As the world faces growing challenges in urban mobility, safety, and sustainability, data-driven solutions have become essential for building efficient and intelligent transportation systems. Transportation big data analysis serves as a key enabler to extract valuable insights from massive, multi-source traffic data and address critical issues in modern mobility.

This special issue on Transportation Big Data Analysis invites innovative research on theories, methods, and real-world applications related to multi-source data fusion, spatiotemporal mining, and advanced machine learning. It aims to bridge data analytics with intelligent traffic management, connected vehicles, public transit, safety, and low-carbon mobility, toward building safer, more efficient, and sustainable smart transportation systems.

This special issue is open for submissions on the following topics including but not limited to:

• Multi-source transportation data fusion and quality assurance for heterogeneous data (e.g., GPS, Smart card, LoT sensor, and Mobile signaling data)

• Spatiotemporal pattern mining of urban mobility flows using big data and graph neural networks

• Privacy-preserving data sharing and anonymization techniques for transportation big data

• Deep learning-based short-term traffic flow prediction and congestion hotspot identification

• Data-driven optimization of traffic signal control and dynamic route planning for smart cities

• Big data analytics for connected and autonomous vehicles (CAVs) and cooperative driving systems

• Anomaly detection and risk assessment for transportation safety using real-time big data

• Data-enabled evaluation and optimization of electric vehicle (EV) charging infrastructure and usage patterns

• High-performance computing frameworks for scalable transportation big data analytics

We look forward to receiving your contributions and advancing the discourse on Transportation Big Data Analysis. Together, we can pave the way for more intelligent, efficient, and safe transportation systems that benefit future smart cities.

Guest Editors

Lead Guest Editor: 

Prof. Weiwei Jiang, Associate Professor
Beijing University of Posts and Telecommunications, China
E-Mail: jww@bupt.edu.cn
Interests: Satellite communication, Internet of Things, and Artificial intelligence-based wireless communications.

Co-Editors:

Prof. Stefano Cirillo, Assistant Professor (Tenure-Track)
University of Salerno, Italy
E-Mail: scirillo@unisa.it
Interests: Data profiling, Data mining, Artificial intelligence, Data privacy, Big data analysis, and Social networks.

Prof. Ahmad Taher Azar, Professor
Prince Sultan University, Riyadh, Kingdom Saudi Arabia
E-Mail:  aazar@psu.edu.sa
Interests: Computational intelligence, AI, Machine learning, Big data, Robotics, and Control systems.

Prof. Muhammet Deveci, Senior Research Fellow
University College London, London, UK and Professor, National Defence University, Istanbul, Turkey
E-Mail: m.deveci@ucl.ac.uk
Interests: Computational intelligence, Fuzzy decision making, Big data analytics, Sustainable transportation, Autonomous vehicles, and Intelligent mobility systems.

Submission Deadline

The deadline for manuscript submissions is December 31, 2026, but we can accommodate extensions on a case-by-case basis. All papers will be published as open access articles upon acceptance.

Submission Instructions

Manuscripts should be prepared according to the guidelines of Digital Transportation and Safety and submitted through the journal's online submission system. All submitted papers will undergo a rigorous peer-review process. 

For inquiries regarding this special issue, please contact the guest editors or the journal's Executive Editor.