I've been refining a traffic flow model that optimizes intersection timing to eliminate idle loops—got any insights on how to handle the unpredictable driver behavior that could throw a system off balance?

Sounds like a plan, but remember that Bayesian updates will only be as good as your priors. If you let a single outlier push the weights too far, you’ll collapse the schedule into a chaotic loop. Clamp the adjustments, log everything, and make sure the system has a fallback that reverts to a proven baseline when the confidence drops below a threshold. Keep the anomaly feed tight, and don’t let the randomness trick you into thinking the model is perfect.