AI transit systems are moving from limited demonstrations into operational decision support, but the strongest lessons from recent studies are less about algorithms than about implementation discipline. Transit agencies need accurate data, well-defined use cases, staff capacity, privacy controls, and evidence that a tool improves service without shifting risk onto riders or operators.
The recent evidence base is mixed but useful. Some deployments have reported measurable gains in dispatching, travel time, operating cost, or staff workflow.… Read the rest