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Integration of Advanced Driver Assistance Systems on Full-Vehicle Level - Parametrization of an Adaptive Cruise Control System Based on Test Drives
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5. Selection of the Object to Follow CG xβyβ parabola circle d x0 y0 measured STM xvk yvk kβ kv kt xv yv kψ0 )i|ky,i|kx( )i|ky,ˆi|kx(ˆ i|kψˆvk t∆i+kt i|ke Figure 5.2.: Estimated trajectories using a parabola, a circle, a linear STM and the measured path at the initial time tk and at time tk+ i∆t For the predicted trajectory in the vehicle coordinate system at time stepk, the integra- tion [ vkxˆi|k vkyˆi|k ] = tk+i∆t∫ tk [ vk ˙ˆxi|k vk ˙ˆyi|k ] dt (5.17) has to be solved. 5.1.3. Path Prediction the Using Non-Constant Steering Angle Hypothesis The Non-Constant Steering Angle Hypothesis uses the vehicle model described in chap- ter 5.1.2. The only difference from the prediction algorithm of chapter 5.1.2 is that the steering angle δ, which is the input for the linear STM, is not constant. It is predicted 60
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Integration of Advanced Driver Assistance Systems on Full-Vehicle Level Parametrization of an Adaptive Cruise Control System Based on Test Drives
Title
Integration of Advanced Driver Assistance Systems on Full-Vehicle Level
Subtitle
Parametrization of an Adaptive Cruise Control System Based on Test Drives
Author
Stefan Bernsteiner
Publisher
Verlag der Technischen Universität Graz
Location
Graz
Date
2016
Language
English
License
CC BY 4.0
ISBN
978-3-85125-469-3
Size
21.0 x 29.7 cm
Pages
148
Category
Technik
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Integration of Advanced Driver Assistance Systems on Full-Vehicle Level