Data-Driven Intelligence for Road Infrastructure Service Performance

This special issue aims to bring together the latest research findings on data-driven intelligence for road infrastructure service performance.

Guest editors:

1) Hui Li, Ph.D., Professor, Tongji University, China (hli@tongji.edu.cn)

2) Xudong Wang, Ph.D., Chief Researcher, Research Institute of Highway Ministry of Transport, China (xd.wang@rioh.cn)

3) Hongzhou Zhu, Ph.D., Professor, Chongqing Jiaotong University, China (zhuhongzhouchina@126.com)

4) Zhongren Wang, Ph.D., Professor, California Department of Transportation (zhongren.wang@dot.ca.gov)

Special issue information:

Road infrastructure service performance is critical for sustainable transportation systems. The 1st Road Infrastructure Service Performance Data Analysis Competition (hosted by the Research Institute of Highway Ministry of Transport, Tongji University, Chongqing Jiaotong University) has generated cutting-edge insights from multi-source field data, including mechanical responses, environmental loads, and structural degradation metrics (e.g., deflection, rutting, cracking).

This special issue focuses on data-driven intelligence for road infrastructure service performance. We invites extended versions of competition award-winning papers and original research leveraging large-scale road performance datasets to advance data-driven intelligence for infrastructure lifecycle management.

Potential topics include, but are not limited to:

•         Inverse Analysis & Multi-source Fusion: Dynamic modulus inversion, spatiotemporal evolution of material properties, fusion of mechanical-environmental-load data.
•         Damage-Cracking-Mechanics Coupling: Quantitative modeling of hidden damage vs. surface cracks, modulus reduction theory, preventive maintenance strategies.
•         High-Throughput Mechanics Data Mining: AI-driven analysis of high-frequency sensor signals (stress/strain, temperature/humidity).
•         Long-Term Performance Prediction: Decoupling environmental-load effects, deterioration modeling of deflection/rutting, residual life estimation.
•         Low-Carbon Performance Optimization: Coupling IRI, rutting, and GHG emissions; eco-efficient maintenance decision-making.

Manuscript submission information:

All submissions must be original and must not be under review elsewhere. All manuscripts should be submitted via the International Journal of Transportation Science and Technology( IJTST）online submission system. Authors should indicate that the paper is submitted for consideration for publication in this special issue. When choosing Manuscript “Article Type” during the submission procedure, click “VSI: Road Data Intelligence”, otherwise your submission will be handled as a regular manuscript.

Author Guidelines: https://www.keaipublishing.com/en/journals/international-journal-of-transportation-science-and-technology/guide-for-authors

All submitted papers should address significant issues pertinent to the theme of this issue and fall within the scope of IJTST. Criteria for acceptance include originality, contribution and scientific merit. All manuscripts must be written in English with high scientific writing standards. Acceptance for publication will be based on referees’ and editors’ recommendations, following a detailed peer review process. An article processing charge of $1,000 will be charged after the article is accepted.