rxlawdude
Active Member
Words matter. I'm done arguing about your repeated opinions couched as fact.
Carry on!
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Autonomous Car Progress
- Thread starter stopcrazypp
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- Autonomous Vehicles
Carry on!
Daniel in SD
(supervised)
What evidence do you think is required to prove that someone is arrogant?
rxlawdude
Active Member
The whole point: arrogance is subjective, so your question cannot be answered universally.
Daniel in SD
(supervised)
If a claim about arrogance is always subjective then it seems unnecessary to preface that claim with the disclaimer that it is an opinion.
I must say that I rarely have trouble parsing peoples posts and determining which parts are opinions and which parts are factual claims. Very few people here explicitly separate the two so I'm not sure why you're always insisting that @diplomat33's post are hard to interpret.
powertoold
Active Member
I watched the Mobileye NYC drive YouTube video. My conclusion is the same: Mobileye is a joke and will never deploy any meaningful level 4 service to consumers.
I‘m not going to point out specifics because it really doesn’t matter, as the naysayers will not change their minds.
However, take a look at Mobileye’s wording of the video. It doesn’t say the drive was fully autonomous. It says it was in an autonomous vehicle. Also, pay attention to Mobileye’s drivable space NN as it turns toward a white bus and also later on when it turns into an adjacent car to the left.
Compare to Tesla’s drivable space NN:
I‘m not going to point out specifics because it really doesn’t matter, as the naysayers will not change their minds.
However, take a look at Mobileye’s wording of the video. It doesn’t say the drive was fully autonomous. It says it was in an autonomous vehicle. Also, pay attention to Mobileye’s drivable space NN as it turns toward a white bus and also later on when it turns into an adjacent car to the left.
Compare to Tesla’s drivable space NN:
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diplomat33
Average guy who loves autonomous vehicles
Mobileye is a global supplier of ADAS that has provided their ADAS to tens of millions of cars worldwide. Furthermore, Mobileye is testing autonomous driving in several cities around the world and has demonstrated very capable FSD. The NYC drive is very impressive. Nobody with any objectivity would call them a "joke". That just makes you sound ridiculous.
And as we speak, Mobileye is preparing to launch a L4 robotaxi service in Tel Aviv as early as next year.
Now, it is always possible that there could be some unforeseen delays but to say they will "never" deploy any meaningful L4 service is just silly.
rxlawdude
Active Member
powertoold
Active Member
Nah, it's not silly. I do believe Mobileye will never be good enough to get to where Waymo is now for example. Also, I don't think their Zeeker or whatever car will produce over 10,000 total (I'm thinking it'll be delayed as well, if not the car itself, the SuperVision features will be delayed or very lackluster). Again, just my view based on the logical spaghetti I've gathered through their videos and seeing their end results (in their drive videos).
You went from 'will never have or deploy L4' to 'will never deploy any meaningful L4'. You're already backpeddling like clockwork lmfao.
Yes because saying the drive was fully autonomous is all its about right right?
And then it proceeded to run into the bus...wait thats a tesla thing lmaoooo
And then look at this lol
So now you consider Waymo good?
All zeekr preorder for this year is already sold out. They are aiming for 8k deliveries for Q4 and 50k for 2022. Any delay will be due to supply constraints that is affecting every automaker. You are literally grasping at straws. This is not a good look.
MobilEye was around 40 minutes of uninterrupted city driving. No safety disengaments.
FSD beta; I don't think I have seen one single FSD beta video with from any city centre with more than 5 minutes between safety disengagments.
Why doesn't the beta testers try the same route as MobilEye in NYC btw?
FSD beta; I don't think I have seen one single FSD beta video with from any city centre with more than 5 minutes between safety disengagments.
Why doesn't the beta testers try the same route as MobilEye in NYC btw?
It is my opinion that it is a fact that Elon has been arrogant
Lease see:
Thread 'FSD Timeline Promises (summary)'
FSD Timeline Promises (summary)
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powertoold
Active Member
Waymo has a level 4 service available to the public in Chandler. Tesla and Mobileye only have level 2, so they must be way behind!
It's funny how people can watch the same thing and come up with different conclusions. People seem to miss how sloppy and unpolished Mobileye is. They'll never get there. They're like the Nikola of FSD (although probably not fraud). They use the most smoke and mirrors and jibberish presentations. Watch and be critical of their technical presentations, particularly the parts about separate lidar radar subsystems, vision only, true redundancy, REM mapping with 10kb a mile, needing to practice, their roadmap, etc.
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jimm01
Member
Human error being the main cause of traffic accidents includes distracted driving (#1), bad weather (carelessness), recklessness, speeding, and intoxication. It would be hard to argue that self-driving cars will not help eliminate human error. Even the best skilled drivers make bad decisions, and as anyone who drives routinely knows there are a lot of unskilled, dare I say clueless, drivers on the highway. Add to this pedestrians, wildlife, and anything that could fall into the roadway, (and ones reaction to them), there is a considerable amount of unpredictability that needs to be included in an autonomous model (driver ontology). My argument is the level of randomness needed to model the behavior of a driver will be in some respect proportional to the level of total system autonomy. Although autonomous vehicles will be able to achieve a high degree of autonomy, it will be difficult to achieve full self-driving, without external influence (e.g. geofencing), until the models can eliminate ‘humans’ in the ontology.
A human centric autonomous vehicle model will require external influence (this in not level 5). The reasoning needed to achieve level 6 must be independent of human operational decision-making. I’m not begging the question here. Although “by definition” level 5 is free of human operational decision-making and control, a level 5model will need to make decisions following a strict protocol based on present meteorological and highway conditions. In other words it’s based on the limits of the vehicle within the system not the limits of driver reaction and situational awareness. If there ever is a locally interpreted level 5 model I believe it will require all other vehicles to be at level 3/4 (some form of peer-to-peer situational awareness). We will have to wait until human driver decision-making is relegated to merely picking a destination for fully robust and resilient autonomous system is realized, (consider the OODA loop).
On final thought. It is relatively easy to create passable test conditions when one knows the limits of what’s being tested, (I’m not imply smoke and mirrors). However, we have some real world feedback and at present none of these ‘systems’ are at level-2.
“Artificial intelligence is no match for natural stupidity.” ~ unknown (at least I don’t know)
Edit: replaced level 6 with 5.
A human centric autonomous vehicle model will require external influence (this in not level 5). The reasoning needed to achieve level 6 must be independent of human operational decision-making. I’m not begging the question here. Although “by definition” level 5 is free of human operational decision-making and control, a level 5model will need to make decisions following a strict protocol based on present meteorological and highway conditions. In other words it’s based on the limits of the vehicle within the system not the limits of driver reaction and situational awareness. If there ever is a locally interpreted level 5 model I believe it will require all other vehicles to be at level 3/4 (some form of peer-to-peer situational awareness). We will have to wait until human driver decision-making is relegated to merely picking a destination for fully robust and resilient autonomous system is realized, (consider the OODA loop).
On final thought. It is relatively easy to create passable test conditions when one knows the limits of what’s being tested, (I’m not imply smoke and mirrors). However, we have some real world feedback and at present none of these ‘systems’ are at level-2.
“Artificial intelligence is no match for natural stupidity.” ~ unknown (at least I don’t know)
Edit: replaced level 6 with 5.
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diplomat33
Average guy who loves autonomous vehicles
There is no such thing as Level 6. The SAE levels go from L0 to L5. Do you mean Level 5?
jimm01
Member
diplomat33
Average guy who loves autonomous vehicles
Thanks, Sorry I am not zero-based.
Well, the SAE levels are zero-based. You need to use the correct terms please or people won't understand you.
diplomat33
Average guy who loves autonomous vehicles
Interesting. Aurora says that their robotaxi service to launch in 2024 will focus on higher speeds highway runs to the airport because their data from Uber suggests that it is a more lucrative business model:
www.forbes.com
Aurora Leverages Uber Ride Data To Plan High-Speed Robotaxi Service
The Silicon Valley startup intends to initially focus its autonomous ride service on highway routes, which it thinks may be higher demand and more lucrative in 2024.
www.forbes.com
This is my thesis and speculative.
Vision is "solved" enough that it is a practical platform from which to build/expand driving.
Limited access highway driving is not perfect but delivering results that demonstrate value.
Surface street driving is a much larger challenge and vision alone does not solve it. The solution that DOJO is focused upon seems to be labeling and processing video data much faster but possibly much more.
The next level solution to surface street driving is applying the mothership NN to mapping. Each intersection gets a probability of successful navigation based on vast processing of past experience with each intersection. The NN determines a route based on the highest probability of intersection success. This would primarily be based on approach. Which approach to an intersection has the highest probability of a safe transition?
This would be route based optimization of navigation on autopilot or something like it. This would deliver surface street safety performance equal to highway driving.
This could be compared to geo-fencing but it is far more NN based as I see it.
Map routing analysis solves to approach each intersection the "best" way given the dynamic conditions of traffic, weather, visibility, activity, time of day etc. What this means is that the idea of handling any driving situation is surrendered to an approach that there is a best way for each intersection. As an extreme example, it could be that mapping routes in a way that maximizes right turns and minimizes left turns, avoids circles and uncontrolled intersections for example.
Tesla has already separated tasks such as "summon" and "highway driving" into their own catagories. I am proposing that one (not the only) way forward is to generate dynamic maps for each destination that maximizes intersection success based on the vast experience of the fleet. This is a practical way to significantly advance the march of 9s in terms of safety.
One possible way this could work (not the only way) would be for the driver to have a setting for mapping under FSD that allows a choice of zero intervention success probability. The choice the driver is making is time vs convenience vs safety. This would provide the maximum likelihood of a safe trip to destination. Human driving would have a lower probability of success for example.
As NN solution probabilities improve the time to safe destination would improve.
Every day FSD waits to reach a near perfect solution (.999999...) for every driving situation, there are deaths and injuries due to accidents. At some point the NN technology will good enough that some navigational maps/routes could deliver the desired endpoint based on a particular route. We should seek this solution in the near term and make it available. Tesla is about to come to this decision point IMO.
Vision is "solved" enough that it is a practical platform from which to build/expand driving.
Limited access highway driving is not perfect but delivering results that demonstrate value.
Surface street driving is a much larger challenge and vision alone does not solve it. The solution that DOJO is focused upon seems to be labeling and processing video data much faster but possibly much more.
The next level solution to surface street driving is applying the mothership NN to mapping. Each intersection gets a probability of successful navigation based on vast processing of past experience with each intersection. The NN determines a route based on the highest probability of intersection success. This would primarily be based on approach. Which approach to an intersection has the highest probability of a safe transition?
This would be route based optimization of navigation on autopilot or something like it. This would deliver surface street safety performance equal to highway driving.
This could be compared to geo-fencing but it is far more NN based as I see it.
Map routing analysis solves to approach each intersection the "best" way given the dynamic conditions of traffic, weather, visibility, activity, time of day etc. What this means is that the idea of handling any driving situation is surrendered to an approach that there is a best way for each intersection. As an extreme example, it could be that mapping routes in a way that maximizes right turns and minimizes left turns, avoids circles and uncontrolled intersections for example.
Tesla has already separated tasks such as "summon" and "highway driving" into their own catagories. I am proposing that one (not the only) way forward is to generate dynamic maps for each destination that maximizes intersection success based on the vast experience of the fleet. This is a practical way to significantly advance the march of 9s in terms of safety.
One possible way this could work (not the only way) would be for the driver to have a setting for mapping under FSD that allows a choice of zero intervention success probability. The choice the driver is making is time vs convenience vs safety. This would provide the maximum likelihood of a safe trip to destination. Human driving would have a lower probability of success for example.
As NN solution probabilities improve the time to safe destination would improve.
Every day FSD waits to reach a near perfect solution (.999999...) for every driving situation, there are deaths and injuries due to accidents. At some point the NN technology will good enough that some navigational maps/routes could deliver the desired endpoint based on a particular route. We should seek this solution in the near term and make it available. Tesla is about to come to this decision point IMO.
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