A Review: An Evaluation of Current Artificial Intelligent Methods in Traffic Flow Prediction. Issue 1 (September 2020)

• Record Type: Journal Article
• Authors: Rusyaidi, Muhammad; Ibrahim, Zunaidi
• Is Part Of: IOP conference series. Volume 917:Issue 1(2020)
• Publication Date: 2020-09
• Subjects: machine learning -- artificial intelligence -- traffic control; Materials science -- Periodicals; 620.1105
• DOI: 10.1088/1757-899X/917/1/012063
• Languages: English
• ISSNs: 1757-8981

Abstract

Abstract: Modelling the flow of traffic is a growing issue for several city and traffic issues, using artificial intelligence to engineer as a better traffic system is the focus of artificial intelligence research. This paper, therefore, compares, analyzes and evaluates machine learning and deep learning in autonomous vehicle traffic flow prediction. Methods of machine learning and deep learning used by other researchers will be compared to each other to give results and suggestions based on their methods evaluation. The paper concludes with suggestions as to where the method would provide the most appropriate and effective technique for modern smart transport systems.