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Self Driving Uber Fatality - Thread II 8
- Thread starter drawoh
- Start date
- Thread starter
- #101
GregLocock,
I agree. If you are responsible for your robot not causing accident, keeping it well within its limits is one of your strategies. Shutting down on a country road way out in the middle of now where sounds like a disaster. Choosing to not operate at all in adverse conditions like ice storms is a better idea.
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JHG
I agree. If you are responsible for your robot not causing accident, keeping it well within its limits is one of your strategies. Shutting down on a country road way out in the middle of now where sounds like a disaster. Choosing to not operate at all in adverse conditions like ice storms is a better idea.
--
JHG
RoopinderTara
Mechanical
Technology vs Humans. Engineers Seek Answers in Uber’s Fatal Self Driving Car Accident, article in Engineering.com
Roopinder Tara
Director of Content
ENGINEERING.com
Roopinder Tara
Director of Content
ENGINEERING.com
While "Operating at frequencies outside the visible spectrum, LiDAR should have given the Uber vehicle a full “360 degree 3 dimensional scan of the environment,”" isn't technically incorrect, most people would use "wavelengths," instead of "frequencies" as light is more typically referred to as wavelengths.
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"(light safe, infrared)"
should be (eye-safe, infrared)
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should be (eye-safe, infrared)
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I have read all the posts on why lidar and the software from everyone my problem is a simple one every new component fitted to a motor vehicle that is released to the public has been tested in the military or in a motor-racing series ABS, traction control, fuel injection safety cells if the race teams with their budgets and their safety protocols will not have it why should the public look it would save Mercedes Benz $50m that they pay Louis Hamilton per year. Have the cars racing around the track all wanting to be first and see what happens then? the race track is the best way to test look at the DARPA competition a few years back they have not got any better until the electronics understand death they have no concept of self-preservation and if we give them that concept they will understand what the off switch is computers and all electronics work on garbage in garbage out if they the garbage is not what they are expecting they have no contingencies programmed in the human has over 60 million years of knowledge from the day we are born to keep alive computers do not have that so no self-driving car should be on the road until it has had proper testing in closed enviroments with all and any thing that can happen even with autopilot on aircraft they have a pilot and they are flying in free air nothing to hit at 35,000 feet except Mt Everest ha ha just think how many times have you had to restart your phone? try restarting a car when it freezes heading towards a cliff at 100kph, not for me thank you very much
I fail to see your point. Racing cars don't need AI, so why would they kill their aerodynamics and add weight to vehicles that are scrapping for every fraction of a CD they can carve off a car body and are driving in a single lane that's about 35 ft wide?
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MacGyverS2000
Electrical
clough69, please use proper punctuation (commas are missing all over the place). I can't tell where one thought ends and the next begins... makes it very difficult to read.
Dan - Owner
Dan - Owner
- Thread starter
- #109
IRstuff,
If the car has LiDAR and a robot, you can save 100-250lb of the driver.![[smile]](/data/assets/smilies/smile.gif "[smile] [smile]")
The only problem I see with LiDAR in car racing is it that its limited range limits your speed. Otherwise, you have a controlled environment, lacking bicycles, children and Bambi and Bullwinkle. If all the cars are robots, there are no ethical issues about hitting stuff. Battlebots could be a whole lot of fun, at least until the robot overlords take over and accuse us of murder.
The big problem facing a robot car is traffic. Traffic is unpredictable. Robot traffic will provide all sorts of non-specular reflection of LiDAR wavelengths that your LiDAR will have to filter out.
--
JHG
If the car has LiDAR and a robot, you can save 100-250lb of the driver.
The only problem I see with LiDAR in car racing is it that its limited range limits your speed. Otherwise, you have a controlled environment, lacking bicycles, children and Bambi and Bullwinkle. If all the cars are robots, there are no ethical issues about hitting stuff. Battlebots could be a whole lot of fun, at least until the robot overlords take over and accuse us of murder.
The big problem facing a robot car is traffic. Traffic is unpredictable. Robot traffic will provide all sorts of non-specular reflection of LiDAR wavelengths that your LiDAR will have to filter out.
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JHG
The whole point of human drivers in car racing is the humans. Otherwise, it's less entertaining than a video game movie.
"Robot traffic will provide all sorts of non-specular reflection of LiDAR wavelengths that your LiDAR will have to filter out"
Solutions already exist for things like that; that's how rolling code garage door openers came to be.
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"Robot traffic will provide all sorts of non-specular reflection of LiDAR wavelengths that your LiDAR will have to filter out"
Solutions already exist for things like that; that's how rolling code garage door openers came to be.
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BridgeSmith
Structural
"Robot traffic will provide all sorts of non-specular reflection of LiDAR wavelengths that your LiDAR will have to filter out"
"Solutions already exist for things like that; that's how rolling code garage door openers came to be."
Not really the same thing. LIDAR uses millions of laser beam pulses bouncing back from objects. What happens when there are several LIDAR systems operating in the same area, all bouncing laser beams off of their surroundings? How does each LIDAR sort out its laser beam reflections from the others?
"Solutions already exist for things like that; that's how rolling code garage door openers came to be."
Not really the same thing. LIDAR uses millions of laser beam pulses bouncing back from objects. What happens when there are several LIDAR systems operating in the same area, all bouncing laser beams off of their surroundings? How does each LIDAR sort out its laser beam reflections from the others?
The main factor in lidar is the narrow field of view of the receivers and the narrow time they are expecting to have a signal return. There is a similar problem in flash photography where a crowd is taking pictures. It is possible to have two or more flashes go off during the exposure, but it is relatively rare and subsequent images aren't likely to have the same problem; this is the case where the exposure was 1/60th to 1/30th of a second. The duration of exposure for lidar is much lower.
One of the bigger problems is for microwave systems that have much larger viewing angles.
I suppose the ultimate answer will be what Ethernet did for communications over co-ax. Each Ethernet adapter would listen for any ongoing traffic and would start transmitting when it was clear. If two adapters started at the same time the conflict would be detected and they would stop for a random interval before retrying. This might be milliseconds of delay, so just a few inches of vehicle travel.
One of the bigger problems is for microwave systems that have much larger viewing angles.
I suppose the ultimate answer will be what Ethernet did for communications over co-ax. Each Ethernet adapter would listen for any ongoing traffic and would start transmitting when it was clear. If two adapters started at the same time the conflict would be detected and they would stop for a random interval before retrying. This might be milliseconds of delay, so just a few inches of vehicle travel.
The field of view of the receivers are sized specifically for the ranges and scan rates on something like the HDL64, so it's on the order of milliradians. Interference requires another laser hitting essentially the exact same spot that your laser hit at exactly (within TWO microseconds) the same time. Despite claims of dozens of lidars interfering, realistically, it'll be on the order of 6. In, say, bumper to bumper traffic, distances are reduced, and masking by adjacent cars prevent the cars behind you from hitting most things in front of you. In sparse traffic distances are increased, but there are fewer cars emitting.
Moreover, as I stated, there are a variety of existing solutions to co-channel interference, such the pseudo-random number codes used on GPS, or the Tri-Service code used for laser designation systems such as the Apache Target Acquisition and Designation Systems (TADS). As you might imagine, if you fired your Hellfire missile at a target you designated, you wouldn't want it to get distracted by someone else's laser designation for their own Hellfire. Which is why there are hundreds of different codes that Allied forces can use and not interfere with each other. Additionally, the Tri-Service code that the Hellfire uses also has a rolling code that's comparable to garage door opener rolling codes called Pulse Interval Modulation (PIM) codes. There are billions of possible PIM codes. The receiver basically uses a temporal matched filter to look for the code that it's programmed for, and ignores other pulses from other emitters with different codes.
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Moreover, as I stated, there are a variety of existing solutions to co-channel interference, such the pseudo-random number codes used on GPS, or the Tri-Service code used for laser designation systems such as the Apache Target Acquisition and Designation Systems (TADS). As you might imagine, if you fired your Hellfire missile at a target you designated, you wouldn't want it to get distracted by someone else's laser designation for their own Hellfire. Which is why there are hundreds of different codes that Allied forces can use and not interfere with each other. Additionally, the Tri-Service code that the Hellfire uses also has a rolling code that's comparable to garage door opener rolling codes called Pulse Interval Modulation (PIM) codes. There are billions of possible PIM codes. The receiver basically uses a temporal matched filter to look for the code that it's programmed for, and ignores other pulses from other emitters with different codes.
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GregLocock
Automotive
Isn't it amazing that all these FUD ideas still keep cropping up on a professional forum and presented as "OMG I'm the first person to have ever thought of this".
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Greg Locock
New here? Try reading these, they might help FAQ731-376
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GregLocock
Automotive
Your brain runs at about 0.2 ms cycle time (ie 5000 Hz). Where do you get 1 MHz from?
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Greg Locock
New here? Try reading these, they might help FAQ731-376
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New here? Try reading these, they might help FAQ731-376
My son pointed this out...
"After this training period, all of the subjects were asked to make quick decisions in several tasks designed by the researchers. In the tasks, the participants had to look at a screen, analyze what was going on, and answer a simple question about the action in as little time as possible (i.e. whether a clump of erratically moving dots was migrating right or left across the screen on average).
In order to make sure the effect wasn’t limited to just visual perception, the participants were also asked to complete an analogous task that was purely auditory.
The action game players were up to 25 percent faster at coming to a conclusion and answered just as many questions correctly as their strategy game playing peers.
“It’s not the case that the action game players are trigger-happy and less accurate: They are just as accurate and also faster,” says Daphne Bavelier. “Action game players make more correct decisions per unit time. If you are a surgeon or you are in the middle of a battlefield, that can make all the difference.”
The neural simulations shed light on why action gamers have augmented decision making capabilities.
People make decisions based on probabilities that they are constantly calculating and refining in their heads, Bavelier explains. The process is called probabilistic inference."
Dik
"After this training period, all of the subjects were asked to make quick decisions in several tasks designed by the researchers. In the tasks, the participants had to look at a screen, analyze what was going on, and answer a simple question about the action in as little time as possible (i.e. whether a clump of erratically moving dots was migrating right or left across the screen on average).
In order to make sure the effect wasn’t limited to just visual perception, the participants were also asked to complete an analogous task that was purely auditory.
The action game players were up to 25 percent faster at coming to a conclusion and answered just as many questions correctly as their strategy game playing peers.
“It’s not the case that the action game players are trigger-happy and less accurate: They are just as accurate and also faster,” says Daphne Bavelier. “Action game players make more correct decisions per unit time. If you are a surgeon or you are in the middle of a battlefield, that can make all the difference.”
The neural simulations shed light on why action gamers have augmented decision making capabilities.
People make decisions based on probabilities that they are constantly calculating and refining in their heads, Bavelier explains. The process is called probabilistic inference."
Dik
Comparing clock rate to brains is a bit of a miss. Brains operate on massive parallel processing by pre-programming general responses. There is a maximum speed at which a response can happen based on an input, but the huge number of parallels can be extremely complex. I've come across articles similar to the gamers; one was that baseball players hit balls more frequently than non-players. Experiments could find no special speed to the way their brains or muscles worked; what made the difference is that the players were predicting where the ball would be based on the kinematics of the pitcher before the ball was released, there being too little time to observe the ball on the way to the mound. A similar experiment was run on chess masters who could memorize board positions given only a glance. It turned out this only worked when the positions were from realizable game states. If the pieces were placed in locations that could not be part of a game (pawns in all four corners, perhaps) the chess masters were just as poor as anyone else. They weren't memorizing the positions; they seemed to recreate the entire match required to get to those positions based on memories formed from the tens of thousands of games already played.
One of the things that brains seem to do is to create massive 3D and 4D simulations. I have from time to time, needed to get a glass I've left on a table but don't care to turn on a light. Even though I've left the room, remembered I wanted the glass, and come back to pitch darkness, I can bring my hand to with 1/4 of an inch centered on the glass. And I can do that because I have a simulation of the entire path I took and the table and the glass and the memory of where I last put the glass down.
Getting a data structure that is suitable for that would go a long way to making robotic driving a reality.
What's amazing is that this process has to be enabled in some pretty small animals. Small birds can build up a 4D simulation to allow them to fly at fair speeds through forest, avoiding trees and vines based on stereoscopic vision. Even wasps and bees have some location memory - for a couple of years I had cicada killers drilling holes in the back yard and if I moved a leaf a few inches from the burrow they would have difficulty finding their latest hole, scanning back and forth to reacquire the position. They did, because leaves move, so they are prepared. (Cicada killers are cool, and completely harmless, but look like they could kill.)
One of the things that brains seem to do is to create massive 3D and 4D simulations. I have from time to time, needed to get a glass I've left on a table but don't care to turn on a light. Even though I've left the room, remembered I wanted the glass, and come back to pitch darkness, I can bring my hand to with 1/4 of an inch centered on the glass. And I can do that because I have a simulation of the entire path I took and the table and the glass and the memory of where I last put the glass down.
Getting a data structure that is suitable for that would go a long way to making robotic driving a reality.
What's amazing is that this process has to be enabled in some pretty small animals. Small birds can build up a 4D simulation to allow them to fly at fair speeds through forest, avoiding trees and vines based on stereoscopic vision. Even wasps and bees have some location memory - for a couple of years I had cicada killers drilling holes in the back yard and if I moved a leaf a few inches from the burrow they would have difficulty finding their latest hole, scanning back and forth to reacquire the position. They did, because leaves move, so they are prepared. (Cicada killers are cool, and completely harmless, but look like they could kill.)
- Thread starter
- #119
IRstuff said:
If your garage door opener takes a full second to identify your controller, you won't notice. If I am using a laser to paint a target for my Hellfire missile, is there any reason to pulse the laser other than to provide a unique signature.
In my analysis above, the LiDAR is scanning at 10Hz, and the laser is firing at
You are looking at 150,000 spots every scan. Given that number, there is a high probability you will see some laser spots from the car next to you.
--
JHG
The gate-time for a single receiver is 2 microseconds after pulse launch. Everything outside that time period is nonexistent and therefore irrelevant. Each receiver's "spot" is only active for 2 us a maximum of 20 times a second.
Bear in mind that this is not like RF co-channel interference; in order for anything to happen at all, two lidars must hit exactly the same spot within 2 us of each other to have anything happen at all. Assuming the 4E-5 duty cycle as a random probability, the probability of both occurring simultaneously is essentially on the order of 1.6E-9, which means that two systems would have to be scanning the same area for hours to have any realistic probability of interfering.
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Bear in mind that this is not like RF co-channel interference; in order for anything to happen at all, two lidars must hit exactly the same spot within 2 us of each other to have anything happen at all. Assuming the 4E-5 duty cycle as a random probability, the probability of both occurring simultaneously is essentially on the order of 1.6E-9, which means that two systems would have to be scanning the same area for hours to have any realistic probability of interfering.
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