, it would appear that Tesla's handling of edge cases isn't quite as neat and clean as your comment implies. That might be the spec, but the implementation appears to this outside observer to be a fair bit different.

AlotOfReading 3y ago

You're basically describing one way AV companies already deal with issues. I'll describe a typical pipeline based on broad public information: When an autonomous vehicle encounters a situation, it will initially attempt to resolve it automatically. Sometimes that fails, so it will fall back to asking a human for guidance. Depending on the company and the vehicle there may or may not be a local safety driver available as a secondary backup. In either case, that situation will be flagged. The amount of detail varies depending on whether there's a human taking notes. One major difference from Tesla here that all of the high resolution cameras, the LIDARs, the radars, etc will be recorded and made available, alongside the full logging data for the ride. Depending on the car and the software it's running, stack tracing data may also be available. Some of the consumers of this data collect these incidents into buckets to identify issues. This is used to determine things like rollout success (any particular company will have multiple "fleets" running the equivalent of canary/beta/stable) and for finding edge cases. Once one is identified (say through a news story), they'll search for similar events. From there, they can generate simulated test cases based on real incidents or do things more manually. There are multiple kinds of test cases as well. All subsequent updates will run against those test cases. Updates will be deployed to the vehicles when they're not on road. The exact frequency varies, but it's typically higher than Tesla's update cadence.