Nadeem, Khodabacchus Muhamad and Fowdur, Tulsi Pawan (2018) Performance Analysis of a Real-Time Adaptive Prediction Algorithm for Traffic Congestion. Journal of Information and Communication Technology, 17 (3). pp. 493-511. ISSN 2180-3862

Preview

PDF - Published Version Available under License Attribution 4.0 International (CC BY 4.0). Download (1MB) | Preview

Abstract

Traffic congestion is a major factor to consider in the development of a sustainable urban road network. In the past, several mechanisms have been developed to predict congestion, but few have considered an adaptive real-time congestion prediction. This paper proposes two congestion prediction approaches are created. The approaches choose between five different prediction algorithms using the Root Mean Square Error model selection criterion. The implementation consisted of a Global Positioning System based transmitter connected to an Arduino board with a Global System for Mobile/General Packet Radio Service shield that relays the vehicles position to a cloud server. A control station then accesses the vehicles position in real-time, computes its speed. Based on the calculated speed, it estimates the congestion level and it applies the prediction algorithms to the congestion level to predict the congestion for future time intervals. The performance of the prediction algorithms was analysed, and it was observed that the proposed schemes provide the best prediction results with a lower Mean Square Error than all other prediction algorithms when compared with the actual traffic congestion states.

Item Type:	Article
Uncontrolled Keywords:	Adaptive prediction, cloud server, Global Positioning System, real-time, traffic congestion
Subjects:	T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions:	School of Computing
Depositing User:	Mrs Nurin Jazlina Hamid
Date Deposited:	09 Feb 2023 02:37
Last Modified:	09 Feb 2023 02:37
URI:	https://repo.uum.edu.my/id/eprint/29163

Actions (login required)

View Item