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Unless you live in an area with perfect weather, don't expect autonomous vehicles very soon. They have difficulty in heavy rain, snow, and ice.
by greedo 11y ago
Unless you live in an area with perfect weather, don't expect autonomous vehicles very soon. They have difficulty in heavy rain, snow, and ice.
- rogx76 11y agoBecause we humans do not in the exact same circumstances.
- krapp 11y agoIn the exact same circumstances, humans can adapt to and handle the difficulty, whereas autonomous car technology currently can't and doesn't.
- Someone1234 11y agoThat's a significant problem. So does Google only send their car out in good weather?
- enneff 11y agoThe cars are developed in California. The weather is great here almost all the time. The cars are still under development and inclement weather is an obvious thing the team must be thinking about. I fully expect, in time, that autonomous vehicles to drive more safely in bad weather than people. (They'll be more cautious, for one.)
- TwiztidK 11y agoAbsolutely. If you've ever driven though heavy snow, you know that you can barely see any of the road (no white or yellow lines) and lights are the only part of other cars that you can see. Signs and other traffic signals get completely covered with snow. People can barely drive in those conditions, I highly doubt that a self driving car could with current technology. Although I have high hopes for the future.
- deleted 11y ago[deleted]
- alooPotato 11y agoWhy would machines be worse than humans in bad weather if they are better than humans in good weather? Its not like our eyes are better than the machines cameras. If its because human drivers can better "build a mental model" of whats happening with limited visibility/data - that seems like the same problem that autonomous cars are designed to solve. Whats stopping autonomous cars from making progress in the bad weather arena? Is it just we haven't done enough miles in that weather and we need to train the ML some more?
- teraflop 11y agoYou're putting a lot of faith in the ability to solve a very difficult problem. Computer vision has made huge strides in recent years, but it's still far behind the capabilities of the human visual cortex. It's not just a matter of building a simple model and training it until it achieves arbitrarily high accuracy. ML encompasses a powerful set of tools, but it's not a magic black box that eats data and spits out AI. We don't yet know how the human brain processes images at a detailed level, and it's too complex of a system to optimize by brute-force. The best ML image processing systems still rely on a lot of pre-encoded assumptions, and require huge amounts of training data/computational resources, and don't perform as well as humans even on simple tasks. For now, autonomous vehicles "cheat" a lot by using sensor technologies like lidar and radar -- techniques that produce spatial data that can be interpreted more easily than raw imagery. That adds a lot to the hardware costs, but it's currently the only way we can make them perform acceptably well in real-world scenarios. And conditions that interfere with those technologies more severely, like fog or snow, are still crippling.
- JoeAltmaier 11y agoActually there's no reason to suppose that computer vision hasn't already exceeded the human capacity. After all, it has lidar and radar. Cheating or not, it has a very good result.
- mullen 11y agoPerfect! I live in San Diego, CA, so I can expect my autonomous car soon.