Technology

59999 readers

2461 users here now

This is a most excellent place for technology news and articles.

Our Rules

Follow the lemmy.world rules.
Only tech related content.
Be excellent to each another!
Mod approved content bots can post up to 10 articles per day.
Threads asking for personal tech support may be deleted.
Politics threads may be removed.
No memes allowed as posts, OK to post as comments.
Only approved bots from the list below, to ask if your bot can be added please contact us.
Check for duplicates before posting, duplicates may be removed

Approved Bots

founded 2 years ago

MODERATORS

787

US to probe Tesla's 'Full Self-Driving' system after pedestrian killed in low visibility conditions (apnews.com)

submitted 2 months ago by Stopthatgirl7@lemmy.world to c/technology@lemmy.world

196 comments fedilink hide all child comments

The U.S. government’s road safety agency is again investigating Tesla’s “Full Self-Driving” system, this time after getting reports of crashes in low-visibility conditions, including one that killed a pedestrian.

The National Highway Traffic Safety Administration says in documents that it opened the probe on Thursday with the company reporting four crashes after Teslas entered areas of low visibility, including sun glare, fog and airborne dust.

In addition to the pedestrian’s death, another crash involved an injury, the agency said.

Investigators will look into the ability of “Full Self-Driving” to “detect and respond appropriately to reduced roadway visibility conditions, and if so, the contributing circumstances for these crashes.”

you are viewing a single comment's thread
view the rest of the comments

[–] tekato@lemmy.world 0 points 2 months ago (1 children)

Yes, but confidence values are not magic. These values are calculated based on how familiar the current input is to a previous observed input. If the type of input is unfamiliar to the model, what do you think happens? Usually, there will be a category with a high enough confidence score so that it will be chosen as the correct one, while being wrong. Now, assuming you somehow manage to not get a favorable confidence score for any decision. What do you think happens in that case? I never encountered this, but there can only be 3 possible paths: 1) Choose a random value. Not good. 2) Do nothing. Not good. 3) Rerun the model with slightly newer data? Maybe helps, but in the case of driving a car, slightly newer data might be too late.

[–] FatCrab@lemmy.one 1 points 2 months ago

There's plenty you could do if no label was produced with a sufficiently high confidence. These are continuous systems, so the idea of "rerunning" the model isn't that crazy, but you could pair that with an automatic decrease in speed to generate more frames, stop the whole vehicle (safely of course), divert path, and I'm sure plenty more an actual domain and subject matter expert might come up with--or a whole team of them. But while we're on the topic, it's not really right to even label these confidence intervals as such--they're just output weighting associated with respective levels. We've sort of decided they vaguely match up to something kind of sort approximate to confidence values but they aren't based on a ground truth like I'm understanding your comment to imply--they entirely derive out of the trained model weights and their confluence. Don't really have anywhere to go with that thought beyond the observation itself.