Open Access

ARTICLE

A New System for Road Traffic Optimisation Using the Virtual Traffic Light Technology

by Ahmad A. A. Alkhatib^*, Adnan A. Hnaif, Thaer Sawalha

Faculty of Science and Information Technology, Al-Zaytoonah University of Jordan, Amman, 11733, Jordan

* Corresponding Author: Ahmad A. A. Alkhatib. Email:

(This article belongs to the Special Issue: Intelligent Devices and Computing Applications)

Computer Systems Science and Engineering 2023, 47(1), 637-656. https://doi.org/10.32604/csse.2023.037345

Received 31 October 2022; Accepted 09 February 2023; Issue published 26 May 2023

Abstract

Large cities suffer from traffic congestion, particularly at intersections, due to a large number of vehicles, which leads to the loss of time by increasing carbon emissions, including fuel consumption. Therefore, the need for optimising the flow of vehicles at different intersections and reducing the waiting time is a critical challenge. Conventional traffic lights have been used to control traffic flow at different intersections and have been improved to become more efficient by using different algorithms, sensors and cameras. However, they also face some challenges, such as high-cost installation, operation, and maintenance issues. This paper develops a new system based on the Virtual Traffic Light (VTL) technology to improve traffic flow at different intersections and reduce the encountered loss of time and vehicles’ travel time. Additionally, it reduces the costs of installation, maintenance and operation over various conventional traffic light systems. Consequently, the system proposes algorithms for traffic scheduling and lane identification by using vehicle ID, priority and time of arrival. To evaluate the system, four scenarios were presented where each scenario uses a different number of vehicles consisting of three types (emergency vehicles, public buses and private vehicles), each given a different priority. The proposed system is evaluated by integrating two simulators, namely, (OMNeT++) and (SUMO), and two frameworks, namely, (VEINS) and (INET) to prepare an appropriate working environment. the results prove that an improvement in the average travel time for several vehicles reaches 44.43%–49.76% compared with conventional traffic lights. Further, it is proven from the obtained results that the average waiting time for emergency vehicles is enhanced by 96.63%–97.63%, while the average waiting time for public buses is improved by 94.81%–97.23%. On the other hand, the waiting time for private vehicles ‘improved by 87.14% to 89.71%’.

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Keywords

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