Why collision avoidance is harder for an AI-based system
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Re: Why collision avoidance is harder for an AI-based system
#2> AI is not preprogrammed to monitor a known input from a sensor to take a predefined action.
I guess one of my outstanding questions, which reading this only confirmed, is why this is the case? I mean, humans are pretty good examples of intelligence. And yet we still have and use these anti-collision systems. Because, in the end, when wrong decisions are made these systems save lives.
Why would AI-driven vehicles not have dedicated, single-purpose subsystems such as anti-collision? I mean, are we going to also remove ABS, because the AI could learn to modulate the brakes itself? How much are we going to push into AI, when the purpose-built systems are both functional and effective?
Re: Why collision avoidance is harder for an AI-based system
#3I don't know what would have happened if "this guy programmed it", but the answer should be yes, the car should have seen the cyclist and it should have pressed the brakes.
This was an interesting post, too, by Brad Templeton who worked on Google's self-driving car project for a while:
http://ideas.4brad.com/almost-every-thing-went-wrong-uber-fa...
Re: Why collision avoidance is harder for an AI-based system
#4> AI is not preprogrammed to monitor a known input from a sensor to take a predefined action. I guess one of my outstanding questions, which reading this only confirmed, is why this is the case? I mean, humans are pretty good examples of intelligence. And yet we still have and use these anti-collision systems. Because, in the end, when wrong decisions are made these systems save lives. Why would AI-driven vehicles no…
>I mean, are we going to also remove ABS, because the AI could learn to modulate the brakes itself?
This is the topic that I feel SDC enthusiasts forget. Not everything HAS TO BE AI. And we could maybe make steps towards SDC, not fantastic leaps that get people killed and really just get government involved where it doesn't need to be yet.
We could replace the ABS/ESP/traction control systems in current vehicles with a machine learning / deep learning system absolutely - that's not sexy though!
No one wants increments, they want whole self-driving cars right now - and while I have opinions about that, there is no doubt it's driving (pun intended) the industry.
Ideally, at first, we'd see components in consumer vehicles, and completely automated long haul trucks from A to B determined routes - but like I said, not sexy.
Re: Why collision avoidance is harder for an AI-based system
#5Has anyone been able to even remotely explain why the LIDAR system wasn't going nuts? I saw the "it was dark" nonsense, but I assume this vehicle had laser and IR right?
The camera footage was released, I'd like to see the lidar representation.
Re: Why collision avoidance is harder for an AI-based system
#6I don't know what would have happened if "this guy programmed it", but the answer should be yes , the car should have seen the cyclist and it should have pressed the brakes. This was an interesting post, too, by Brad Templeton who worked on Google's self-driving car project for a while: http://ideas.4brad.com/almost-every-thing-went-wrong-uber-fa...
in response to that piece by Brad, I sincerely hope that the "safety" driver in the uber accident was fired.
Re: Why collision avoidance is harder for an AI-based system
#7> AI is not preprogrammed to monitor a known input from a sensor to take a predefined action. I guess one of my outstanding questions, which reading this only confirmed, is why this is the case? I mean, humans are pretty good examples of intelligence. And yet we still have and use these anti-collision systems. Because, in the end, when wrong decisions are made these systems save lives. Why would AI-driven vehicles no…
I don't know much about AI or ML and even less about how it relates to automotive engineering but I imagine this is already how it works. I don't think there is one model for everything as much as there are models for individual components of driving. Something for steering, something(s?) for identifying obstructions, etc.
In this case maybe letting a model modulate brake pulses based on conditions like temperature and velocity makes more sense?
Hopefully someone with more experience in this domain can enlighten us.
Re: Why collision avoidance is harder for an AI-based system
#8If the technology were as undeterministic as this post makes it seem to be, there should not be any self driving car allowed even under the best conditions.
I fully agree that an AI can be fooled, but that is high level logic (path planing), the system should be designed to have a fallback that does emergency braking if all else fails.
There simply is a point where the high-level AI does not matter any more. And that is if I (the car) am moving at 45 mph towards an obstacle that is in the middle of the road less than 2 meters from my projected path. This does not mean that a full brake is required but the speed definitely needs to be reduced to account for the uncertainty, and once it is determined that it is physically impossible to miss the obstacle the system must do a full stop to reduce the impact velocity as much as possible.
It's fine, if the LIDAR data is plugged into a machine learning algorithm, and you will probably get less than the 10-20 Hz the scanner can produce, but at the same time it is probably also used by a much simpler obstacle tracking algorithm that can run at near real-time speeds.
Re: Why collision avoidance is harder for an AI-based system
#9I don't know what would have happened if "this guy programmed it", but the answer should be yes , the car should have seen the cyclist and it should have pressed the brakes. This was an interesting post, too, by Brad Templeton who worked on Google's self-driving car project for a while: http://ideas.4brad.com/almost-every-thing-went-wrong-uber-fa...
in response to that piece by Brad, I sincerely hope that the "safety" driver in the uber accident was fired.
Why? If it is not proven the driver was negligent why fire this individual? Presumably this individual has a lot of experience and domain knowledge in testing self driving cars so replacing them with someone else may not be an improvement.
If they did make a mistake that got someone killed that could change things but I would hope we wait to find out if the driver was actually at fault.
Re: Why collision avoidance is harder for an AI-based system
#10Has anyone been able to even remotely explain why the LIDAR system wasn't going nuts? I saw the "it was dark" nonsense, but I assume this vehicle had laser and IR right? The camera footage was released, I'd like to see the lidar representation.
The closest I can give you is a simulation of a scene modeled after the video using a very simple reconstruction of the site of the accident (based on google maps and street view)