5 ms·

Does anyone with a better understanding about LIDAR vs camera approach to autonomous drivng explain how would Tesla handle such situation ?

xnx 5mo ago
Waymo has LIDAR and cameras, so it is better equipped for every situation.
- lizardking 5mo ago
  Unless the power is out https://abc7news.com/post/san-francisco-leaders-press-waymo-stalled-robotaxis-during-december-power-outage/18669520/ https://abc7news.com/post/san-francisco-leaders-press-waymo-...
  - xnx 5mo ago
    Kind of unrelated. That issue was due to a misguided effort to be cautious by having vehicles requesting human-review when they didn't really need it. Waymo fixed the issue by allowing the vehicles to operate in their normal, independent, mode.
  - whimsicalism 5mo ago
    part of the problem is that SFs traffic lights just turn off in a power outage, rather than flashing red battery power as I have seen in many other jurisdictions
- CSMastermind 5mo ago
  This seems tautological, but in practice, you might expect to see different results. Engineering hours are finite, so if they're spread across interpreting signals from two different sources, they might not go deep enough to make either one as good as it could be. Having your engineering resources more focused on a particular approach might actually yield better results. I say this as someone who's dealing with LiDAR + vision vs pure vision in a different domain, and at this point, I actually think our pure vision systems are better.
  - Caracas288 5mo ago
    More often than not, constraints refine and focus a project, rather than restricting it. It’s best to start work with as few variables as possible, and only add new ones when absolutely necessary; You make a lot more progress that way. For very complex things like AVs, it is critically important to keep the number of such variables down, since each acts on complexity & workload not as an addition but more like a quadratic, or worse—combinatorial explosion.
- cryptoegorophy 5mo ago
  What if they oppose each other? Which one do you trust?
  - jjjfjjgd 5mo ago
    Google ”Sensor fusion”.
    - red75prime 5mo ago
      Also google "sensitivity-specificity tradeoff." Initiating emergency braking when at least one sensor detects a pedestrian has the highest sensitivity, but the worst specificity. The real trolley problem of self-driving: how many spilled drinks and read-end collisions society is willing to tolerate to save one life.
tintor 5mo ago
LIDAR isn't helpful for water. Standing water behaves like a mirror on LIDAR.
- throwway120385 5mo ago
  Could you use a different spectrum of EM radiation to detect water? There are parts of the microwave band that attenuate the signal by absorption and I wonder if you could use that. The only clue a human driver has in that situation is in the visible spectrum. The lines of the road disappear from view, which can be challenging to see at night.
  - esseph 5mo ago
    In theory you could send different frequencies, but then you run afoul of all kinds of potential interference with other systems and other local regulations.
- amluto 5mo ago
  If the LIDAR can sense the road close enough to the front of the car, then it could estimate how far underwater the car is.
  - 0x457 5mo ago
    There are better ways to measure how far underwater the car is: https://www.landrover.com/ownership/off-road/wading-depths.html https://www.landrover.com/ownership/off-road/wading-depths.h..., this assumes you driving over something more or less flat underwater and that car is built for this. Here the goal is avoiding driving into the water in the first place.
- stevekemp 5mo ago
  This is one of the reasons why I'm suspicious of camera-only systems, here in Finland. Half the year there's a lot of snow and ice around. Which I imagine means most of the view is "white" and "shiny". Coupled with the dark winters it's gotta be a nightmare to deal with.
deleted 5mo ago
[deleted]
ollin 5mo ago
This is a HW4 Tesla on FSD 14.3.2 trying to drive into a lake five days ago (a la The Office): https://www.reddit.com/r/TeslaFSD/comments/1t9rl2u/fsd_tried_to_drive_me_into_a_lake_again/ https://www.reddit.com/r/TeslaFSD/comments/1t9rl2u/fsd_tried..., so I would not say Tesla has solved standing water yet. That said, FSD seems quite capable of routing around standing water in many cases (e.g. https://xcancel.com/planoken/status/2030754820462633031 https://xcancel.com/planoken/status/2030754820462633031, https://www.reddit.com/r/TeslaFSD/comments/1pw9f2m/fsd_navigates_around_partially_flooded_lane/ https://www.reddit.com/r/TeslaFSD/comments/1pw9f2m/fsd_navig..., https://xcancel.com/BLKMDL3/status/1991862465328779317 https://xcancel.com/BLKMDL3/status/1991862465328779317, https://xcancel.com/JVTacoma/status/2046313902749921638 https://xcancel.com/JVTacoma/status/2046313902749921638), so handling the remaining cases seems more like a model intelligence / data issue rather than a sensor limitation. Lidar beams generally bounce off mirrorlike surfaces without returning to the sensor, so I think all lidar would tell you about standing water is "there's something shiny/reflective within this region of the image", which you already know from cameras+headlights.

xnx 5mo ago

Waymo has LIDAR and cameras, so it is better equipped for every situation.

lizardking 5mo ago
Unless the power is out https://abc7news.com/post/san-francisco-leaders-press-waymo-stalled-robotaxis-during-december-power-outage/18669520/ https://abc7news.com/post/san-francisco-leaders-press-waymo-...
- xnx 5mo ago
  Kind of unrelated. That issue was due to a misguided effort to be cautious by having vehicles requesting human-review when they didn't really need it. Waymo fixed the issue by allowing the vehicles to operate in their normal, independent, mode.
- whimsicalism 5mo ago
  part of the problem is that SFs traffic lights just turn off in a power outage, rather than flashing red battery power as I have seen in many other jurisdictions
CSMastermind 5mo ago
This seems tautological, but in practice, you might expect to see different results. Engineering hours are finite, so if they're spread across interpreting signals from two different sources, they might not go deep enough to make either one as good as it could be. Having your engineering resources more focused on a particular approach might actually yield better results. I say this as someone who's dealing with LiDAR + vision vs pure vision in a different domain, and at this point, I actually think our pure vision systems are better.
- Caracas288 5mo ago
  More often than not, constraints refine and focus a project, rather than restricting it. It’s best to start work with as few variables as possible, and only add new ones when absolutely necessary; You make a lot more progress that way. For very complex things like AVs, it is critically important to keep the number of such variables down, since each acts on complexity & workload not as an addition but more like a quadratic, or worse—combinatorial explosion.
cryptoegorophy 5mo ago
What if they oppose each other? Which one do you trust?
- jjjfjjgd 5mo ago
  Google ”Sensor fusion”.
  - red75prime 5mo ago
    Also google "sensitivity-specificity tradeoff." Initiating emergency braking when at least one sensor detects a pedestrian has the highest sensitivity, but the worst specificity. The real trolley problem of self-driving: how many spilled drinks and read-end collisions society is willing to tolerate to save one life.

tintor 5mo ago

LIDAR isn't helpful for water. Standing water behaves like a mirror on LIDAR.

throwway120385 5mo ago
Could you use a different spectrum of EM radiation to detect water? There are parts of the microwave band that attenuate the signal by absorption and I wonder if you could use that. The only clue a human driver has in that situation is in the visible spectrum. The lines of the road disappear from view, which can be challenging to see at night.
- esseph 5mo ago
  In theory you could send different frequencies, but then you run afoul of all kinds of potential interference with other systems and other local regulations.
amluto 5mo ago
If the LIDAR can sense the road close enough to the front of the car, then it could estimate how far underwater the car is.
- 0x457 5mo ago
  There are better ways to measure how far underwater the car is: https://www.landrover.com/ownership/off-road/wading-depths.html https://www.landrover.com/ownership/off-road/wading-depths.h..., this assumes you driving over something more or less flat underwater and that car is built for this. Here the goal is avoiding driving into the water in the first place.
stevekemp 5mo ago
This is one of the reasons why I'm suspicious of camera-only systems, here in Finland. Half the year there's a lot of snow and ice around. Which I imagine means most of the view is "white" and "shiny". Coupled with the dark winters it's gotta be a nightmare to deal with.

deleted 5mo ago

[deleted]

ollin 5mo ago

This is a HW4 Tesla on FSD 14.3.2 trying to drive into a lake five days ago (a la The Office): https://www.reddit.com/r/TeslaFSD/comments/1t9rl2u/fsd_tried_to_drive_me_into_a_lake_again/ https://www.reddit.com/r/TeslaFSD/comments/1t9rl2u/fsd_tried..., so I would not say Tesla has solved standing water yet. That said, FSD seems quite capable of routing around standing water in many cases (e.g. https://xcancel.com/planoken/status/2030754820462633031 https://xcancel.com/planoken/status/2030754820462633031, https://www.reddit.com/r/TeslaFSD/comments/1pw9f2m/fsd_navigates_around_partially_flooded_lane/ https://www.reddit.com/r/TeslaFSD/comments/1pw9f2m/fsd_navig..., https://xcancel.com/BLKMDL3/status/1991862465328779317 https://xcancel.com/BLKMDL3/status/1991862465328779317, https://xcancel.com/JVTacoma/status/2046313902749921638 https://xcancel.com/JVTacoma/status/2046313902749921638), so handling the remaining cases seems more like a model intelligence / data issue rather than a sensor limitation. Lidar beams generally bounce off mirrorlike surfaces without returning to the sensor, so I think all lidar would tell you about standing water is "there's something shiny/reflective within this region of the image", which you already know from cameras+headlights.