Big Data and Artificial Intelligence in Transportation Systems: Methods and Applications
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Transportation and Future Mobility".
Deadline for manuscript submissions: 20 April 2026
Special Issue Editor
Interests: multisource sensor data processing and mining; accuracy and precision of big data; real-time non-recurrent event detection and management; management of connected and automated vehicles; mass evacuation operations; parallel simulation of microscopic traffic network; traffic flow theory; big data-based human behavior analysis and modification; dynamic traffic modeling and simulations
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Special Issue Information
Dear Colleagues,
Transportation systems are filled with vast amounts of data from various sources, such as GPS devices, traffic cameras, roadway detectors, Bluetooth sensors, and crowdsourced platforms like social media. These data streams offer unprecedented opportunities for researchers and practitioners to develop data-driven approaches for improving traffic operations and management. Artificial intelligence, particularly foundation models, has been widely adopted across various domains and holds significant potential in the field of transportation.
The synergy between big data and artificial intelligence presents immense potential to address the multifaceted challenges of transportation systems. Big data obtained from multiple sources can be fused to enhance traffic monitoring, anomaly detection, and prediction. Meanwhile, artificial intelligence, like foundation models and large language models, can integrate multimodal datasets and provide advanced support in decision-making, management strategies, and policy development.
This Special Issue will focus on the innovative applications of Big Data and Artificial Intelligence in addressing emerging challenges in transportation systems. It invites contributions that highlight the methodologies, novel data, and application scenarios.
High-quality original studies including, but not limited to, the following topics:
- Application of big data and artificial intelligence to enhance the traffic monitoring, anomaly detection, and traffic prediction;
- Foundation models and Large Language Models for Intelligent Transportation Systems, customer sentiment, traffic evaluations;
- High-performance computing and edge-computing techniques for big data-driven models;
- Crowdsourced data mining from social media, and reports;
- Spatio-temporal perspective big data.
Prof. Dr. Lee D. Han
Guest Editor
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. Applied Sciences 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 2400 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
- big data analytics and visulization
- artificial intelligence
- machine learning
- foundation models
- large language models
- sensors
- traffic detectors
- crowdsourcing
- connected vehicles
- traffic operations and mangement
- high performance computing
- mobility
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