Recent Advances in Artificial Intelligence and Big Data for Intelligent Transportation Systems
A special issue of Future Transportation (ISSN 2673-7590).
Deadline for manuscript submissions: 30 June 2026 | Viewed by 3
Special Issue Editors
Interests: intelligent transportation systems; traffic safety warnings; multi-source data fusion; artificial intelligence and video image processing; multi-network integration planning
Interests: transportation digitalization and public administration; governance frameworks for intelligent transportation systems; policy evaluation and risk management in smart mobility; human–AI collaboration in transport decision-making; data ethics and governance in transportation
Interests: game theory; deep reinforcement learning
Interests: intelligent perception and information fusion of road traffic; long-term performance prediction and maintenance decision-making for pavement; mechanisms of vehicle–road coupling interaction; digitalization of transportation infrastructure for the operation and maintenance stage
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Special Issue Information
Dear Colleagues,
Artificial intelligence (AI) and big data are reshaping intelligent transportation systems (ITSs) from perception to decision-making. Rapid urbanization, mixed traffic, and adverse weather call for data-driven methods that are accurate, robust, and scalable. This Special Issue welcomes original research and critical reviews that advance AI- and data-centric approaches for sensing, prediction, control, and management of transportation systems, with clear evidence of methodological novelty, practical impact, and reproducibility.
Topics include, but are not limited to, computer vision and remote sensing for traffic perception and scene understanding; multi-sensor fusion (cameras, radar, LiDAR) and trajectory extraction; behavior and intent prediction; surrogate safety indicators and proactive risk assessment in complex areas (weaving/diverging, intersections, and work zones); traffic state estimation, anomaly/incident detection, and operations optimization; reinforcement learning and optimization for traffic management and control; connected and automated vehicles (CAVs), V2X, and cooperative perception; edge–cloud pipelines, big-data platforms, and federated and privacy-preserving learning; digital twins and simulation for planning and real-time management; robust, interpretable, and trustworthy AI; and datasets, benchmarks, open-source tools, and real-world deployments under adverse weather or low visibility.
We look forward to receiving your contributions.
Dr. Zhe Dai
Dr. Chao Gao
Dr. Ang Ji
Dr. Shi Dong
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 100 words) can be sent to the Editorial Office for announcement on this website.
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 quarterly 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 (ITSs)
- artificial intelligence
- big data analytics
- computer vision
- multi-sensor data fusion
- vehicle trajectory analysis
- surrogate safety measures
- traffic risk assessment
- connected and automated vehicles (CAVs) and V2X
- digital twins for transportation
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