Most practical navigation systems employ some form of sensor fusion. It’s more the norm than not. I’m sure even Tesla’s FSD does too for fusing vision, inertial sensors, wheel speed, multiple etc.
I believe traffic lights currently use three bulbs, red, yellow and green. Even without color a computer system can easily determine when each light is lit.
If there are single bulbs displaying red, green and yellow please give clear examples.
What do you mean by proportion? They are different data sources, and their usage is determined by system design.
eg A driving decision system needs to know object distances AND traffic light colours. It doesn't particularly need to know the source of either.
You could have a camera-only system that accurately determines colour and fuzzy-determines distance. Or you could have a LIDAR-only system that accurately determines distance and fuzzy-determines colour.
Or you use both, get accurate LIDAR-distance and accurate camera-colour and skip all the fuzzy-determination steps.
Or keep the fuzzy stuff and build a layer of measurement-agreement for redundancy.
So then the question becomes, what's your proportion when deciding whether to stop at a traffic light? Is it mostly light colour or mostly distance to other objects? Or 50/50?
> At what proportion? Is it mostly lidar or mostly cameras? Or 50/50?
What proportion of your vision is rods or cones? Depends on the context. You can do without one. But it’s better with both.
> How about when you come 4 way stop. LIDAR is useless as it wouldn't recognize anyones turn signals
Bad example. 99% of a 4-way stop is remembering who moved last, who moves next by custom and who may jump the line. What someone is indicating is, depending on where you are, between mildly helpful and useless.
Something I've seen noises about is time of flight systems for traffic. I think the idea is you can put those systems on traffic lights, cars, bicycles, and pedestrians and then cars can know where those things are.