General > General Technical Chat
Electric car for £9500?
Siwastaja:
--- Quote from: tggzzz on October 12, 2023, 10:50:16 am ---I think you'll find there are cases where LIDAR is better than cameras, and vice versa. "Sensor fusion" has long been an interesting and important topic.
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Spot on. I don't believe in the ability of doing reliable obstacle detection and emergency braking without combining at least two very different types of data source, vision and some sort of distance measurement (stereo vision does not count); human-like vision plus a "superhuman" one. It's sad to see how tech companies see all the buzz in trying to replicate very complex human systems like gigapixel vision and gazillion-neuron NNs, when they could assist these worse-than-human replicas with some superhuman skills like ultrasonic, radar, LIDAR, etc., pretty easily!
nctnico:
--- Quote from: Siwastaja on October 12, 2023, 05:13:02 pm ---
--- Quote from: tggzzz on October 12, 2023, 10:50:16 am ---I think you'll find there are cases where LIDAR is better than cameras, and vice versa. "Sensor fusion" has long been an interesting and important topic.
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Spot on. I don't believe in the ability of doing reliable obstacle detection and emergency braking without combining at least two very different types of data source, vision and some sort of distance measurement (stereo vision does not count); human-like vision plus a "superhuman" one. It's sad to see how tech companies see all the buzz in trying to replicate very complex human systems like gigapixel vision and gazillion-neuron NNs, when they could assist these worse-than-human replicas with some superhuman skills like ultrasonic, radar, LIDAR, etc., pretty easily!
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Throwing more sensors at a problem is not a solution in itself. The key problem to solve is to determine when the sensor data is correct and when not. That will take most of the computational power.
For example: In the early 2000's I worked at a research institute where one of my ongoing projects involved an instrumented car which was used for research into how people drive a car. This had a lidar for measuring distance between the car in front and a scanning sensor to measure the distance to the line on the side of the road. When I first started people had to sort through the data manually to get rid of pieces of data that where invalid. That was a lot of work so I automated it through software. One of the problems with the Lidar was that it would pick up trees or signs when driving through corners so I set a limit on the valid distance based on speed / steer rotation. The line detector was also good at detecting puddles with water. So I created an algorithm that looked for a line that was a) wide enough and b) followed the general distance between the car and the line. A car won't jump 25cm left/right in less than 0.1 seconds.
coppice:
--- Quote from: nctnico on October 12, 2023, 05:53:33 pm ---Throwing more sensors at a problem is not a solution in itself. The key problem to solve is to determine when the sensor data is correct and when not. That will take most of the computational power.
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Why do you think that? Do you have an reference models to base that on? Everything I've ever seen where results of sensing are solid and reliable use some form of sensor fusion specifically to resolve which data is correct. Biological systems do this to an extreme. Our own senses are very easy to fool in isolation, while the fused set works quite well, Most illusions are based on the senses not being able to fuse as they would otherwise do. There is hardly anything we get consistently right with just one sense. Good solid science and engineering work almost always relies on looking at things in multiple ways to resolve ambiguities.
nctnico:
--- Quote from: coppice on October 12, 2023, 06:00:31 pm ---
--- Quote from: nctnico on October 12, 2023, 05:53:33 pm ---Throwing more sensors at a problem is not a solution in itself. The key problem to solve is to determine when the sensor data is correct and when not. That will take most of the computational power.
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Why do you think that? Do you have an reference models to base that on? Everything I've ever seen where results of sensing are solid and reliable use some form of sensor fusion specifically to resolve which data is correct. Biological systems do this to an extreme. Our own senses are very easy to fool in isolation, while the fused set works quite well, Most illusions are based on the senses not being able to fuse as they would otherwise do. There is hardly anything we get consistently right with just one sense. Good solid science and engineering work almost always relies on looking at things in multiple ways to resolve ambiguities.
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That is exactly what I wrote...
tszaboo:
--- Quote from: nctnico on October 11, 2023, 01:30:53 pm ---
--- Quote from: tom66 on October 07, 2023, 09:08:12 pm ---Just on the way back from London my ID.3 perceived "something" (I've no idea what) on the M25 as a 100 mph speed limit sign and set the ACC to 100 mph. I would have thought the software would be smart enough to know the maximum legal limits for certain countries...
I am tempted to attach an OBD11 and code out a lot of these "safety" functions, they're not ready for prime time. The worst one is lane centering on badly marked rural roads, it likes to ditchfind, so you have to be quite firm with the steering wheel to override it.
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Volkswagen... what do you expect? A couple of years ago I rented a Peugeot which also had automatic speed limit reading. It failed pretty bad while driving in France. Go figure.
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People reported this driving a Lexus.
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