International Journal of Transportation Engineering and Traffic System
Civil Engineering ISSN 2456-2343 2 issues a year Hybrid open accessWhat does hybrid open access mean? This journal has two kinds of articles. Open access articles are free for anyone to read; the author pays an article processing charge for that. All other articles are for subscribers. Authors can also publish at no cost under the subscription-based option.
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About the journal
Journal metrics
Counted from this archive, not supplied by anyone.
- 30Articles published
- 10Published in 2026
- 60Authors
- 0Open access
Journal information
- Title
- International Journal of Transportation Engineering and Traffic System
- Issues per year
- 2 issues
- E-ISSN
- 2456-2343
- Publisher
- JournalsPub
- DOI
- 10.37628/IJTETS
- Starting year
- 2024
- Subject
- Civil Engineering
- Publication format
- Hybrid open access
- Language
- English
- Copyright policy
- Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
- Type
- Peer-reviewed journal (refereed)
- Subscription-based publication
- No cost. Author copy, DOI and certificate are chargeable.
Editorial board
-
Associate Editor-in-Chief
Dr. Saad Issa Sarsam
Civil Engineering, University of Baghdad
Latest articles
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Modelling and Simulation of Adaptive Traffic Control Systems: Electrical Engineering Techniques for Urban Applications
Abstract: Traffic congestion is a ubiquitous challenge in urban areas, necessitating innovative solutions to improve transportation efficiency and alleviate gridlock. Traditional traffic signal control methods often prove inadequate in dynamically adapting to fluctuating traffic conditions, leading to increased travel times, fuel consumption, and emissions. In response, adaptive traffic control systems have emerged as a promising approach to mitigate congestion and enhance traffic flow in urban environments. These systems use real-time data …
Published in International Journal of Transportation Engineering and Traffic System Read article
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Predicting Traffic Congestion in Mumbai Using Artificial Intelligence
Abstract: Abstract — Mumbai's ongoing traffic problems are brought on by the city's fast urbanization, population expansion, and growing reliance on private automobiles. The majority of traffic management technologies in use today are reactive, frequently reacting only after congestion has already arisen. Using information from a variety of sources, such as commuter surveys, weather reports, and traffic incident logs, this study explores the application of artificial intelligence (AI) and machine learning …
Published in International Journal of Transportation Engineering and Traffic System · Vol. 12, Issue 2, 2026 Read article
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A Machine Learning-Based Framework for Urban Traffic Congestion Prediction and Control Using Intelligent Transportation Systems
Abstract: Abstract Traffic congestion remains a critical challenge in rapidly expanding urban areas, causing increased travel delays, excessive fuel consumption, environmental degradation, and economic inefficiencies. Traditional traffic management approaches are often insufficient, as they lack the ability to respond dynamically to continuously changing traffic conditions. This study proposes a novel data-driven framework for the prediction and management of traffic congestion using Intelligent Transportation Systems (ITS). The methodology integrates real-time and historical …
Published in International Journal of Transportation Engineering and Traffic System · Vol. 12, Issue 1, 2026 Read article
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A Machine Learning-Based Framework for Urban Traffic Congestion Prediction and Control Using Intelligent Transportation Systems
Abstract: Abstract Traffic congestion remains a critical challenge in rapidly expanding urban areas, causing increased travel delays, excessive fuel consumption, environmental degradation, and economic inefficiencies. Traditional traffic management approaches are often insufficient, as they lack the ability to respond dynamically to continuously changing traffic conditions. This study proposes a novel data-driven framework for the prediction and management of traffic congestion using Intelligent Transportation Systems (ITS). The methodology integrates real-time and historical …
Published in International Journal of Transportation Engineering and Traffic System · Vol. 12, Issue 1, 2026 · pp. 12–17 Read article
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Traffic Safety in Indore: Analysis of Accident Trends, Causes, and Preventive Measures
Abstract: Abstract Traffic safety has emerged as a significant concern in rapidly growing urban cities like Indore due to increasing population, rising vehicle ownership, and expanding infrastructure. This study focuses on analyzing traffic safety conditions in Indore by examining accident trends, major causes, high-risk zones, and existing safety measures over the period from 2020 to 2026. The analysis reveals a continuous increase in road accidents and fatalities, indicating a growing risk …
Published in International Journal of Transportation Engineering and Traffic System · Vol. 12, Issue 1, 2026 · pp. 18–25 Read article
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A Comprehensive Review of Transportation Network Design and Congestion Modeling: Methods, Challenges, and Emerging Trends
Abstract: Abstract As urbanization and travel demand continue to grow rapidly, traffic congestion has emerged as a widespread issue worldwide. The design of transportation networks and the modeling of congestion are essential disciplines that provide foundational tools for analyzing, predicting, and mitigating congestion impacts. This review complies key theories, modeling frameworks, optimization techniques, and algorithms used in network design and congestion modeling. We discuss static and dynamic models, equilibrium concepts, congestion …
Published in International Journal of Transportation Engineering and Traffic System · Vol. 12, Issue 1, 2026 Read article
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Automated Vehicle classification and counting for Smart City Traffic management using AI/ML and DL
Abstract: Abstract: Traffic jam and safety at the road have become a serious problem in modern cities. They need smart and versatile solutions. This project is a proposal to use automated vehicles to count and classify real- time vehicles. The system will enhance the traffic monitoring and management in smart cities. It is capable of identifying and differentiating the various kinds of vehicles: cars, trucks, buses, and motorcycles by utilizing machine …
Published in International Journal of Transportation Engineering and Traffic System · Vol. 12, Issue 1, 2026 Read article
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Automated Vehicle classification and counting for Smart City Traffic management using AI/ML and DL
Abstract: Traffic jams and safety on the road have become a serious problem in modern cities. They need smart and versatile solutions. This project is a proposal to use automated vehicles to count and classify real- time vehicles. The system will enhance the traffic monitoring and management in smart cities. It can identify and differentiate the various kinds of vehicles: cars, trucks, buses, and motorcycles by utilizing machine learning on real-time …
Published in International Journal of Transportation Engineering and Traffic System · Vol. 12, Issue 1, 2026 Read article
Ahead of print
Accepted and online before they are assigned to an issue.
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Modelling and Simulation of Adaptive Traffic Control Systems: Electrical Engineering Techniques for Urban Applications
Abstract: Traffic congestion is a ubiquitous challenge in urban areas, necessitating innovative solutions to improve transportation efficiency and alleviate gridlock. Traditional traffic signal control methods often prove inadequate in dynamically adapting to fluctuating traffic conditions, leading to increased travel times, fuel consumption, and emissions. In response, adaptive traffic control systems have emerged as a promising approach to mitigate congestion and enhance traffic flow in urban environments. These systems use real-time data …
Published in International Journal of Transportation Engineering and Traffic System Read article