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.
Original language | English |
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Title of host publication | Artificial Neural Networks and Machine Learning - 25th International Conference on Artificial Neural Networks, ICANN 2016, Proceedings |
Editors | Alessandro E.P. Villa, Paolo Masulli, Antonio Javier Pons Rivero |
Publisher | Springer Verlag |
Pages | 515-522 |
Number of pages | 8 |
ISBN (Print) | 9783319447803 |
DOIs | |
Publication status | Published - 2016 |
Event | 25th International Conference on Artificial Neural Networks and Machine Learning, ICANN 2016 - Barcelona, Spain Duration: 6 Sept 2016 → 9 Sept 2016 |
Publication series
Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
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Volume | 9887 LNCS |
ISSN (Print) | 0302-9743 |
ISSN (Electronic) | 1611-3349 |
Conference
Conference | 25th International Conference on Artificial Neural Networks and Machine Learning, ICANN 2016 |
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Country/Territory | Spain |
City | Barcelona |
Period | 6/09/16 → 9/09/16 |
Bibliographical note
Publisher Copyright:© Springer International Publishing Switzerland 2016.
Keywords
- Adaptive cruise control
- Artificial neural network
- Controller
- MATLAB
- Vehicle