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The ongoing development of new traffic monitoring technologies gives rise to a situation with multiple sources of data and multiple algorithms for the estimation of variables that may be of interest, among them information on travel time. This context with data from different sources, all of them imprecise to varying degrees, is the right one for applying data merging techniques. Their objective is to obtain a more reliable and precise merged value than that obtained from any individual estimations by themselves. This article presents a simple data merging methodology for the estimation of travel time on the highway. The proposed method uses data from loop detectors and toll tickets and would be easy to extend to other data sources. Its pilot application on the AP-7 highway has produced promising results. [ABSTRACT FROM AUTHOR]

The application of new technologies to traffic engineering has allowed the development of Intelligent Transport Systems. ITS improve traffic management and increase road safety optimizing the use of the existing road infrastructure. ITS systems make easy traffic dynamic management. One of most used parameters in traffic management is the Level of Service. Currently, Level of Service are based on the Highways Capacity Manual from Transportation Research Board. However, the proposed model is completely static. Thus, this model is considered suitable for the dimensioning of future road network, but not for dynamic traffic management. This paper presents a new model for the identification of level of service in highways that allows a dynamic traffic management in real time. This model is based on the fundamental relation between speed and occupancy. [ABSTRACT FROM AUTHOR]