Abstract
Science and technology researchers are currently focused on the creationof self-driving cars. This can havea profound effect on social and economic progress;self-driving vehicles can help reduce auto accidents dramatically and enhance the quality of life of people the world over. Self-driving cars have had a tremendous increase in popularity in the recent past because of artificial intelligence development. However, there is a lot of research work to be done to manufacture fully-automated cars becausea self-driving carshas tto be able to sense its environment and operate without human involvement. A human passenger is not required to take control of the vehicle at any time, nor are they required to be present in the vehicle at all. Currently, self-driving cars are still at level 3 and are not allowed ply the roads due to many challenges which usually cause blurred images, including irregular roads, weather factors (rain and fog).This paper is a review study on self-driving cars, and will be examining the obstacles that self-driving cars face, as well as how they might overcome them. The paperwill provide the researchers with pieces of informationabout self-driving cars, the challenges they face, the recent methods usedto overcome these challenges,and theadvantage, disadvantage, and accuracyof these methods. The paper aims to encourage researchers to work on solving the problems that inhibitthe evolution of self-driving vehicles
Recommended Citation
Dhaif, Zahraa Salah and El Abbadi, Nidhal K.
(2024)
"A Review of Machine Learning Techniques Utilised in Self-Driving Cars,"
Iraqi Journal for Computer Science and Mathematics: Vol. 5:
Iss.
1, Article 1.
DOI: https://doi.org/10.52866/ijcsm.2024.05.01.015
Available at:
https://ijcsm.researchcommons.org/ijcsm/vol5/iss1/1
