Machine learning approach in identifying speed breakers for autonomous driving: an overview
Advanced control systems for autonomous driving is capable of nav-igating vehicles without human interaction with appropriate devices by sensing the environment nearby the vehicle. Majority of such systems, autonomous ve-hicles implement a deliberative architecture that will pave the way for vehicle...
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ump-24517 |
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eprints |
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ump-245172020-02-11T07:34:46Z http://umpir.ump.edu.my/id/eprint/24517/ Machine learning approach in identifying speed breakers for autonomous driving: an overview Choong, Chun Sern Ahmad Fakhri, Ab. Nasir Anwar, P. P. Abdul Majeed Muhammad Aizzat, Zakaria Mohd Azraai, M. Razman TS Manufactures Advanced control systems for autonomous driving is capable of nav-igating vehicles without human interaction with appropriate devices by sensing the environment nearby the vehicle. Majority of such systems, autonomous ve-hicles implement a deliberative architecture that will pave the way for vehicle tracking, vehicle recognition, and collision avoidance. This paper provides a brief overview of the most advanced and recent approaches taken to detect and track speed breakers that employ various devices that allows pattern recognition. The discussion of various speed breaker detection will be limited to 3D recon-struction-based, vibration-based and vision-based. Moreover, the common ma-chine learning models that have been used to investigate speed breakers are also discussed. Springer, Singapore 2018-06 Book Section PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/24517/1/57.%20Machine%20learning%20approach%20in%20identifying%20speed%20breakers.pdf pdf en http://umpir.ump.edu.my/id/eprint/24517/2/57.1%20Machine%20learning%20approach%20in%20identifying%20speed%20breakers.pdf pdf en http://umpir.ump.edu.my/id/eprint/24517/13/9.%20Machine%20learning%20approach%20in%20identifying%20speed%20breakers%20for%20autonomous%20driving%20an%20overview.pdf pdf en http://umpir.ump.edu.my/id/eprint/24517/14/9.1%20Machine%20learning%20approach%20in%20identifying%20speed%20breakers%20for%20autonomous%20driving%20an%20overview.pdf Choong, Chun Sern and Ahmad Fakhri, Ab. Nasir and Anwar, P. P. Abdul Majeed and Muhammad Aizzat, Zakaria and Mohd Azraai, M. Razman (2018) Machine learning approach in identifying speed breakers for autonomous driving: an overview. In: Lecture Notes in Mechanical Engineering. Springer, Singapore, pp. 409-424. ISBN 978-981-13-8323-6 https://doi.org/10.1007/978-981-13-8323-6_35 https://link.springer.com/chapter/10.1007/978-981-13-8323-6_35 |
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Digital Repository |
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Local University |
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Universiti Malaysia Pahang |
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UMP Institutional Repository |
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Online Access |
| language |
English English English English |
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TS Manufactures |
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TS Manufactures Choong, Chun Sern Ahmad Fakhri, Ab. Nasir Anwar, P. P. Abdul Majeed Muhammad Aizzat, Zakaria Mohd Azraai, M. Razman Machine learning approach in identifying speed breakers for autonomous driving: an overview |
| description |
Advanced control systems for autonomous driving is capable of nav-igating vehicles without human interaction with appropriate devices by sensing the environment nearby the vehicle. Majority of such systems, autonomous ve-hicles implement a deliberative architecture that will pave the way for vehicle tracking, vehicle recognition, and collision avoidance. This paper provides a brief overview of the most advanced and recent approaches taken to detect and track speed breakers that employ various devices that allows pattern recognition. The discussion of various speed breaker detection will be limited to 3D recon-struction-based, vibration-based and vision-based. Moreover, the common ma-chine learning models that have been used to investigate speed breakers are also discussed. |
| format |
Book Section |
| author |
Choong, Chun Sern Ahmad Fakhri, Ab. Nasir Anwar, P. P. Abdul Majeed Muhammad Aizzat, Zakaria Mohd Azraai, M. Razman |
| author_facet |
Choong, Chun Sern Ahmad Fakhri, Ab. Nasir Anwar, P. P. Abdul Majeed Muhammad Aizzat, Zakaria Mohd Azraai, M. Razman |
| author_sort |
Choong, Chun Sern |
| title |
Machine learning approach in identifying speed breakers for autonomous driving: an overview |
| title_short |
Machine learning approach in identifying speed breakers for autonomous driving: an overview |
| title_full |
Machine learning approach in identifying speed breakers for autonomous driving: an overview |
| title_fullStr |
Machine learning approach in identifying speed breakers for autonomous driving: an overview |
| title_full_unstemmed |
Machine learning approach in identifying speed breakers for autonomous driving: an overview |
| title_sort |
machine learning approach in identifying speed breakers for autonomous driving: an overview |
| publisher |
Springer, Singapore |
| publishDate |
2018 |
| url |
http://umpir.ump.edu.my/id/eprint/24517/ http://umpir.ump.edu.my/id/eprint/24517/ http://umpir.ump.edu.my/id/eprint/24517/ http://umpir.ump.edu.my/id/eprint/24517/1/57.%20Machine%20learning%20approach%20in%20identifying%20speed%20breakers.pdf http://umpir.ump.edu.my/id/eprint/24517/2/57.1%20Machine%20learning%20approach%20in%20identifying%20speed%20breakers.pdf http://umpir.ump.edu.my/id/eprint/24517/13/9.%20Machine%20learning%20approach%20in%20identifying%20speed%20breakers%20for%20autonomous%20driving%20an%20overview.pdf http://umpir.ump.edu.my/id/eprint/24517/14/9.1%20Machine%20learning%20approach%20in%20identifying%20speed%20breakers%20for%20autonomous%20driving%20an%20overview.pdf |
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2023-09-18T22:37:09Z |
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2023-09-18T22:37:09Z |
| _version_ |
1777416672044384256 |