Self-Driving Tesla causes 8 Car Crash (UPDATE: Self-Driving Tesla bursts in Flames)

TRUEST

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The logic in the code is flawed. I will tell Elon to let me take it over. This is ridiculous. I’ll charge him half a Billie
 

Alix217

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So apparently Elon was against having radar/LIDAR on the cars:


Now he's backtracking, what a dumbass:

 

Stir Fry

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Yeah, I got stuck in the city at my aunt's house for a couple extra hours the day that that had happened
 

null

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So apparently Elon was against having radar/LIDAR on the cars:


Now he's backtracking, what a dumbass:


a lot of teslas have radar hardware already. he only started removing it from some models in 2021 IIRC. now they are reversing that.

he went all-in with vision only AI and tried to save costs :hubie:
 

Rekkapryde

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a lot of teslas have radar hardware already. he only started removing it from some models in 2021 IIRC. now they are reversing that.

he went all-in with vision only AI and tried to save costs :hubie:
He gotta go.

Needs to listen to the real engineers more at the company.
 

BigMoneyGrip

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a lot of teslas have radar hardware already. he only started removing it from some models in 2021 IIRC. now they are reversing that.

he went all-in with vision only AI and tried to save costs :hubie:
Radar is more reliable.. mans tried it with AI and that shyt out here straight killing folk
 

StretfordRed

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Imagine the slaughter when those 18 wheelers hit the motorways.

The UK need to ban all road automation. Not even joking. I don’t see anything good about it until it’s 110% fault free.

Humans need to legally pass test to drive on real streets but who is testing the autonomous drivers?

We can’t use humans as real life crash dummies.
 

null

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Radar is more reliable..

.. for some things .. obstacle and distance detection

mans tried it with AI and that shyt out here straight killing folk

you will always need the AI, else how is the car going to interpret its environment?

you have lidar/ridar running as a collision/obstacle warning sub-system where AI executive combines that with visual modelling.

priority being avoid colliding with dangerous obstacles (including those behind/beside you).
 

BigMoneyGrip

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.. for some things .. obstacle and distance detection



you will always need the AI, else how is the car going to interpret its environment?

you have lidar/ridar running as a collision/obstacle warning sub-system where AI executive combines that with visual modelling.

priority being avoid colliding with dangerous obstacles (including those behind/beside you).
But why can’t they have the AI working in tandem with radar?
 

null

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But why can’t they have the AI working in tandem with radar?

what i said is in tandem. it is just a question of which information you give priority. you don't however mix two/n sets of raw data. you act on n/sets of interpreted data as the raw data is each sub-system is very different.

at the end of the day you have to deal with conflicting information and have a decision matrix/model based on that.

in most cases for possible collisions/obstacles you are going to trust radar/lidar. but in any real world example you are going to have to deal with faulty data, faulty devices so mitigation actions will have to be layered, with normal state recoverable and extreme action (full brake) the last option.

the more i think about it the more device redundancy, vehicle-2-vehicle data sharing etc will play a role in driving accidents down past a certain threshold.

or put another way, how much can you trust a single device? in computing systems you might build in some self-diagnotics redundancy (checksums. alive-pings, predicatble data-stream) you might need the same out there in the real world i.e. obstacles of known distances (or in practice delta differences between two objects) to allow for automatic device checks.
 

BigMoneyGrip

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what i said is in tandem. it is just a question of which information you give priority. you don't however mix two/n sets of raw data. you act on n/sets of interpreted data as the raw data is each sub-system is very different.

at the end of the day you have to deal with conflicting information and have a decision matrix/model based on that.

in most cases for possible collisions/obstacles you are going to trust radar/lidar. but in any real world example you are going to have to deal with faulty data, faulty devices so mitigation actions will have to be layered, with normal state recoverable and extreme action (full brake) the last option.

the more i think about it the more device redundancy, vehicle-2-vehicle data sharing etc will play a role in driving accidents down past a certain threshold.

or put another way, how much can you trust a single device? in computing systems you might build in some self-diagnotics redundancy (checksums. alive-pings, predicatble data-stream) you might need the same out there in the real world i.e. obstacles of known distances (or in practice delta differences between two objects) to allow for automatic device checks.
Aircraft today have those exact systems that you are talking about..
 

MR. SNIFLES

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THIS IS ONE OF THE REASONS FORD ABANDONED FULLY AUTONOMOUS VEHICLES FOR NOW. IT'S NOT POSSIBLE RIGHT NOW WITHOUT SUPPORT INFRASTRUCTURE.
 
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