You're taking an example of a sub-optimal local solution and claiming that is proof that the global solution is sub-optimal. That does not follow.
It could easily be, taking your example, that the platoon of 5 cars must stop at some future light, and the delay for 1 car is the smallest delay available for those cars. Therefore, stopping for the 1 car reduces the platoon's total travel time. As the driver, it's easy to think that was dumb because you'll never see the 15-car wait that was avoided by stopping early for 1 car.
Essentially, you are claiming that a greedy algorithm for traffic would always find the globally optimal solution (which we know is not true).
Me, I've been stuck at traffic lights for 5 minutes at 2 in the morning, with no traffic whatsoever around. A very local algorithm would be highly preferable at that time of night, assuming usual (i.e. very little) traffic at that hour. It's an extreme example, yes: but there does exist a range of traffic patterns between the small hours of the morning and rush hour, and the same amount of global optimization effort is not applied to all hours, for obvious reasons. Something that could analyse the traffic using cameras and sensors and optimize wouldn't have to be paid extra to work late at night.
The system is called SCOOT if you are interested.
I've seen a lot of these claims, and they're easily debunked by driving through a city. The usual case is a platoon of 5 cars cruising down an arterial. A solitary car pulls up on a side street, and the light turns read for the arterial just in time to stop the platoon for the solitary car. A sensible algorithm would let the platoon pass first.
There are endless scenarios of these, to the point where the light algorithm finds a local optima where it is completely out of phase with the traffic and causes maximum delay and minimum throughput.
A relatively small amount of effort going into cameras and an adaptive system that minimizes a cost function would save billions of dollars in gas, time, and unneeded road widening.