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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

#101

Post by skgoa »

hangonhn wrote: post #44

Hang on. That argument makes no sense. We've had subsumption architecture for a long time now( https://en.wikipedia.org/wiki/Subsumption_architecture ). Subsumption architecture puts some of the intelligence in the lower level systems. While the higher level controls can tell the lower level systems what it wants, it can't do things that the lower system determines is dangerous. So if a normal Mercedez has a collisio…

> So if a normal Mercedez has a collision avoidance system that automatically brakes, there is no reason why an AI based system can't be built on top of that and the collision avoidance system automatically braking without intervention from the higher AI systems.

In fact this 'bottom up' approach is exactly what all automoted driving efforts in the automotive industry follow. It's the biggest difference between how the auto industry and Silicon Valley are tackling this problem. A lot of digital ink has been spilled over how slow and supposedly prone to disruption by hip and agile software companies this approach is, yet it becomes ever more evident that it was the correct choice.

Re: Why collision avoidance is harder for an AI-based system

#102

Post by skgoa »

mulmen wrote: post #7
jdmichal wrote: post #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 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 a…

It is exactly how it works. There ~40-115 different computers in a modern car that often have completely walled-off modules running on them. Most 'models' you will find in a car's software aren't even generated through machine learning, but tried and true engineering/statistics.

No one in their right mind is proposing to replace those with one big AI monolith. That's marketing BS from the likes of NVidia, who would stand to gain from it.

AI is being used in certain subfunctions like visual object detection. In the future, AI will be used to make higher level decisions like trajectory (lane choice, overtaking etc.) and route planning. But it will only hand those higher level plans down to the mostly 'dumb' computer systems of the car to be carried out just as with a manually driven car.

Re: Why collision avoidance is harder for an AI-based system

#103

Post by rimliu »

amelius wrote: post #56
hangonhn wrote: post #44

Hang on. That argument makes no sense. We've had subsumption architecture for a long time now( https://en.wikipedia.org/wiki/Subsumption_architecture ). Subsumption architecture puts some of the intelligence in the lower level systems. While the higher level controls can tell the lower level systems what it wants, it can't do things that the lower system determines is dangerous. So if a normal Mercedez has a collisio…

But braking on a highway might not be the best response in all circumstances.

Probably still the best if you are about to kill someone.

Re: Why collision avoidance is harder for an AI-based system

#104

Post by skgoa »

randomdata wrote: post #89
ams6110 wrote: post #76

Earlier quoted context omitted.

The conventional ABS system is not AI in any sense. It is a few sensors and maybe some look up tables of what to do under various speed / brake pressure / wheel rotation situations

Does that not fit the definition of artificial intelligence? The system makes decisions – ones that would be otherwise done by a human – based on its perception of the world. That is what I have always understood AI to mean. To be sure, a conventional ABS system does not use machine learning, but machine learning is only a subset of AI.

The core of this debate is the matter of what intelligence actually is. We don't really know, but the most common definition I have heard/read is that intelligence is the ability to generate new solutions when presented with previously unseen input. An ABS would not qualify under this definition, because its output is predefined rigorously for all possible combinations of input values.

Re: Why collision avoidance is harder for an AI-based system

#105

Post by gambiting »

pj_mukh wrote: post #79
hangonhn wrote: post #44

Hang on. That argument makes no sense. We've had subsumption architecture for a long time now( https://en.wikipedia.org/wiki/Subsumption_architecture ). Subsumption architecture puts some of the intelligence in the lower level systems. While the higher level controls can tell the lower level systems what it wants, it can't do things that the lower system determines is dangerous. So if a normal Mercedez has a collisio…

Very true. Which is why I'm still waiting for what happened to all the lower level safety systems, presumably driven by lighting invariant LIDAR or RADAR systems, in the Uber situation. The article kind of mentions: "cyclist detection from 3D point cloud is much harder task than cyclist detection from an image" The system didn't need to know that it was a "cyclist". There was something there, in its path. Stop.

In fact, the XC90 is already equipped with a radar-based emergency stop system from factory - that alone would have been 100% sufficient to prevent or vastly reduce the impact. But of course it looks like the system was disabled/overriden by the Uber's autonomous solution.

Re: Why collision avoidance is harder for an AI-based system

#106

Post by skgoa »

natch wrote: post #24

I'd like to see a law that says: to obtain certification to operate a self-driving car on a roadway, an organization must agree to: 1) Conform to a standard set of protocols for how sensors provide data to a self-driving software system. 2) Log data in a form that could be submitted to any conforming self-driving software system, to obtain results from that system reporting what the system would do given these inputs…

> 1) Conform to a standard set of protocols for how sensors provide data to a self-driving software system.

Doesn't exist yet, though.

Re: Why collision avoidance is harder for an AI-based system

#107

Post by skgoa »

Animats wrote: post #65

This is looking at it all wrong. Watch Chris Urmson's video from SXSW on how Waymo does it. I've mentioned that before. You build a map of what's around the vehicle. Then you try to tag some obstacles to help predict their behavior. But the obstacle detection is geometric, and does not depend on the tagging, which uses machine learning. If there's an obstacle, the system doesn't hit it, even if it has no clue how to…

> I've mentioned that before. You build a map of what's around the vehicle.

If it were that easy, everyone would have solved it already. Detecting distances, objects etc. from several varied sensors is exactly how you build this map. You can't just handwave the map into existence.

Re: Why collision avoidance is harder for an AI-based system

#108

Post by andreyk »

jdmichal wrote: post #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 no…

"Why would AI-driven vehicles not have dedicated, single-purpose subsystems such as anti-collision? "

The answer is that they will. And probably already mostly do (at least for Waymo/Cruise/most of them). It's not clear why Uber's vehicle did not brake.

Re: Why collision avoidance is harder for an AI-based system

#109

Post by amelius »

adrianN wrote: post #97
amelius wrote: post #56

Earlier quoted context omitted.

But braking on a highway might not be the best response in all circumstances.

When the collision detection system kicks in and determines that you're going to hit something in the next couple of seconds, then braking probably is the best option.

What if it's a large piece of cardboard?

Re: Why collision avoidance is harder for an AI-based system

#110

Post by chopin »

amelius wrote: post #109
adrianN wrote: post #97

Earlier quoted context omitted.

When the collision detection system kicks in and determines that you're going to hit something in the next couple of seconds, then braking probably is the best option.

What if it's a large piece of cardboard?

I know of an accident where someone overran a cardboard container used to package washing machines. He thought it was empty. Unfortunately it was not. Some truck lost part of its load.

I think its safe to break always when encountering an ambiguous situation.

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