3 ms·

"Ignore" was probably the wrong word, but it is tricky. Remember that a vehicle is evaluating the environmental state at a given point in time to make decision

"Ignore" was probably the wrong word, but it is tricky. Remember that a vehicle is evaluating the environmental state at a given point in time to make decisions. Let's take the example of everyday driving on the freeway where you are following a car going the same speed as you. From your car's radar and camera perspective, the vehicle in front of you is stationary. It's not until you combine that information with additional information (your own velocity) and infer a more complicated state of affairs that you get a more complete picture. The camera and radar are both screaming "there's a stationary object right in front of us!", but you're still traveling at 60mph directly toward it. Combine that with the normal event of a garage wall or building directly in front of you while parking and we have three different "stationary object in front" situations that all have to be handled differently. In all three, the radar and camera are saying "stationary object ahead". But in the left-turn-with-wall situation you need to turn instead of stop. In the following-another-car situation you do nothing, and in the parking situation you need to stop instead of turn. And that's all without even starting to account for things like rain (opaque to some LIDAR and cameras = "we're literally crashing right now!" while radar reports nothing amiss). In order to decide what to do you have to pull in additional environment information, but then that's going to have similar caveats and conflicting reports to account for, so you need additional rules and information, etc. and now you've snowballed into a highly complex model with corner cases and potential bugs everywhere. If it was easy we would have had self-driving cars a decade ago.

mirimir 9y ago
There's some confusion about what "stationary" means. I was using the external reference frame. So I called road signs etc stationary. But in the vehicle's reference frame, road signs etc have closing velocity. Vehicles in front moving at the same speed aren't stationary in the external reference frame. They're stationary in the vehicle's reference frame. If one stops, though, it becomes stationary in the external reference frame, and has closing velocity in the vehicle's reference frame. Sorry to be pedantic.
- mdorazio 9y ago
  You're not being pedantic - it's an important distinction. That's why I've been putting "stationary" in quotes the whole time. An individual sensor has no concept of a reference frame, only the broader ADAS/autonomous system does. That's why acting on object detection is non-trivial - individual sensors report "object" with no context and it's up to fallible algorithms to make sense of often conflicting information.
Dylan16807 9y ago
Don't make it sound like subtracting your own velocity is anything but trivial. Your whole first paragraph is playing semantics about the definition of the word "stationary". If the camera says you have zero relative velocity, that is not it saying "stationary", and you are not ignoring a "stationary" object. > Combine that with the normal event of a garage wall or building directly in front of you while parking and we have three different "stationary object in front" situations that all have to be handled differently. In all three, the radar and camera are saying "stationary object ahead". But in the left-turn-with-wall situation you need to turn instead of stop. In the following-another-car situation you do nothing, and in the parking situation you need to stop instead of turn. If the object is stationary, you turn-or-stop. If it's another car, it's really easy to measure that it's not stationary. If your sensors can't figure out the distance or velocity for multiple seconds in a row, your equipment should not be allowed to drive. > highly complex model with corner cases and potential bugs everywhere That's all in object detection, though. And none of that noise looks at all like a solid object at a specific location. > If it was easy we would have had self-driving cars a decade ago. I disagree. Even if you have a system that competently avoids stationary-object collisions, you're nowhere near a full self-driving car. And while the overall problem of avoiding collisions has hard parts, none of the hard parts are in the "What do we do about a stationary object?" logic.
- mdorazio 9y ago
  Subtracting your own velocity from what? I've been talking about individual sensor reporting with conflicting information and the complexity of decision making that results. A radar return from a rear bumper at relative zero miles an hour is exactly the same whether the car is actually in motion or not. Reference frame and velocity relative to the ground is up to your software algorithms to determine, not the sensors, and I've been trying to explain why that's non-trivial and "stationary" is always relative to something. You seem to be treating the entire system as an always-in-consensus whole, which it isn't. I feel like we're just going in circles here. I could keep giving you examples of cases where sensors will report conflicting information that makes decisions like turn or stop difficult or false-positive prone, and you'll keep insisting that it's just object recognition and you should always know to turn or stop. I'll stop here and stand by my original point - sensor limitations and immature algorithms are the reason for issues like the ones Autopilot has; completely preventing these issues is not straight forward.

mirimir 9y ago

There's some confusion about what "stationary" means. I was using the external reference frame. So I called road signs etc stationary. But in the vehicle's reference frame, road signs etc have closing velocity. Vehicles in front moving at the same speed aren't stationary in the external reference frame. They're stationary in the vehicle's reference frame. If one stops, though, it becomes stationary in the external reference frame, and has closing velocity in the vehicle's reference frame. Sorry to be pedantic.

mdorazio 9y ago
You're not being pedantic - it's an important distinction. That's why I've been putting "stationary" in quotes the whole time. An individual sensor has no concept of a reference frame, only the broader ADAS/autonomous system does. That's why acting on object detection is non-trivial - individual sensors report "object" with no context and it's up to fallible algorithms to make sense of often conflicting information.

Dylan16807 9y ago

Don't make it sound like subtracting your own velocity is anything but trivial. Your whole first paragraph is playing semantics about the definition of the word "stationary". If the camera says you have zero relative velocity, that is not it saying "stationary", and you are not ignoring a "stationary" object. > Combine that with the normal event of a garage wall or building directly in front of you while parking and we have three different "stationary object in front" situations that all have to be handled differently. In all three, the radar and camera are saying "stationary object ahead". But in the left-turn-with-wall situation you need to turn instead of stop. In the following-another-car situation you do nothing, and in the parking situation you need to stop instead of turn. If the object is stationary, you turn-or-stop. If it's another car, it's really easy to measure that it's not stationary. If your sensors can't figure out the distance or velocity for multiple seconds in a row, your equipment should not be allowed to drive. > highly complex model with corner cases and potential bugs everywhere That's all in object detection, though. And none of that noise looks at all like a solid object at a specific location. > If it was easy we would have had self-driving cars a decade ago. I disagree. Even if you have a system that competently avoids stationary-object collisions, you're nowhere near a full self-driving car. And while the overall problem of avoiding collisions has hard parts, none of the hard parts are in the "What do we do about a stationary object?" logic.

mdorazio 9y ago
Subtracting your own velocity from what? I've been talking about individual sensor reporting with conflicting information and the complexity of decision making that results. A radar return from a rear bumper at relative zero miles an hour is exactly the same whether the car is actually in motion or not. Reference frame and velocity relative to the ground is up to your software algorithms to determine, not the sensors, and I've been trying to explain why that's non-trivial and "stationary" is always relative to something. You seem to be treating the entire system as an always-in-consensus whole, which it isn't. I feel like we're just going in circles here. I could keep giving you examples of cases where sensors will report conflicting information that makes decisions like turn or stop difficult or false-positive prone, and you'll keep insisting that it's just object recognition and you should always know to turn or stop. I'll stop here and stand by my original point - sensor limitations and immature algorithms are the reason for issues like the ones Autopilot has; completely preventing these issues is not straight forward.