This monograph presents a simple,
innovative approach for the measurement and short-term prediction of highway
travel times based on the fusion of inductive loop detector and toll ticket
data. The methodology is generic and not technologically captive, allowing it
to be easily generalized for other equivalent types of data.  The book
shows how Bayesian analysis can be used to obtain fused estimates that are more
reliable than the original inputs, overcoming some of the drawbacks of
travel-time estimations based on unique data sources. The developed methodology
adds value and obtains the maximum (in terms of travel time estimation) from
the available data, without recurrent and costly requirements for additional
data. The application of the algorithms to empirical testing in the AP-7 toll
highway in Barcelona proves that it is possible to develop an accurate
real-time, travel-time information system on closed-toll highways with the
existing surveillance equipment, suggesting that highway operators might provide
their customers with such an added value with little additional investment in
technology.