5 ms·

"A lie", FSD as it stands right now is a lie. A few cars might be able to drive a few geofenced places, but no car anywhere can drive anywhere, even with perfec

"A lie", FSD as it stands right now is a lie. A few cars might be able to drive a few geofenced places, but no car anywhere can drive anywhere, even with perfect weather and visibility and I'd even wager no traffic or even no other cars at all. Our Subaru gives up steering if there's no olcar in front, on "suburban" and rural roads about 35% of the time. More on some roads, less on others. I cannot determine, while driving, the cause for half of the self driving disable occurrences. No fog line and a broken center for an intersection on a 1 lane road it'll shut off nearly every time. It's surprising when it doesn't. I've clocked nearly a half million miles on the road (I'll be there sometime in the next 9 months), and the range of technical ability you need to drive in just the US, no, scratch that, any given state or even county varies so much and potentially so often that FSD is just a lie to sell cars. I'm willing to upload a full hour drive touring a few parishes around here in my quite heavy Lexus, front and rear cameras, just to prove my point. I'd do it in the subaru but the dashcam isn't very good and also it's lineage is rally so it exaggerates how poor the roads are. My YouTube has dashcam footage of drives that I'm willing to bet no automated system could handle, even if it claimed to be "level 5". Driving after a storm or hurricane is another issue. I know the hazards in general and specifically for the areas I'd need to travel during or after an emergency. I cannot fathom the amount of storage and processing that would take, to have that for every location with roads. On board, in the car? Maybe in 20 years.

Dylan16807 1y ago
> I cannot fathom the amount of storage and processing that would take, to have that for every location with roads. On board, in the car? Maybe in 20 years. Doing some napkin math, with 4 million miles of road in the US, if you wanted to store 1KB of data per meter of road, hundreds of data points, you'd only need 7TB for the entire database. And the processing to make it shouldn't be anything special, should it? Collection would be hard.
- genewitch 1y ago
  > only [...] 7TB Currently that would probably cost ~$500 per car to implement based on retail pricing of 8TB SSDs. It would need to be updated constantly, too, with road closures, potholes, missing signage, construction. With an external GPS unit like a tomtom, they had radio receivers in the power cord that tuned to traffic frequencies, if available, and could route you around closures, construction, and the like, so you need a nationwide network to handle this. Cellphone won't cut it. Starlink might, but regardless, you need to add that radio and accoutrements to the BOM for each car. and i'm not talking about the processing of the dataset that gets put onto the 8TB SSD in the car; i am talking about the processing of the data on the 8TB SSD on the car while at speed. furthermore, i am fairly certain that it would take, on average, more than 1.6MB per mile to describe the road, road condition, hazards, etc. a shapefile of all roads in the US - that which gets one closer to knowing where the lanes are, how wide the shoulders are, etc is 616MB. and it's incomplete - i put in two roads near me with fairly unique names and neither are in the dataset. So your self driving car using these GIS datasets won't know those roads. I had an idea to put an atomicpi in my car, with two cameras. it has a bosch 9-dof sensor on the board, coupled with the cameras you can map road surface perturbations, hazards, and the like, which i believe will be much more than 1KB per meter, especially as you need "base" conditions and updates and current conditions (reported by the cars in front of you, ideally). the csv GIS dataset looks like this: >OBJECTID,ID,DIR,LENGTH,LINKID,COUNTRY,JURISCODE,JURISNAME,ROADNUM,ROADNAME,ADMIN,SURFACE,LANES,SPEEDLIM,CLASS,NHS,BORDER,Shape__Length > 568143,964990,0,0.07,02_36250355,2,02_39,Ohio,S161,DUBLIN GRANVILLE RD,State,Paved,4,88,3,7,0,0.000759951397761616 and i ran, for example `awk -F, '/PACIFIC COAST/ {sum += $4} END {print sum}' NTAD*.csv` and it spat out 79.04, which i think is a bit shorter than reality. Looks like the dataset i pulled is only "major roads" as well - but that doesn't explain 79.04 as the sum of lengths of all rows with "PACIFIC COAST" in them. It does show the total length of interstate 10 is 3986.55, which is roughly double what the actual length is (2460mi), so perhaps i'm just not understanding this dataset. Anyhow 600+ MB for just that sort of information (plus shapes) for only a really quite small subset of roads in the US. anyhow my thoughts are scattered, this input box is too small, and i'm not really arguing. Maybe it is possible, but it will raise the price thousands of dollars per auto, you need infrastructure (starlink will work) to update the cars, and so on. I'm prepared to admit i am wrong, but your comment didn't move the needle for me. also, just to be fun, which self driving car could manage this entire drive? https://www.youtube.com/watch?v=sNqFN7KeOYE https://www.youtube.com/watch?v=sNqFN7KeOYE
  - Dylan16807 1y ago
    If you want such constant updates that's tricky to distribute and hard to collect, but let's put that aside for a bit. I want to focus on the amount of data and how the car would use it. With $500 of SSD being nice and cheap. > i am talking about the processing of the data on the 8TB SSD on the car while at speed. I'm not worried about that. The actual driving takes such powerful computers that even if there was a petabyte of total data, the amount the car would have to process as it moves would be a trickle in comparison to what it's already doing. Max 50KB per 10 milliseconds. And obviously the data would by sorted by location so there's very little extra processing required. But you tell me, how many data points do you think you need per meter of road? I really don't think you need millimeter-level surface perturbations all the way across. Mapping the precise edges of the road and lanes should only need dozens of data points, 4 bytes each. And then you can throw a few more dozen at points inside the lanes to flesh it out. You can throw a hundred data points at each pothole without breaking a sweat. Measuring the surface texture in various ways and how it responds to weather is only going to take a handful of bytes per square meter, in a way that repeats a lot and is easy to compress. > 568143,964990,0,0.07,02_36250355,2,02_39,Ohio,S161,DUBLIN GRANVILLE RD,State,Paved,4,88,3,7,0,0.000759951397761616 That's an extremely inefficient format. Unnecessary object ids, repeating metadata over and over, way too many decimal places, and all stored as text. But even then, your database is so tiny compared to the size I suggested that I don't think we can extrapolate anything useful. Even if we 4x it or whatever to compensate for a lack of rural roads.
    - genewitch 1y ago
      Suffice to say that the 600MB just lets you draw the roads on a plane, it's like comparing an ascii art drawing of the road (from .csv/shp) to a digital still of the road (the amount of information you'd actually need). you absolutely cannot rely on "a couple of sensor [types]". I mentioned i have nearly a half million miles on the road. All of that prior experience influences my driving when i am driving someplace new. in that 8TB disk, you have to find a way to produce that "experience", except instead of my 0.5mm miles, you are talking about the aggregate "experience" of 0.5mm miles per road per unit of time (day for some places like I-10 through Los Angeles, month for others, maybe a year for some "rural" roads.) none of this has to do with visual or proprioception. It's knowing "every inch" of road. It's knowing how far i can leave the center of the lane if someone else crowds me or goes over the center divider, because the shoulder is soft through here because logging trucks have been exiting the forest onto the highway. It's knowing what part of I-605 floods - not the whole thing, some lanes, some places, and "flood" means 2+ inches of water on the road surface, hitting it at speed makes a tidal wave flying into other lanes. If someone hits that in front of you, you're blind for a couple of seconds minimum. If we want to have semi trucks be "FSD" it needs to know, for the traffic and other conditions, how fast to go and what gear to be in to climb each hill, and then the hazards that are over the hill - that a trucker would know. Where's the gravel bed on more mountainous passes? Or more simply, what time of day neighborhoods are more likely to have people approaching or going through / out of intersections, blind or otherwise. How many "bytes" is that information, times every neighborhood? If many cars brake at the same place, there's probably a reason, and that needs to be either in the dataset or updated somehow if conditions change. You ever used Waze and had a report of something on the road or a cop parked somewhere, and it's nowhere to be seen? And that's updated much more frequently than the radio-info on the GPS systems i referred to earlier. Some roads become impassable in the rain, some roads ice more readily. If this was easy/simple/solved, waymo et al would be bragging about it, the tech in their cars. Waymo (or the other one) specifically, because they cover less than 0.1% of road surfaces in the US, in some of the most maintained and heavily traveled corridors in the world. So, if anyone from a robotaxi company happens by and knows roughly how much storage is needed for <0.1% of the road surfaces in the US, then we could actually start to have this dialog in a meaningful way. Also i am unsure how much coverage robotaxis actually have in their service area. A "grid system" of roads makes mapping and aggregate data "simple", for sure. This reminded me a bit of the idea that somewhere in the US there's a database of every sms sent to or from US cellular phones. "it's just text; it'll compress well" - belies how much text there is, there. for reference, the map in my lexus is ~8GB, for the US. And that's just "shapes" and POI and knowing how the addressing works on each road. It doesn't know what lane i'm in, it doesn't track curves in the road effectively (the icon leaves the road while i'm driving quite often), and overpasses and the like confuse all GPS systems i've ever used - like in Dallas, TX where it's 4 layers high and parallel roads stacked. furthermore, just the road data on google maps for the nearest metro area to my house is 20MB. i have a recollection it goes real quick into hundreds of MB if you need to download maps for the swaths of areas where there is no cellphone reception, like areas in western Nevada. given 20MB for my metro, that's 40GB of just road shapes and addresses for the US, which is much more than the 600MB incomplete GIS files i downloaded. so we've moved from fencing 600MB "text" data; to the actual data needed by a GPS to give directions, 8000MB. Your claim is that a mere 1000x more data is enough to autonomously self-drive anywhere in the US, at any time of day or year, etc... you know who actually has this data and would know how big it is? Tesla.

Dylan16807 1y ago

> I cannot fathom the amount of storage and processing that would take, to have that for every location with roads. On board, in the car? Maybe in 20 years. Doing some napkin math, with 4 million miles of road in the US, if you wanted to store 1KB of data per meter of road, hundreds of data points, you'd only need 7TB for the entire database. And the processing to make it shouldn't be anything special, should it? Collection would be hard.

genewitch 1y ago
> only [...] 7TB Currently that would probably cost ~$500 per car to implement based on retail pricing of 8TB SSDs. It would need to be updated constantly, too, with road closures, potholes, missing signage, construction. With an external GPS unit like a tomtom, they had radio receivers in the power cord that tuned to traffic frequencies, if available, and could route you around closures, construction, and the like, so you need a nationwide network to handle this. Cellphone won't cut it. Starlink might, but regardless, you need to add that radio and accoutrements to the BOM for each car. and i'm not talking about the processing of the dataset that gets put onto the 8TB SSD in the car; i am talking about the processing of the data on the 8TB SSD on the car while at speed. furthermore, i am fairly certain that it would take, on average, more than 1.6MB per mile to describe the road, road condition, hazards, etc. a shapefile of all roads in the US - that which gets one closer to knowing where the lanes are, how wide the shoulders are, etc is 616MB. and it's incomplete - i put in two roads near me with fairly unique names and neither are in the dataset. So your self driving car using these GIS datasets won't know those roads. I had an idea to put an atomicpi in my car, with two cameras. it has a bosch 9-dof sensor on the board, coupled with the cameras you can map road surface perturbations, hazards, and the like, which i believe will be much more than 1KB per meter, especially as you need "base" conditions and updates and current conditions (reported by the cars in front of you, ideally). the csv GIS dataset looks like this: >OBJECTID,ID,DIR,LENGTH,LINKID,COUNTRY,JURISCODE,JURISNAME,ROADNUM,ROADNAME,ADMIN,SURFACE,LANES,SPEEDLIM,CLASS,NHS,BORDER,Shape__Length > 568143,964990,0,0.07,02_36250355,2,02_39,Ohio,S161,DUBLIN GRANVILLE RD,State,Paved,4,88,3,7,0,0.000759951397761616 and i ran, for example `awk -F, '/PACIFIC COAST/ {sum += $4} END {print sum}' NTAD*.csv` and it spat out 79.04, which i think is a bit shorter than reality. Looks like the dataset i pulled is only "major roads" as well - but that doesn't explain 79.04 as the sum of lengths of all rows with "PACIFIC COAST" in them. It does show the total length of interstate 10 is 3986.55, which is roughly double what the actual length is (2460mi), so perhaps i'm just not understanding this dataset. Anyhow 600+ MB for just that sort of information (plus shapes) for only a really quite small subset of roads in the US. anyhow my thoughts are scattered, this input box is too small, and i'm not really arguing. Maybe it is possible, but it will raise the price thousands of dollars per auto, you need infrastructure (starlink will work) to update the cars, and so on. I'm prepared to admit i am wrong, but your comment didn't move the needle for me. also, just to be fun, which self driving car could manage this entire drive? https://www.youtube.com/watch?v=sNqFN7KeOYE https://www.youtube.com/watch?v=sNqFN7KeOYE
- Dylan16807 1y ago
  If you want such constant updates that's tricky to distribute and hard to collect, but let's put that aside for a bit. I want to focus on the amount of data and how the car would use it. With $500 of SSD being nice and cheap. > i am talking about the processing of the data on the 8TB SSD on the car while at speed. I'm not worried about that. The actual driving takes such powerful computers that even if there was a petabyte of total data, the amount the car would have to process as it moves would be a trickle in comparison to what it's already doing. Max 50KB per 10 milliseconds. And obviously the data would by sorted by location so there's very little extra processing required. But you tell me, how many data points do you think you need per meter of road? I really don't think you need millimeter-level surface perturbations all the way across. Mapping the precise edges of the road and lanes should only need dozens of data points, 4 bytes each. And then you can throw a few more dozen at points inside the lanes to flesh it out. You can throw a hundred data points at each pothole without breaking a sweat. Measuring the surface texture in various ways and how it responds to weather is only going to take a handful of bytes per square meter, in a way that repeats a lot and is easy to compress. > 568143,964990,0,0.07,02_36250355,2,02_39,Ohio,S161,DUBLIN GRANVILLE RD,State,Paved,4,88,3,7,0,0.000759951397761616 That's an extremely inefficient format. Unnecessary object ids, repeating metadata over and over, way too many decimal places, and all stored as text. But even then, your database is so tiny compared to the size I suggested that I don't think we can extrapolate anything useful. Even if we 4x it or whatever to compensate for a lack of rural roads.
  - genewitch 1y ago
    Suffice to say that the 600MB just lets you draw the roads on a plane, it's like comparing an ascii art drawing of the road (from .csv/shp) to a digital still of the road (the amount of information you'd actually need). you absolutely cannot rely on "a couple of sensor [types]". I mentioned i have nearly a half million miles on the road. All of that prior experience influences my driving when i am driving someplace new. in that 8TB disk, you have to find a way to produce that "experience", except instead of my 0.5mm miles, you are talking about the aggregate "experience" of 0.5mm miles per road per unit of time (day for some places like I-10 through Los Angeles, month for others, maybe a year for some "rural" roads.) none of this has to do with visual or proprioception. It's knowing "every inch" of road. It's knowing how far i can leave the center of the lane if someone else crowds me or goes over the center divider, because the shoulder is soft through here because logging trucks have been exiting the forest onto the highway. It's knowing what part of I-605 floods - not the whole thing, some lanes, some places, and "flood" means 2+ inches of water on the road surface, hitting it at speed makes a tidal wave flying into other lanes. If someone hits that in front of you, you're blind for a couple of seconds minimum. If we want to have semi trucks be "FSD" it needs to know, for the traffic and other conditions, how fast to go and what gear to be in to climb each hill, and then the hazards that are over the hill - that a trucker would know. Where's the gravel bed on more mountainous passes? Or more simply, what time of day neighborhoods are more likely to have people approaching or going through / out of intersections, blind or otherwise. How many "bytes" is that information, times every neighborhood? If many cars brake at the same place, there's probably a reason, and that needs to be either in the dataset or updated somehow if conditions change. You ever used Waze and had a report of something on the road or a cop parked somewhere, and it's nowhere to be seen? And that's updated much more frequently than the radio-info on the GPS systems i referred to earlier. Some roads become impassable in the rain, some roads ice more readily. If this was easy/simple/solved, waymo et al would be bragging about it, the tech in their cars. Waymo (or the other one) specifically, because they cover less than 0.1% of road surfaces in the US, in some of the most maintained and heavily traveled corridors in the world. So, if anyone from a robotaxi company happens by and knows roughly how much storage is needed for <0.1% of the road surfaces in the US, then we could actually start to have this dialog in a meaningful way. Also i am unsure how much coverage robotaxis actually have in their service area. A "grid system" of roads makes mapping and aggregate data "simple", for sure. This reminded me a bit of the idea that somewhere in the US there's a database of every sms sent to or from US cellular phones. "it's just text; it'll compress well" - belies how much text there is, there. for reference, the map in my lexus is ~8GB, for the US. And that's just "shapes" and POI and knowing how the addressing works on each road. It doesn't know what lane i'm in, it doesn't track curves in the road effectively (the icon leaves the road while i'm driving quite often), and overpasses and the like confuse all GPS systems i've ever used - like in Dallas, TX where it's 4 layers high and parallel roads stacked. furthermore, just the road data on google maps for the nearest metro area to my house is 20MB. i have a recollection it goes real quick into hundreds of MB if you need to download maps for the swaths of areas where there is no cellphone reception, like areas in western Nevada. given 20MB for my metro, that's 40GB of just road shapes and addresses for the US, which is much more than the 600MB incomplete GIS files i downloaded. so we've moved from fencing 600MB "text" data; to the actual data needed by a GPS to give directions, 8000MB. Your claim is that a mere 1000x more data is enough to autonomously self-drive anywhere in the US, at any time of day or year, etc... you know who actually has this data and would know how big it is? Tesla.