[esafak]

> Two is kinda useless: if they disagree, which is right?

They don't work by merely taking a straw poll. They effectively build the joint probability distribution, which improves accuracy with any number of sensors, including two.

> You're on a two lane road. Your vision system tells you there's a pedestrian in your lane. Your LIDAR says the pedestrian is actually in the other lane. There's enough time for a lane change, but not to stop.

Any realistic system would see them long before your eyes do. If you are so worried, override the AI in the moment.

[AnIrishDuck]

> They don't work by merely taking a straw poll. They effectively build the joint probability distribution, which improves accuracy with any number of sensors, including two.

Lots of safety critical systems actually do operate by "voting". The space shuttle control computers are one famous example [1], but there are plenty of others in aerospace. I have personally worked on a few such systems.

It's the simplest thing that can obviously work. Simplicity is a virtue when safety is involved.

You can of course do sensor fusion and other more complicated things, but the core problem I outlined remains.

> If you are so worried, override the AI in the moment.

This is sneakily inserting a third set of sensors (your own). It can be a valid solution to the problem, but Waymo famously does not have a steering wheel you can just hop behind.

This might seem like an edge case, but edge cases matter when failure might kill somebody.

1. https://space.stackexchange.com/questions/9827/if-the-space-...

[mafuy]

Voting is used when the systems are equivalent, e.g. 3 identical computers, where one might have a bit flip.

This is completely different from systems that cover different domains, like vision and lidar.

[sfifs]

Isn't the historical voting pattern something more of a legacy thing dictated by limited edge compute of the past vs necessarily a best practice.

I see in many domains a tendency to oversimplify decision making algorithms for human understanding convenience (eg vote rather that develop a joint probability distribution in this case, supply chain and manufacturing in particular seem to love rules of thumb) rather than use better algorithms that modern compute enables higher performance, safety etc

[AnIrishDuck]

This is an interesting question where I do not know the answer.

I will not pretend to be an expert. I would suggest that "human understanding convenience" is pretty important in safety domains. The famous Brian Kernighan quote comes to mind:

> Everyone knows that debugging is twice as hard as writing a program in the first place. So if you're as clever as you can be when you write it, how will you ever debug it?

When it comes to obscure corner cases, it seems to me that simpler is better. But Waymo does seem to have chosen a different path! They employ a lot of smart folk, and appear to be the state of the art for autonomous driving. I wouldn't bet against them.

[ImPostingOnHN]

Seatbelt mechanisms are complicated, airbag timing is complicated, let's just do away with them entirely in the name of simplicity?

No, when it comes to not killing people, I'd say that safer is usually better.

Remember the core function of the system is safety, simplicity is nice to have, but explicitly not as important.

That said, beware of calling something 'complicated' just because you don't understand it, especially if you don't have training and experience in that thing. What's more relevant is whether the people building the systems think it is too complicated.

[qingcharles]

We're trying to build vehicles that are totally autonomous, though. How do you grab the wheel of the new Waymos without steering wheels? Especially if you're in the back seat staring at Candy Crush.

[esafak]

Waymos are safer, and drive more defensively than humans. There is no way a Waymo is going to drive aggressively enough to get itself into the trolley problem.