What's becoming clear is that the self-driving car industry will be the car industry. Autonomous driving equipment may come from suppliers, but they'll just be suppliers to the automakers. That's not a great place to be; the margins are low and suppliers are totally under the thumb of the automakers.
Volvo, which will deploy 100 self driving cars with actual customers in Gothenberg, Sweden in 2017, is way ahead on the user interface.[2] Volvo takes the firm position that, in autonomous mode, the driver is not required to pay attention at all, and if something goes wrong, it's Volvo's problem. They have redundant sensors, actuators, and computers.
Volvo is also way ahead on ads for self-driving.[3]
[1] http://www.volvocars.com/intl/about/our-innovation-brands/in...
But I wonder about the snow though. How does the car know where to go when there are no identifying lane features? Maybe its not as hard of a problem as I believe it to be?
For substantially less crazy conditions, you can infer where the lanes would be by (a) looking at the spots of the road you can see, (b) prior knowledge of the road from experience, and (c) looking at oncoming cars and the flow of traffic, and driving in a way that doesn't surprise them. Though it's likely the case that you shouldn't be driving in these conditions anyway.
You mean carefully get to the nearest settlement as soon as possible? Some of these storms can last for days at a time. Stopping to wait it out in the middle of nowhere, especially if you don't have a full tank of fuel to keep the car warm for extended periods, is a pretty scary situation.
While I think it's plausible to teach a self-driving car to drive in snow (like I do, generally following in the tracks of the cars ahead of me), I honestly think this is one of the best justifications that cars should continue to have steering wheels and pedals: Because automated snow driving is going to take a lot longer to become a solved problem than fair weather driving.
These kinds of extreme situations are scary, but that's what insurance is for.
Everyone is worried about how we get autonomous driving that's perfect in every situation, but that's not how automation works. You just have to automate the common case so a small number of humans can focus on the corner cases.
We are? I went up the comment chain again and still did not get that impression the second time around. What statement in particular gave you that idea?
> These kinds of extreme situations are scary, but that's what insurance is for.
Like... life insurance?
> You just have to automate the common case so a small number of humans can focus on the corner cases.
If I'm going to be sitting in the car anyway, I can drive it in those conditions, assuming the vehicle allows me to. However, Google has stated before that it is unlikely that they will release a car that needs to be taken over by human drivers. It's all or nothing for them.
Anyways, if this is true, it's a grim future then. Radar is incredibly trivial to interfere with.
One is the basic "environmental" interference with competing radar signals from other devices. Imagine how much more complicated this gets when a majority of competing traffic is likewise equipped.
But the other risk, which seems to be mostly ignored thus far, is sabotage. Can you design a system that is hardened not only against stray competing EMR but also against attempts to hack or vandalize your system into misbehavior or malfunction? For example, consider a terrorist plot. Or even a smart neighborhood crazy who wants the neighborhood kids off his lawn and neighborhood traffic to stop during his midday nap. Or, a British organized crime gang using stopped traffic to cover an escape[0].
This would be very difficult to train with ML, however. I'm sure there are other downsides I'm not thinking of
It uses many kinds of sensors. Yes I know about clutter, I've spent quite a lot of time in the radar industry. But by combining data from radars of multiple wavelengths, it becomes pretty feasible. Though yes, difficult.
We need to fundamentally redesign our road systems to accommodate self driving cars. That might happen... in 50-100 years...after we address the already crumbling infrastructure we have. For perfect, sunny conditions, like the roads in Nevada all these self driving startups are doing their testing, with straight flat landscapes, I am sure the tech can work fine. Rest of the country, maybe not so much.
Radar clutter, attenuation, penetration, etc are all affected by wavelengths. By using multiple frequencies, you can get a better idea of what is and isn't really there. As far as interference, there are ways to filter out noise. The car presumably knows how fast it is going. Therefor, it can do doppler filtering on the received waves. IE... car knows it sent waves at 50 GHz and is traveling at 60 mph. It knows to expect a response at ~54 GHz from the front and 50 GHz from the side.
For tracking objects, you can use a pulse-doppler radar [0] to get both range and rate information.