A Study For Self-Driving Car Analysis

Computer vision has demonstrated itself to be a key component of recent technological advancements. Among computer vision applications, the self-driving automobile. The self-driving cars is one of the most significant developments in the automotive sector. Also Currently, artificial intelligence, especially neural networks, has contributed greatly to the field of automated driving. This paper presents an overview of the use of artificial neural networks for lane detection and demonstrates how this technology has become a key component of vision-controlled autonomous vehicles. Convolutional Neural Networks (CNN) are used for lane detection, which contributes to the car's autonomous operation. Also, the convolutional Neural Networks model gives the vehicle the ability to learn from various road conditions and weather conditions weather rainy, sunny, night or day, granting it the capability of direction prediction so that it can handle any scenario arise which will help the driver to make the right decision and avoid accidents. Index Terms— Self-Driving Car, Deep Learning, Deep Neural Networks, Computer Vision, Lane Detection.

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Publication Details

Journal
Iraqi Journal of Computer Communication Control and System Engineering
Published
2024-12-30
DOI
https://doi.org/10.33103/uot.ijccce.24.4.4
Primary Topic
Engineering Applied Research
Type
article
Field-Weighted Citation Impact
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article

A Study For Self-Driving Car Analysis

Iraqi Journal of Computer Communication Control and System Engineering
Engineering Applied Research
article

A Study For Self-Driving Car Analysis

article en

Abstract

Computer vision has demonstrated itself to be a key component of recent technological advancements. Among computer vision applications, the self-driving automobile. The self-driving cars is one of the most significant developments in the automotive sector. Also Currently, artificial intelligence, especially neural networks, has contributed greatly to the field of automated driving. This paper presents an overview of the use of artificial neural networks for lane detection and demonstrates how this technology has become a key component of vision-controlled autonomous vehicles. Convolutional Neural Networks (CNN) are used for lane detection, which contributes to the car's autonomous operation. Also, the convolutional Neural Networks model gives the vehicle the ability to learn from various road conditions and weather conditions weather rainy, sunny, night or day, granting it the capability of direction prediction so that it can handle any scenario arise which will help the driver to make the right decision and avoid accidents. Index Terms— Self-Driving Car, Deep Learning, Deep Neural Networks, Computer Vision, Lane Detection.

Iraqi Journal of Computer Communication Control and System Engineering
University of Technology - Iraq (IQ)
Openalex Percentile: Top 70%
Engineering Applied Research
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