[methodin]

I thought the whole point of these "fixed traffic jam" articles was to make your undoubtedly terrible commute go faster by giving you something to do, or at the very least providing a false sense of control over a situation (like a superstition). The science behind traffic is completely arbitrary and nonsensical no matter how many graphs or numbers you put behind it. There are simply too many different drivers out there to make any empirical evidence useful.

[privong]

I think the idea is to give it a treatment analgous to how statistical mechanics works for properties of gas, for example. True, we can't easily say what individual atoms/molecules might do, but we can say something about the gas as an ensemble.

It's true that free will may make drivers tougher to predict than individual molecules. But molecules obey quantum mechanics and one could conceivibly construct probability distributions for how that particle might behave. In principle, probability distributions could also be constructed for the behavior of individual cars/drivers, so a statistical approximation for the behavior of the ensemble of drivers in a system is probably a reasonable aim.

[methodin]

I get that we want it to be consistent but having driven the same roads for years, in the same times of day, in varying but similar weather patterns the driving is completely sporadic so no amount of normalization well give you anything more than a crapshoot on any given day other than "it will probably take me anywhere from 20 to 50 minutes." Statistical analysis is great for many things but understanding the "now" of a traffic pattern is not one of them.

[privong]

I think it depends on what one wants to model. For a general understanding of how traffic flows, a statistical model is okay. On the other hand, if you want to know why a specific traffic jam is happening and how it's affecting the flow, a statistical model won't be sufficient.