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Published on 27 September 2024
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Li,Y. (2024).Review on Intelligent Driving Schemes Based on Different Sensors.Applied and Computational Engineering,93,29-34.
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Review on Intelligent Driving Schemes Based on Different Sensors

Yihui Li *,1,
  • 1 The Affiliated International School of Shenzhen University, Shenzhen, China

* Author to whom correspondence should be addressed.

https://doi.org/10.54254/2755-2721/93/2024BJ0057

Abstract

With the progress of science and technology, more and more cars have the function of automatic driving. After reviewing a series of articles, it is found that there are still many problems in the research on automatic driving. These include problems with sensors, cameras, navigation systems, signals and so on. The primary focus of this article is the automobile's sensor system, which includes body-sensing sensors, radar sensors, vision sensors, and GPS systems. However, there will be numerous issues if these sensors are used alone. It can be seen that many researchers have done the application of multiple sensors and achieved good results. Thus, in order to enable the widespread adoption of automated driving in the future, it is advised to integrate two or three sensors and conduct testing through real-world applications. This can not only reduce the occurrence of accidents but also promote the broader development of autonomous driving.

Keywords

Intelligent driving, sensor, multi-sensor

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Cite this article

Li,Y. (2024).Review on Intelligent Driving Schemes Based on Different Sensors.Applied and Computational Engineering,93,29-34.

Data availability

The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.

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About volume

Volume title: Proceedings of Machine Learning assisted Automation Sensing System - CONFMLA 2024

Conference website: https://2024.confmla.org/
ISBN:978-1-83558-627-3(Print) / 978-1-83558-628-0(Online)
Conference date: 21 November 2024
Editor:Mustafa ISTANBULLU
Series: Applied and Computational Engineering
Volume number: Vol.93
ISSN:2755-2721(Print) / 2755-273X(Online)

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