Travel time is probably the most important indicator of the level of service of a highway, and it is also the most appreciated information for its users. Administrations and private companies make increasing efforts to improve its real time estimation. The appearance of new technologies makes the precise measurement of travel times easier than never before. However, direct measurements of travel time are, by nature, outdated in real time, and lack of the desired forecasting capabilities. This paper introduces a new methodology to improve the real time estimation of travel times by using the equipment usually present in most highways, i.e., loop detectors, in combination with Automatic Vehicle Identification or Tracking Technologies. One of the most important features of the method is the usage of cumulative counts at detectors as an input, avoiding the drawbacks of common spot-speed methodologies. Cumulative count curves have great potential for freeway travel time information systems, as they provide spatial measurements and thus allow the calculation of instantaneous travel times. In addition, they exhibit predictive capabilities. Nevertheless, they have not been used extensively mainly because of the error introduced by the accumulation of the detector drift. The proposed methodology solves this problem by correcting the deviations using direct travel time measurements. The method results highly beneficial for its accuracy as well as for its low implementation cost.