Data-Driven Intelligent Transportation Systems
A special issue of Vehicles (ISSN 2624-8921).
Deadline for manuscript submissions: 25 October 2026 | Viewed by 1282
Special Issue Editors
Interests: modeling safety analysis; data driven method; crash analysis; ecometric model; machine learning
Special Issues, Collections and Topics in MDPI journals
Interests: ITS; CPS; autonomous and connected vehicle; transportation digital twin; GNSS; cybersecurity
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The transportation sector is undergoing a fundamental shift driven by the unprecedented growth of data from diverse sources. Connected and automated vehicles, roadside and infrastructure-based sensors, mobile devices, and emerging mobility services generate continuous streams of information that capture detailed characteristics of vehicle trajectories, traffic states, infrastructure conditions, and traveler interactions. This rapidly expanding data ecosystem is becoming indispensable for modeling and managing complex transportation networks.
Advances in computational methods, including machine learning, statistical inference, high-performance simulation, and real-time analytics, now allow for these heterogeneous datasets to be processed, fused, and transformed into predictive and prescriptive insights. Such approaches support system-wide optimization, adaptive traffic management, infrastructure health monitoring, and data-informed planning. Data-driven methodologies are becoming a cornerstone for improving safety, operational efficiency, sustainability, and resilience in transportation systems.
For this Special Issue of Vehicles, titled “Data-Driven Intelligent Transportation Systems,” we invite original research that advances the use of data to analyze, model, and improve mobility systems. Contributions may focus on the development of new analytical frameworks, the integration of multi-source datasets, or applications demonstrating the impact of data-driven approaches on system performance and decision-making. Both theoretical and applied studies are welcome, and interdisciplinary research connecting transportation and data science is encouraged.
We invite you to share your research and contribute to this Special Issue.
Dr. Tanmoy Bhowmik
Dr. Sagar Dasgupta
Dr. Tanmay Das
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. Vehicles is an international peer-reviewed open access monthly 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 1800 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
- data-driven transportation
- intelligent transportation systems
- connected and automated vehicles
- multi-source transportation data
- machine learning in transportation
- mobility data analytics
- transportation system optimization
- transportation big data
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