Meshari D. Alanazi¹, Gehan Elsayed^2,*, Turki M. Alanazi³, Anis Sahbani⁴, Amr Yousef^5,6

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.2, pp. 2277-2309, 2025, DOI:10.32604/cmes.2025.070726 - 26 November 2025

Abstract Traffic congestion plays a significant role in intelligent transportation systems (ITS) due to rapid urbanization and increased vehicle concentration. The congestion is dependent on multiple factors, such as limited road occupancy and vehicle density. Therefore, the transportation system requires an effective prediction model to reduce congestion issues in a dynamic environment. Conventional prediction systems face difficulties in identifying highly congested areas, which leads to reduced prediction accuracy. The problem is addressed by integrating Graph Neural Networks (GNN) with the Lion Swarm Optimization (LSO) framework to tackle the congestion prediction problem. Initially, the traffic information is… More >

Seongsoo Cho¹, Yeonwoo Lee^2,*, Cheolhee Yoon^3,*

CMES-Computer Modeling in Engineering & Sciences, Vol.143, No.3, pp. 3769-3793, 2025, DOI:10.32604/cmes.2025.066298 - 30 June 2025

Abstract As vehicular networks grow increasingly complex due to high node mobility and dynamic traffic conditions, efficient clustering mechanisms are vital to ensure stable and scalable communication. Recent studies have emphasized the need for adaptive clustering strategies to improve performance in Intelligent Transportation Systems (ITS). This paper presents the Grasshopper Optimization Algorithm for Vehicular Network Clustering (GOA-VNET) algorithm, an innovative approach to optimal vehicular clustering in Vehicular Ad-Hoc Networks (VANETs), leveraging the Grasshopper Optimization Algorithm (GOA) to address the critical challenges of traffic congestion and communication inefficiencies in Intelligent Transportation Systems (ITS). The proposed GOA-VNET employs an… More >

Idongesit Sunday Ambrose¹, Sunday Edet Etuk², Okechukwu Ebuka Agbasi^3,*, Ijah Ioryue Silas⁴, Unyime Udoette Saturday⁵, Eyo Edet Orok⁶

Revue Internationale de Géomatique, Vol.34, pp. 335-350, 2025, DOI:10.32604/rig.2025.064552 - 13 June 2025

Abstract Road construction and traffic congestion are increasingly recognized as major contributors to environmental and public health challenges in urban Nigeria, particularly in Rivers State. Despite growing urbanization, a gap remains in localized data on the combined effects of air and noise pollution in hydrocarbon-polluted environments. This study addresses that gap by conducting a preliminary environmental health assessment focused on the Port Harcourt Ring Road project. Air quality and noise levels were monitored in situ at 20 strategically selected locations, with five control points included for baseline comparison. Digital portable meters were used to measure concentrations of… More >

Ahmed Alhussen¹, Arshiya S. Ansari^2,*

CMC-Computers, Materials & Continua, Vol.79, No.2, pp. 1903-1923, 2024, DOI:10.32604/cmc.2024.049260 - 15 May 2024

Abstract Traffic in today’s cities is a serious problem that increases travel times, negatively affects the environment, and drains financial resources. This study presents an Artificial Intelligence (AI) augmented Mobile Ad Hoc Networks (MANETs) based real-time prediction paradigm for urban traffic challenges. MANETs are wireless networks that are based on mobile devices and may self-organize. The distributed nature of MANETs and the power of AI approaches are leveraged in this framework to provide reliable and timely traffic congestion forecasts. This study suggests a unique Chaotic Spatial Fuzzy Polynomial Neural Network (CSFPNN) technique to assess real-time data… More >

Abdulwahab Ali Almazroi^1,*, Nasir Ayub²

CMC-Computers, Materials & Continua, Vol.77, No.3, pp. 3921-3942, 2023, DOI:10.32604/cmc.2023.046602 - 26 December 2023

Abstract Effectively managing complex logistics data is essential for development sustainability and growth, especially in optimizing distribution routes. This article addresses the limitations of current logistics path optimization methods, such as inefficiencies and high operational costs. To overcome these drawbacks, we introduce the Hybrid Firefly-Spotted Hyena Optimization (HFSHO) algorithm, a novel approach that combines the rapid exploration and global search abilities of the Firefly Algorithm (FO) with the localized search and region-exploitation skills of the Spotted Hyena Optimization Algorithm (SHO). HFSHO aims to improve logistics path optimization and reduce operational costs. The algorithm’s effectiveness is systematically… More >

Ahmed Alsheikhy^1,*, Yahia Said¹, Tawfeeq Shawly²

Computer Systems Science and Engineering, Vol.46, No.1, pp. 1109-1126, 2023, DOI:10.32604/csse.2023.035135 - 20 January 2023

Abstract Due to excessive car usage, pollution and traffic have increased. In urban cities in Saudi Arabia, such as Riyadh and Jeddah, drivers and air quality suffer from traffic congestion. Although the government has implemented numerous solutions to resolve this issue or reduce its effect on the environment and residents, it still exists and is getting worse. This paper proposes an intelligent, adaptive, practical, and feasible deep learning method for intelligent traffic control. It uses an Internet of Things (IoT) sensor, a camera, and a Convolutional Neural Network (CNN) tool to control traffic in real time.… More >

Mohammed Gollapalli¹, Atta-ur-Rahman^2,*, Dhiaa Musleh², Nehad Ibrahim², Muhammad Adnan Khan³, Sagheer Abbas⁴, Ayesha Atta⁵, Muhammad Aftab Khan⁶, Mehwash Farooqui⁶, Tahir Iqbal⁷, Mohammed Salih Ahmed⁶, Mohammed Imran B. Ahmed⁶, Dakheel Almoqbil⁸, Majd Nabeel², Abdullah Omer²

CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 295-310, 2022, DOI:10.32604/cmc.2022.027925 - 18 May 2022

Abstract The fast-paced growth of artificial intelligence applications provides unparalleled opportunities to improve the efficiency of various systems. Such as the transportation sector faces many obstacles following the implementation and integration of different vehicular and environmental aspects worldwide. Traffic congestion is among the major issues in this regard which demands serious attention due to the rapid growth in the number of vehicles on the road. To address this overwhelming problem, in this article, a cloud-based intelligent road traffic congestion prediction model is proposed that is empowered with a hybrid Neuro-Fuzzy approach. The aim of the study… More >

Andrea Sant¹, Lalit Garg^1,*, Peter Xuereb¹, Chinmay Chakraborty²

CMC-Computers, Materials & Continua, Vol.67, No.3, pp. 3523-3544, 2021, DOI:10.32604/cmc.2021.015265 - 01 March 2021

Abstract The better management of resources and the potential improvement in traffic congestion via reducing the orbiting time for parking spaces is crucial in a smart city, particularly those with an uneven correlation between the increase in vehicles and infrastructure. This paper proposes and analyses a novel green IoT-based Pay-As-You-Go (PAYG) smart parking system by utilizing unused garage parking spaces. The article also presents an intelligent system that offers the most favorable prices to its users by matching private garages’ pricing portfolio with a garage’s current demand. Malta, the world’s fourth-most densely populated country, is considered More >

M.J. Galán Moreno, J.J. Sánchez Medina, L. Álvarez Álvarez E. Rubio Royo¹

CMES-Computer Modeling in Engineering & Sciences, Vol.50, No.3, pp. 191-226, 2009, DOI:10.3970/cmes.2009.050.191

Abstract Urban traffic is a key factor for the development of a city. There exist many different approaches facing traffic optimization. In our case we have focused on traffic lights optimization. We have designed and tested a new architecture to optimize traffic light cycle times. The purpose of this research is to demonstrate the good performance of our architecture in a congested scenario. We have simulated several congestion situations for a very large real world traffic network - "La Almozara" in Zaragoza, Spain. Our results seem encouraging in this extreme situation. As we increase the load More >