Intelligent Transport System and Sustainable Traffic Management

Dear Colleagues,

The rapid advancement of big data and artificial intelligence (AI) has significantly impacted the field of transportation, and the growing availability of large-scale, multi-modal traffic data, combined with powerful AI-based analytical tools, is transforming transportation systems and reshaping our ability to make data-driven decisions in this field. The integration of AI with big data analytics enables us to uncover hidden patterns in traffic flows, optimize traffic management processes, and enhance prediction accuracy, all of which are crucial for modernizing transportation infrastructure and improving efficiency, safety, and sustainability. This Special Issue focuses on the intersection of big data and AI within transportation, aiming to showcase state-of-the-art theories, applications, and systems. We seek innovative methods and solutions that address the inherent challenges of processing complex, high-dimensional transportation data, improving predictive accuracy with AI models, and enhancing the reliability of optimized traffic solutions. Key topics include, but are not limited to:

1. Big data and artificial intelligence applications in transportation;
2. Spatio-temporal big data analytics in transportation;
3. Traffic flow data imputation and prediction in transportation systems;
4.  Multi-modal traffic data analytics;
5. Data-driven approaches in traffic optimization;
6. Traffic data mining;
7. Transportation engineering;
8. Traffic management using AI-based techniques;
9. Emerging technologies in railway, road, and urban rail transit systems;
10. Multimodal transport systems. 

Dr. Jinlei Zhang
Dr. Wei Ma
Guest Editors

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