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We have developed sensor units and additionally installed them on an existing measuring vehicle in order to record various road parameters. These parameters mainly include the inclination of the road both parallel and perpendicular to the travel movement, the width of the road, the detection and location of road markings and the detection of weather-related road damage. These values can be used to calculate the maximum speed, the shock absorber settings or the optimization of the driving comfort of vehicles traversing these roads. The roll-angle-module, in conjunction with the additional values given by the measuring vehicle itself, provides the transverse inclination of the road. For this purpose, the distances obtained from two infrared (IR) modules located on the outside of the vehicle are recorded in real time and the resulting angle of the vehicle with respect to the road is determined with a suitable function. This is necessary since the measured value changes of the two modules based on the rotation-related movement and the radiation characteristics of the IR modules do not have the same magnitude. Thus, without mathematical adjustment, the ascertained value of the inclination would be greater than the actual angle of vehicle to the road. This value is again calculated with the angle from the vehicle to the center of the earth, which is output directly from the vehicles accelerometers and GPS data, and the angle of the road is obtained. The angle in the direction of travel is calculated purely on the GPS data. A mesh of the road topography can be created by the superposition of the angular values at all measurement coordinates. The width module, which consists of a camera and two line lasers, provides the width of the roadway in a post-processing step. Furthermore, road markings are detected and provided with the corresponding time stamp of the video and grouped on the basis of various criteria. The lasers used here serve as a wide standard for calibration. A schematic diagram of the measuring vehicle is shown in Figure 1. The post-processing is done by means of a Python code which stores the individual frames of the recorded video one by one. By means of a routine colors are detected, a recalibration of the width over the created ”green” image is executed and then the ”white” image is examined on objects with specific parameters and divided into groups, such as ”pedestrian crossing”. The bluish-colored cameras shown in Fig. 1 are used for the stereoscopic recording of the road and the subsequent processing and recognition of road signs, traffic lights and roadside borders. The output can be saved as a text document or as a collection in the graphical user interface. Furthermore, a laser module is used to generate a structured light pattern in order to detect weather-induced influences on the road, such as potholes. For this purpose a routine was developed and adapted, which can determine the dimensions of the road defects based on the position of the imaged points and the known geometric parameters.
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