5 ms·

I'm sorry I can't back up my claims but you will be proved wrong with time. I would bet in less than 10 years you'll have camera only fully autonomous systems.

by Nydhal 8y ago

Fricken 8y ago
From Sterling Anderson, former director of Autopilot who oversaw the implementation of HW2: >Perception is a game of statistics.Crudely speaking, if we have three independent modalities with epsilon miss-detection-rates and we combine them we can achieve an epsilon³ rate in perception. In practice, relatively orthogonal failure modes won’t achieve that level of benefit, however, an error every million miles can get boosted to an error every billion miles. It is extremely difficult to achieve this level of accuracy with a single modality alone. >Different sensor modalities have different strengths and weaknesses; thus, incorporating multiple modalities drives orders of magnitude improvements in the reliability of the system. Cameras suffer from difficulty in low-light and high dynamic range scenarios; radars suffer from limited resolution and artifacts due to multi-path and doppler ambiguity; lidars “see” obscurants. https://medium.com/aurora-blog/auroras-approach-to-development-5e42fec2ee4b https://medium.com/aurora-blog/auroras-approach-to-developme...
- dstroot 8y ago
  First, thanks for sharing this! Second - based on the language used I can’t tell if he is saying Tesla’s camera and Radar approach will work, or that it won’t. The only thing that I pulled out was that if we increase the types of sensors we get better results because they have different strengths and weakenesses.
  - Fricken 8y ago
    Sterling does believe cameras may someday be good enough, but I'm personally of the belief that Lidar will get cheap before vision gets good, and as such there's no good reason to not have the extra redundancy.
- salty_biscuits 8y ago
  He is basically just saying that the errors need to be independent, so you can get that with different capture mechanisms. I think that is wrong. For example, small, fast and poorly reflective will have similar detection performance for lidar and cameras. I think that the real problem is getting consistent statistical estimators and fusing them at a useful update rate. Has anyone seen the lidar from the uber crash? It would be interesting to see if a person could "tell" that the poor pedestrian wasn't an artifact quickly from lidar alone.
  - Fricken 8y ago
    The radar, Lidar and cameras on the Uber that struck Elaine Herzberg all detected her, it wasn't a sensor failure that led to her death, it was a software failure, the autonomous OS tuned to not respond to positives below a certain threshold.
deleted 8y ago
[deleted]
Jdam 8y ago
Have you ever heard about that thing called fog?
- ModernMech 8y ago
  As an existence proof, people drive through fog every day. We prove that it's possible to take binocular visual data and convert that into a series of control signals that will propel a car through fog. Sure sometimes accidents happen, but every day thousands upon thousands of people safely navigate fog in e.g. San Francisco or London. I see no reason machines shouldn't be able to perform at least as well one day.
  - nutjob2 8y ago
    > I see no reason machines shouldn't be able to perform at least as well one day. Assuming that day is infinitely far away, then you're right.
    - beat 8y ago
      Why? What's magical about human beings that a sufficiently advanced sensor and sufficiently advanced AI can't do the same responsive task? If there's magic in the human mind at all, it's the creative side of the mind. Driving isn't a creative act.
  - mikepurvis 8y ago
    Machines will be (and already are) held to a much higher standard than human drivers— there are a lot of reasons for this, ranging from the emotional to the pragmatic. Just because thousands of people roll the dice every day driving in unsafe conditions does not mean that we should tolerate machines doing so.
    - spitfire 8y ago
      One note is that perhaps people roll the dice because they want to feel some control and forward momentum. But if you're sitting in the car, being autonomously driven somewhere will you be so impatient? I assume the car will give you an ETA, so you'll check the clock and go back to your book/social media. I'm okay with "slower, but smoother".
jpm_sd 8y ago
There is no upside to this approach. LIDAR is only getting cheaper, there is no reason not to use it.
oliveshell 8y ago
I’ll take the “over” on that bet any day of the week. It might not be 20 years, but it’ll be a friggin’ while. There are scenarios it’s possible to encounter on the road that humans don’t even necessarily know how to handle immediately. In proper, brutal, real-world testing, one very quickly enters the realm of problems that you’d need full-fledged general AI to reason through.

I'm sorry I can't back up my claims but you will be proved wrong with time. I would bet in less than 10 years you'll have camera only fully autonomous systems.

by Nydhal 8y ago

I'm sorry I can't back up my claims but you will be proved wrong with time. I would bet in less than 10 years you'll have camera only fully autonomous systems.

Fricken 8y ago

From Sterling Anderson, former director of Autopilot who oversaw the implementation of HW2: >Perception is a game of statistics.Crudely speaking, if we have three independent modalities with epsilon miss-detection-rates and we combine them we can achieve an epsilon³ rate in perception. In practice, relatively orthogonal failure modes won’t achieve that level of benefit, however, an error every million miles can get boosted to an error every billion miles. It is extremely difficult to achieve this level of accuracy with a single modality alone. >Different sensor modalities have different strengths and weaknesses; thus, incorporating multiple modalities drives orders of magnitude improvements in the reliability of the system. Cameras suffer from difficulty in low-light and high dynamic range scenarios; radars suffer from limited resolution and artifacts due to multi-path and doppler ambiguity; lidars “see” obscurants. https://medium.com/aurora-blog/auroras-approach-to-development-5e42fec2ee4b https://medium.com/aurora-blog/auroras-approach-to-developme...

dstroot 8y ago
First, thanks for sharing this! Second - based on the language used I can’t tell if he is saying Tesla’s camera and Radar approach will work, or that it won’t. The only thing that I pulled out was that if we increase the types of sensors we get better results because they have different strengths and weakenesses.
- Fricken 8y ago
  Sterling does believe cameras may someday be good enough, but I'm personally of the belief that Lidar will get cheap before vision gets good, and as such there's no good reason to not have the extra redundancy.
salty_biscuits 8y ago
He is basically just saying that the errors need to be independent, so you can get that with different capture mechanisms. I think that is wrong. For example, small, fast and poorly reflective will have similar detection performance for lidar and cameras. I think that the real problem is getting consistent statistical estimators and fusing them at a useful update rate. Has anyone seen the lidar from the uber crash? It would be interesting to see if a person could "tell" that the poor pedestrian wasn't an artifact quickly from lidar alone.
- Fricken 8y ago
  The radar, Lidar and cameras on the Uber that struck Elaine Herzberg all detected her, it wasn't a sensor failure that led to her death, it was a software failure, the autonomous OS tuned to not respond to positives below a certain threshold.

deleted 8y ago

[deleted]

Jdam 8y ago

Have you ever heard about that thing called fog?

ModernMech 8y ago
As an existence proof, people drive through fog every day. We prove that it's possible to take binocular visual data and convert that into a series of control signals that will propel a car through fog. Sure sometimes accidents happen, but every day thousands upon thousands of people safely navigate fog in e.g. San Francisco or London. I see no reason machines shouldn't be able to perform at least as well one day.
- nutjob2 8y ago
  > I see no reason machines shouldn't be able to perform at least as well one day. Assuming that day is infinitely far away, then you're right.
  - beat 8y ago
    Why? What's magical about human beings that a sufficiently advanced sensor and sufficiently advanced AI can't do the same responsive task? If there's magic in the human mind at all, it's the creative side of the mind. Driving isn't a creative act.
- mikepurvis 8y ago
  Machines will be (and already are) held to a much higher standard than human drivers— there are a lot of reasons for this, ranging from the emotional to the pragmatic. Just because thousands of people roll the dice every day driving in unsafe conditions does not mean that we should tolerate machines doing so.
  - spitfire 8y ago
    One note is that perhaps people roll the dice because they want to feel some control and forward momentum. But if you're sitting in the car, being autonomously driven somewhere will you be so impatient? I assume the car will give you an ETA, so you'll check the clock and go back to your book/social media. I'm okay with "slower, but smoother".

jpm_sd 8y ago

There is no upside to this approach. LIDAR is only getting cheaper, there is no reason not to use it.

oliveshell 8y ago

I’ll take the “over” on that bet any day of the week. It might not be 20 years, but it’ll be a friggin’ while. There are scenarios it’s possible to encounter on the road that humans don’t even necessarily know how to handle immediately. In proper, brutal, real-world testing, one very quickly enters the realm of problems that you’d need full-fledged general AI to reason through.