Intelligent Transportation Systems and Traffic Management in Urban Networks

A special issue of Future Transportation (ISSN 2673-7590).

Deadline for manuscript submissions: 15 April 2027 | Viewed by 633

Special Issue Editors


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Guest Editor
Transportation Department, Faculty of Civil Engineering and Geodesy, Military University of Technology, 00-908 Warsaw, Poland
Interests: intelligent transportation systems (ITS); artificial intelligence in transportation; traffic flow modelling and prediction; graph theory applications in transport; urban mobility and safety; transport optimization algorithms; machine learning; logistics and vehicle routing

E-Mail Website
Guest Editor
Faculty of Mechanical Engineering, Institute of Mechanics and Computational Engineering, Military University of Technology, Gen. Sylwestra Kaliskiego 2, 00-908 Warsaw, Poland
Interests: intelligent transportation systems (ITS); metaheuristics algorithms; optimization; artificial neural networks; UAV path planning; urban mobility

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Guest Editor
Department of Transport Systems, Traffic Engineering and Logistics, Faculty of Transport and Aviation Engineering, Silesian University of Technology, Katowice, Poland
Interests: public transport organization, management, planning and safety; management in transport; its in public transport; forecasting and modelling of mobility; transport systems planning; traffic engineering; transport measurements

Special Issue Information

Dear Colleagues,

Rapid urbanization and the accelerating demand for seamless mobility are exerting unprecedented pressure on global urban road networks and, as the expansion of traditional infrastructure reaches its physical and economic limits, the future of mobility has come to depend on transformative shifts toward digitalized, intelligent, and autonomous systems. This Special Issue, entitled "Intelligent Transportation Systems and Traffic Management in Urban Networks," is dedicated to capturing this evolution.

In strict alignment with the objectives of Future Transportation, this Special Issue seeks to redefine the boundaries of urban traffic engineering, and to move beyond incremental improvements, focusing instead on cutting-edge innovations that represent the next generation of transport management. The journal’s mission is to foster sustainable, safe, and efficient mobility; accordingly, this Special Issue will emphasize innovative synergies between emerging technologies, such as AI-driven edge computing, 6G-ready V2X communication, and decentralized IoT architectures, as well as their practical adoption in complex urban ecosystems.

We invite contributions that not only propose theoretical models but also demonstrate high practical value, bridging the gap between advanced research and real-world implementation. We are looking for "future-proof" solutions that address the resilience of road networks, the decarbonization of urban flow, and the integration of autonomous agents into existing infrastructures.

Original research articles and reviews are welcome, and areas of interest include, but are not limited to, the following topics:

  • Cutting-edge AI and deep learning architectures for proactive traffic management and anomaly detection;
  • Next-generation V2X and V2I communication protocols for enhanced network throughput;
  • Autonomous and connected vehicles (CAVs)—control strategies, mixed-flow dynamics, and safety protocols;
  • Dynamic and predictive traffic signal control using real-time big data analytics;
  • Resilient Infrastructure—innovative road designs and smart materials supporting ITS integration;
  • Sustainable urban logistics—reducing the environmental footprint through intelligent routing and carbon-aware management;
  • Digital twins and high-fidelity simulations for urban mobility planning;
  • Smart parking and integrated multi-modal hubs as cornerstones of the "15-min city" concept;
  • Data fusion and cybersecurity in the context of critical transportation infrastructure.

By gathering together pioneering research, this Special Issue aims to provide a roadmap for the transition toward smarter, more resilient, and truly sustainable urban environments. We look forward to receiving your innovative contributions.

Dr. Igor Betkier
Dr. Mateusz Oszczypała
Dr. Aleksander Sobota
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Future Transportation is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1200 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • intelligent transportation systems (ITS)
  • urban traffic management
  • smart mobility
  • traffic signal control
  • connected and autonomous vehicles (CAVs)
  • artificial intelligence in transport
  • V2X communication
  • traffic flow optimization
  • urban road networks
  • sustainable transportation

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Published Papers (1 paper)

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Research

25 pages, 4511 KB  
Article
Queue-Responsive Adaptive Signal Control vs. Webster Optimization: A Multi-Criteria Simulation Assessment at a Signalized Intersection
by Mustafa Albdairi and Ali Almusawi
Future Transp. 2026, 6(2), 92; https://doi.org/10.3390/futuretransp6020092 - 21 Apr 2026
Viewed by 244
Abstract
Traffic signal control at signalized intersections plays a key role in mitigating urban congestion, reducing vehicle emissions, and improving road safety. This study examines three signal control strategies at a four-approach isolated intersection simulated using the Simulation of Urban Mobility (SUMO) microscopic traffic [...] Read more.
Traffic signal control at signalized intersections plays a key role in mitigating urban congestion, reducing vehicle emissions, and improving road safety. This study examines three signal control strategies at a four-approach isolated intersection simulated using the Simulation of Urban Mobility (SUMO) microscopic traffic simulator: a baseline fixed-time plan, a Webster-optimized fixed-time plan, and a queue-responsive adaptive controller implemented through the Traffic Control Interface (TraCI). The strategies were evaluated under balanced traffic demand of 600 vehicles per hour per approach over a 3600 s simulation period. Performance was assessed using eight indicators related to mobility, environmental impact, and safety, including average delay, travel time, queue length, network speed, throughput, CO2 emissions, fuel consumption, and time-to-collision events. The results indicate that the adaptive controller produced the greatest improvements, reducing delay by 14.3%, travel time by 13.6%, CO2 emissions by 9.3%, fuel consumption by 9.4%, and TTC conflicts by 11.2%, while increasing network speed by 47.9%. The Webster-optimized plan achieved moderate improvements, lowering delay by 4.8% and fuel consumption by 5.0% without additional infrastructure requirements. Overall, the findings suggest that both signal re-timing and queue-responsive adaptive control can enhance intersection performance, with the preferred approach depending on available infrastructure and implementation costs. Full article
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