Seite - 66 - 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 )i|ky,ˆi|kx(ˆ )|k+2iy,ˆ|k+2ix(ˆ )|k1−iy,ˆ|k1−ix(ˆ in ip iσ )jy,jx( )j,qy,j,qx( ju iη )|k+1iy,ˆ|k+1ix(ˆ )ry,rx( +1iσ ru iα 2 iα 2 iα )ty,tx( tu ‖+1ip‖t+1,ik−‖ip‖1)−r,ik( Figure 5.5.: Calculation of natural coordinates leads to the right part. Figure 5.4 shows that the RADAR sensor estimates the widthwj and length lj of all the measured objects. For further investigations, each object is represented as a list of four points that read ssj,fl= [ sxj+ lj syj+ wj 2 ] , ssj,fr= [ sxj+ lj syj−wj2 ] , ssj,rl= [ sxj syj+ wj 2 ] and ssj,rr= [ sxj syj−wj2 ] , (5.37) as illustrated in fig. 5.4. 5.3. Object Selection The selection of the right OTF strongly depends on the accuracy of the predicted path, the accuracy of the position of the detected objects and their predicted paths. Chap- ters 5.3.1 and 5.3.2 give examples for two different object selection algorithms. 5.3.1. In-Path Algorithm With the In-Path Algorithm, the nearest object in the predicted path is selected as the OTF.Therefore, thepredictedtrajectory is superimposedbyapathwithacertainwidth. Chapters 5.3.1.1 and 5.3.1.2 describe two different path width algorithms in detail. 66