Abstract
Adaptive cruise control is a system which controls a vehicle equipped with radars and a control unit to maintain either velocity of the vehicle or the distance between the preceding vehicle. The basic principle of this system is to read and interpret the radar measurement to determine the required actuating signals and apply these signals to reach the desired goal. In this work, the control is accomplished using a feed-forward artificial neural network, and its role is discussed. All the system is modelled in MATLAB/SIMULINK environment, and the main contribution of this work is to show the applicability of artificial neural network structure to an engineering problem at system level.
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Kuyumcu, A., Şengör, N.S. (2016). Effect of Neural Controller on Adaptive Cruise Control. In: Villa, A., Masulli, P., Pons Rivero, A. (eds) Artificial Neural Networks and Machine Learning – ICANN 2016. ICANN 2016. Lecture Notes in Computer Science(), vol 9887. Springer, Cham. https://doi.org/10.1007/978-3-319-44781-0_61
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DOI: https://doi.org/10.1007/978-3-319-44781-0_61
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