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This paper presents the results of a set of extensive experiments carried out under both daytime and nighttime real traffic conditions. The data were captured using an enhanced or extended Floating Car Data system (xFCD) that includes a stereo vision sensor for detecting the local traffic ahead. The collected information is then used to propose a novel approach to the level-of-service (LOS) calculation. This calculation uses information from both the xFCD and the magnetic loops deployed in the infrastructure to construct a speed/occupancy hybrid plane that characterizes the traffic state of a continuous route. In the xFCD system, the detection component implies the use of previously developed monocular approaches in combination with new stereo vision algorithms that add robustness to the detection and increase the accuracy of the measurements corresponding to relative distance and speed. In addition to the stereo pair of cameras, the vehicle is equipped with a low-cost Global Positioning System (GPS) and an electronic device for controller-area-network bus interfacing. The xFCD system has been tested in a 198-min sequence recorded in real traffic scenarios under different weather and illumination conditions. The results are promising and demonstrate that the xFCD system is ready for being used as a source of traffic status information. As an indicative example of the developed xFCD system, we construct a novel route LOS calculation that combines hybrid information about speed and occupancy from both the xFCD system and the magnetic loops in the infrastructure.