Page - 55 - in Integration of Advanced Driver Assistance Systems on Full-Vehicle Level - Parametrization of an Adaptive Cruise Control System Based on Test Drives

5 Selection of the Object to Follow One of the main challenges in designing Adaptive Cruise Control (ACC) systems is to find a reliable algorithm for the selection of the target, the Object to Follow (OTF). For this task, the ACC system has to predict the ego vehicle path with the available sensor information. Based on the predicted trajectory, the OTF is selected. For this chapter, simple algorithms were chosen intentionally. Despite their simplicity, they lead to good outputs. 5.1. Path Prediction Thischapterdescribesdifferent state-of-the-artpathpredictionalgorithmsandevaluates them based on the measurements made in chapter 4. The path prediction must be performed using the sensor data that is available in the vehicle. Caveney uses digital maps that deliver the expected road curvature, [Cav09]. This data is used in combination with the dynamic state of the vehicle to predict the vehicle path. Since these maps are not currently available for all roads, they were not used in this investigation. Additionally, the use of digital maps may pose a problem at locations where the vehicle localization does not work (e.g. in tunnels or in cities, where the high buildings obscure the Global Navigation Satellite System (GNSS) satellites). In such locations, other technologies such as Vehicle-to-Vehicle Communication (V2V) or Vehicle-to-Infrastructure Communication (V2I) may be used to obtain the necessary data. Another approach was used by Yim et al. in [YSZS10]. They described a system in which the information is stored in the lane markings as binary code and is detected