Deep learning for vehicle safety

Talkhani, Raiyan, Huang, Tao, Gu, Shushi, Guo, Zhaoxia, Zhang, Guanglin, and Xiang, Wei (2023) Deep learning for vehicle safety. In: Hu, Fei, and Rasheed, Iftikhar, (eds.) Deep Learning and Its Applications for Vehicle Networks. CRC Press, Boca Raton, FL, USA, pp. 3-16.

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[Extract] Over the last 30 years, technology in cars has evolved drastically with the introduction of software components to improve the driving experience. By adding traction controls, navigation systems, security systems, airbag deployment systems, and engine management systems, to name just a few, cars have become more reliable to operate, fuel-efficient, and safer for the passengers and drivers. Continuous investment is being made to further develop the technology present in the vehicle to improve the driving experience and safety. This has led to further advancements, such as infotainment systems, automatic climate controls, navigation systems, lane change monitoring, cruise control and lane detection.

Item ID: 77878
Item Type: Book Chapter (Research - B1)
ISSN: 9781003190691
Keywords: Deep Learning; vehicle safety; driver monitoring; perception; traffic monitoring; route planning; communications;
Copyright Information: © 2023 selection and editorial matter, Fei Hu and Iftikhar Rasheed; individual chapters, the contributors.
Date Deposited: 14 Mar 2023 23:38
FoR Codes: 46 INFORMATION AND COMPUTING SCIENCES > 4602 Artificial intelligence > 460299 Artificial intelligence not elsewhere classified @ 60%
40 ENGINEERING > 4006 Communications engineering > 400608 Wireless communication systems and technologies (incl. microwave and millimetrewave) @ 20%
46 INFORMATION AND COMPUTING SCIENCES > 4603 Computer vision and multimedia computation > 460301 Active sensing @ 20%
SEO Codes: 27 TRANSPORT > 2703 Ground transport > 270311 Road safety @ 50%
27 TRANSPORT > 2703 Ground transport > 270302 Autonomous road vehicles @ 50%
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