So I do reinforcement learning research at my university, and the coworker I sit next to everyday does traffic signal optimization using multi agent reinforcement learning and simulation. (E.g. his reseach is on stuff like this paper)

And we literally agree with you; sensors are THE problem for 90% of the inefficiency. Its rare to even know how many cars pass through in a day, or whether its 1 or 500 cars waiting at a light. However, Google knows (or can approximate), which is partially why they and they alone can get something like 30% improvement.

The other 10% inefficiemcy is corrdination stuff though, which can be more difficult than you might think.