When planning a route for a bus it is necessary to estimate people's demand for
this service as well as the time the bus will take from one stop to the next
one. This may require considerable amount of time and resources. Nevertheless,
the results might not be accurate enough since conditions change day by day. In
this paper we explore the use of existing crowdsourcing data (like Waze and
OpenStreetMap) and cloud services (like Google Maps) to support a
transportation network decision making process. The goal is to test the
hypothesis whether it is possible to make a forecasting which provides useful
information using data which can be obtained from freely available public
sources. This would serve to make a preliminary study for decision makers for
example, when evaluating the implementation of a new bus line, more
specifically, the Origin-Destination (OD) evaluation, based on the
Dempster-Shafer theory on plausibility.