[jpk]

My (tenuous) understanding is that the challenge with lidar isn't necessarily the cost of the sensor(s) but the bandwidth and compute required to meaningfully process the point cloud the sensors produce, at a rate/latency acceptable for driving. So the sensors themselves can be a few hundred bucks but what other parts of the system also need to be more expensive?

[fc417fc802]

That seems very unlikely to me. Automotive applications are already doing things like depth reconstruction based on multiple camera angles and ML inference in real time. Why should processing a depth point cloud be significantly more difficult than those things?

[jpk]

The basis for my understanding is a convo with a Google engineer who was working on self-driving stuff around 10-15 years ago -- not sure exactly when, and things have probably changed since then.

At the time they used just a single roof-mounted lidar unit. I remember him saying the one they were using produced point cloud data on the order of Tbps, and they needed custom hardware to process it. So I guess the point cloud data isn't necessarily harder to process than video, but if the sensor's angular resolution and sample rate are high enough, it's just the volume of data that makes it challenging.

[devmor]

This doesn’t seem to stop Teslas competition in self-driving cars from implementing it; and succeeding far more in safety and functionality while doing so.

[fragmede]

What is the cost of a human life worth?

edit: seriously, a $4,000 sensor and an extra, say, $3,000 for an upgraded computer module so your car can drive itself is just too much too afford?

[rogerrogerr]

Valuation of a statistical life is $5-10M, depending on who you ask[0].

So it’s too much to afford, or at least not singularly justifiable, unless more than 1 out of every 2000 cars kills someone in a way that would be prevented by LIDAR.

0: https://www.sciencedirect.com/science/article/pii/S109830152...