  We present an automated methodology for using Automatic Vehicle Location
measurements of public transportation vehicles to construct a probabilistic
model. The model not only allows for accurate evaluation of service
performance, but also makes it possible to study the effects of system
modifications a priori. The methodology is almost entirely agnostic to
otherwise important details of the service -- in particular its route and the
location of stops. Instead, it infers this from the data using automated map
generation techniques. The behaviour of vehicles in the model is analysed using
computer simulation combined with statistical model checking. We present two
case studies involving the Airlink service in Edinburgh and the Bellevue
Express in Seattle. To demonstrate the usefulness of the approach, we analyse
the impact of the scheduling strategies of bus holding and speed modification
on the Airlink's performance. The data and code used to create the figures are
publicly available online.
