4 ms·

When I'm driving at night I cannot reliably determine the difference between a moose and an empty stretch of road because unlike deer moose do not have reflecti

by xoa 3y ago

When I'm driving at night I cannot reliably determine the difference between a moose and an empty stretch of road because unlike deer moose do not have reflective eyes and stand tall enough that headlights will merely show a few easy to miss dark lines (the legs). One of these (empty road) I am perfectly fine to drive through. The other will result in bad day all around (assuming either side survives). Ie, I find people like you just, like, mindbogglingly ridiculous. Sure, no single sensor is going to magically solve everything. But we have tens of thousands of deaths and millions of casualties a year with humans at the wheel, and a sizable number of them are due to the limits of human visual spectrum input. The goal here shouldn't be to match human limits but to greatly exceed them. FLIR, lidar, radar, ultrasonics, all around vision in general, all should be part of the final package. Crashes, injuries and deaths are expensive to put it mildly. The idea that cameras are or ever could be good enough is absurd, and that was if they were as good as human eyes, which they aren't. No amount of software or compute power is going to deal with lack of quality input data, and the visible spectrum alone just can't provide that consistently without costs we have long since determined are unacceptable (have ultra high output flood lights around all vehicles). More sensors beyond human senses can both cover scenarios we can't and help fill in for individual sensors not being as high quality as might be ideal yet.

williamcotton 3y ago
What I find mindbogglingly ridiculous is how emotionally charged all of the "the system must include LIDAR" proponents are. It seems to suggest otherwise is perceived as nothing but a coldly calculated cost cutting measure. None of the arguments I come up against are anything but a surface level "well duh, intuitively more sensors equals more better" along with a litany of "you must like murdering babies". We do not have autonomous systems that can deal with the kinds of problems that human drivers currently deal with, which as I illustrated, is an infinity of embodied problems based on the entirety of our lives spent interacting with our physical environment. My intuitions tell me that in order to have a machine that can make human-like decisions that it needs to have that exact same kind of embodied experience, that is to have interacted with the physical environment in the same manner as a human, which suggests to me that perhaps an android is the way forward. Then once the autonomous system is extracted from the android and placed in a car it can be further trained on additional sensors, like how a human driver can take the input of LIDAR.
- deleted 3y ago
  [deleted]
- donkeyd 3y ago
  > What I find mindbogglingly ridiculous is how emotionally charged all of the "the system must include LIDAR" proponents are. > None of the arguments I come up against are anything but a surface level "well duh, intuitively more sensors equals more better" along with a litany of "you must like murdering babies". A bit pot blaming the kettle there. The thing is, the 'vision is enough' crowd often manages to pick a single use case, like seeing the difference between cardboard and plywood, that has nothing to do with Lidar and then asking, rhetorically, how Lidar would help with that. By opening a discussion in such a disingenuous way, you provoke the emotional response you seem to dislike. If you want to have an actual discussion, maybe start by asking a genuine question. > in order to have a machine that can make human-like decisions Honestly, I don't think many people want it to make human-like decisions. We want it to make much, much better decisions. By your standard, we should just put two camera's on top that rotate on a platform that can only move about 180 degrees both ways. Also, remove radar and ultrasonics, because humans don't have those either. I can't give you decent arguments for using Lidar. I'm not in that field, so I can only return my own gut feeling in response to yours and I honestly don't think that has any value.
  - williamcotton 3y ago
    If you want to have an actual discussion, maybe start by asking a genuine question. Go back and look at the comment that I was responding to… Also, re-read the comment I wrote that you responded to and then re-read your response…
risyachka 3y ago
>> When I'm driving at night I cannot reliably determine the difference between a moose and an empty stretch of road But you are still here so looks like you can drive just fine without that distinction.
- Timon3 3y ago
  ... no? Just because they weren't unlucky enough to crash into a moose so far doesn't mean tomorrow he will be lucky as well? Events tomorrow can take different turns than events yesterday.
aziaziazi 3y ago
> deaths […] with humans at the wheel, and a sizable number of them are due to the limits of human visual spectrum input. There will always be situations where (human or computer) captors aren’t sufficient. You can add more sensors or blame the existing one. Until that, a typical driver adapt its velocity depending on his capabilities and the road/weather. In my country that also partially enforced by the driving code: freeway is limited to 130km/h but reduced to 110km/h if it’s raining or 50km/h if visibility is less than 50m. Adding more sensors will let you increase your speed but if you want safety, look for your speed.
- bee_rider 3y ago
  > Until that, a typical driver ?? adapt its velocity depending on his capabilities and the road/weather. There’s an important missing word here, do you mean “should” or “does” where I’ve added in question marks? Because people hit moose and deer all the time, I think it would be good if everyone would drive safely, but they don’t. An autonomous car with capabilities similar to a human that is designed by responsible engineers to drive safely would not be very popular I think, it would drive very slowly and annoy the passengers. And of course an autonomous car that was as dangerous as a human would be the subject of all sorts of news reports and chatter online, and nobody would buy it because it would be seen as too dangerous. It isn’t fair, but we won’t see widespread adoption until the average person can anthropomorphize a model of a car as, like, a guy they know who drives a lot and has never gotten in an accident. Because the Tesla algorithm is what we hear about, we think of it as being a single entity that drives all Teslas, and it ran into a fire truck or whatever, so it must be kind of an idiot.
sebastos 3y ago
>a sizable number of them are due to the limits of human visual spectrum input But how do you know that? You don't really. The lion's share could well be from just not being consistently careful in the right ways, or reckless high speed driving, or the tyranny of human reaction times. I do agree that at this stage, it's worth trying to pile on all of the sensors possible to see whether that gets you more reliable odometry / mapping. But you are getting super fixated on the specific problem of knowing what the shape of things around you is, and what people are trying to get across to you is that the problem is way, way harder than that. Just knowing where stuff is is like 10% of the problem. You also have to know what that stuff is and how it semantically relates to your driving problem. You have to be able to make predictions about how the world is going to play out, and what constitutes a safe action. And that's not even the hardest part - you also have to figure out how to glide through the world and not drive like a grandma, even though there is some inherent unsafety in building up a head of steam in a 2 ton piece of metal when a child could dive in front of you at any time. In other words, you have to be able to push the limits of UNsafe actions so that you're not completely obnoxious to be around on the road. All of this is going to require a many-levels-up understanding of the world around the car, and that understanding is going to do a ton of heavy lifting in terms of interpreting things that haven't been directly sensed. As soon as you get an occlusion, you have already left the realm of sensing and entered into the higher level realm of reasoning about the world's state based on priors. It might be that the other sensing modalities will help you be better than a human, but by far the more important unsolved problem is getting human-ish to begin with, and we are still very far from that. The other thing you're brushing past is that high-level reasoning does not have an infinite bandwidth of attention. As you ingest more and more sensors, your sensor fusion problem becomes much more expensive. For a reasonable amount of compute hardware, and with the constraints of latency, you don't have infinite latitude to reason over ever-wider sensor streams. So at a certain point you're going to encounter a squaring effect with having to add both sensors and the compute to handle it, with additional considerations once that data gets so wide that "normal" ways of handling it stop working and you have to get exotic. For a given compute substrate, it is not a given that the best way to use it is to slurp a massively wide sensor suite into it. Your cycles could be better spent doing deeper reasoning over the data you've got. If you need an evolutionary analogy, you can ask yourself why two eyes seems to be plenty for the majority of animals? The brainpower is spent on building a complicated internal state of the world, and it can only focus on so much at a time anyway. Bio-inspired robotics is a thing for a reason - we learn a lot of subtle lessons from nature that are not intuitively obvious. This could easily be one of them.

by xoa 3y ago

williamcotton 3y ago

What I find mindbogglingly ridiculous is how emotionally charged all of the "the system must include LIDAR" proponents are. It seems to suggest otherwise is perceived as nothing but a coldly calculated cost cutting measure. None of the arguments I come up against are anything but a surface level "well duh, intuitively more sensors equals more better" along with a litany of "you must like murdering babies". We do not have autonomous systems that can deal with the kinds of problems that human drivers currently deal with, which as I illustrated, is an infinity of embodied problems based on the entirety of our lives spent interacting with our physical environment. My intuitions tell me that in order to have a machine that can make human-like decisions that it needs to have that exact same kind of embodied experience, that is to have interacted with the physical environment in the same manner as a human, which suggests to me that perhaps an android is the way forward. Then once the autonomous system is extracted from the android and placed in a car it can be further trained on additional sensors, like how a human driver can take the input of LIDAR.

deleted 3y ago
[deleted]
donkeyd 3y ago
> What I find mindbogglingly ridiculous is how emotionally charged all of the "the system must include LIDAR" proponents are. > None of the arguments I come up against are anything but a surface level "well duh, intuitively more sensors equals more better" along with a litany of "you must like murdering babies". A bit pot blaming the kettle there. The thing is, the 'vision is enough' crowd often manages to pick a single use case, like seeing the difference between cardboard and plywood, that has nothing to do with Lidar and then asking, rhetorically, how Lidar would help with that. By opening a discussion in such a disingenuous way, you provoke the emotional response you seem to dislike. If you want to have an actual discussion, maybe start by asking a genuine question. > in order to have a machine that can make human-like decisions Honestly, I don't think many people want it to make human-like decisions. We want it to make much, much better decisions. By your standard, we should just put two camera's on top that rotate on a platform that can only move about 180 degrees both ways. Also, remove radar and ultrasonics, because humans don't have those either. I can't give you decent arguments for using Lidar. I'm not in that field, so I can only return my own gut feeling in response to yours and I honestly don't think that has any value.
- williamcotton 3y ago
  If you want to have an actual discussion, maybe start by asking a genuine question. Go back and look at the comment that I was responding to… Also, re-read the comment I wrote that you responded to and then re-read your response…

risyachka 3y ago

>> When I'm driving at night I cannot reliably determine the difference between a moose and an empty stretch of road But you are still here so looks like you can drive just fine without that distinction.

Timon3 3y ago
... no? Just because they weren't unlucky enough to crash into a moose so far doesn't mean tomorrow he will be lucky as well? Events tomorrow can take different turns than events yesterday.

aziaziazi 3y ago

> deaths […] with humans at the wheel, and a sizable number of them are due to the limits of human visual spectrum input. There will always be situations where (human or computer) captors aren’t sufficient. You can add more sensors or blame the existing one. Until that, a typical driver adapt its velocity depending on his capabilities and the road/weather. In my country that also partially enforced by the driving code: freeway is limited to 130km/h but reduced to 110km/h if it’s raining or 50km/h if visibility is less than 50m. Adding more sensors will let you increase your speed but if you want safety, look for your speed.

bee_rider 3y ago
> Until that, a typical driver ?? adapt its velocity depending on his capabilities and the road/weather. There’s an important missing word here, do you mean “should” or “does” where I’ve added in question marks? Because people hit moose and deer all the time, I think it would be good if everyone would drive safely, but they don’t. An autonomous car with capabilities similar to a human that is designed by responsible engineers to drive safely would not be very popular I think, it would drive very slowly and annoy the passengers. And of course an autonomous car that was as dangerous as a human would be the subject of all sorts of news reports and chatter online, and nobody would buy it because it would be seen as too dangerous. It isn’t fair, but we won’t see widespread adoption until the average person can anthropomorphize a model of a car as, like, a guy they know who drives a lot and has never gotten in an accident. Because the Tesla algorithm is what we hear about, we think of it as being a single entity that drives all Teslas, and it ran into a fire truck or whatever, so it must be kind of an idiot.

sebastos 3y ago

>a sizable number of them are due to the limits of human visual spectrum input But how do you know that? You don't really. The lion's share could well be from just not being consistently careful in the right ways, or reckless high speed driving, or the tyranny of human reaction times. I do agree that at this stage, it's worth trying to pile on all of the sensors possible to see whether that gets you more reliable odometry / mapping. But you are getting super fixated on the specific problem of knowing what the shape of things around you is, and what people are trying to get across to you is that the problem is way, way harder than that. Just knowing where stuff is is like 10% of the problem. You also have to know what that stuff is and how it semantically relates to your driving problem. You have to be able to make predictions about how the world is going to play out, and what constitutes a safe action. And that's not even the hardest part - you also have to figure out how to glide through the world and not drive like a grandma, even though there is some inherent unsafety in building up a head of steam in a 2 ton piece of metal when a child could dive in front of you at any time. In other words, you have to be able to push the limits of UNsafe actions so that you're not completely obnoxious to be around on the road. All of this is going to require a many-levels-up understanding of the world around the car, and that understanding is going to do a ton of heavy lifting in terms of interpreting things that haven't been directly sensed. As soon as you get an occlusion, you have already left the realm of sensing and entered into the higher level realm of reasoning about the world's state based on priors. It might be that the other sensing modalities will help you be better than a human, but by far the more important unsolved problem is getting human-ish to begin with, and we are still very far from that. The other thing you're brushing past is that high-level reasoning does not have an infinite bandwidth of attention. As you ingest more and more sensors, your sensor fusion problem becomes much more expensive. For a reasonable amount of compute hardware, and with the constraints of latency, you don't have infinite latitude to reason over ever-wider sensor streams. So at a certain point you're going to encounter a squaring effect with having to add both sensors and the compute to handle it, with additional considerations once that data gets so wide that "normal" ways of handling it stop working and you have to get exotic. For a given compute substrate, it is not a given that the best way to use it is to slurp a massively wide sensor suite into it. Your cycles could be better spent doing deeper reasoning over the data you've got. If you need an evolutionary analogy, you can ask yourself why two eyes seems to be plenty for the majority of animals? The brainpower is spent on building a complicated internal state of the world, and it can only focus on so much at a time anyway. Bio-inspired robotics is a thing for a reason - we learn a lot of subtle lessons from nature that are not intuitively obvious. This could easily be one of them.