A more valid design would be randomly assigning some cities to institute congestion pricing, and other cities to not have it. Obviously not feasible in practice, but that's at least the kind of thing to strive toward when designing these kinds of studies.
In any case, not every policy change needs to be an academic exercise.
I've got a textbook on field experiments that refers to these kinds of questions as FUQ - acronym for "Fundamentally Unanswerable Questions". You can collect suggestive evidence, but firmly establishing cause and effect is something you've just got to let go of.
Cities are stupidly heterogenous. These data wouldn't be more meaningful than comparing cities with congestion pricing to those without. (And comparing them from their congestion eras.)
"Our treatment units are stupidly heterogeneous" is exactly the problem it solves. A century's worth of developing increasingly sophisticated statistical techniques for making do without random assignment has thus far failed to accomplish anything than provisional mitigations that are notoriously easy to use incorrectly in practice.