Resilience Assessment and Enhancement of Transportation Infrastructure and Transportation Systems

Special issue information:

Climate change is reshaping our world, with increasing frequency of floods and landsides threatening transportation and infrastructure. Innovative approaches that integrate AI, optimization models, and transportation resilience strategies are crucial for the future of transportation networks.

This special issue focuses on cutting-edge research on resilience assessment and enhancement of transportation infrastructure and transportation systems. We invite high-quality contributions in the aspects of theoretical advancements, methodological innovations, and practical applications from researchers and practitioners in this domain.

Potential topics include, but are not limited to:

• Pre-disaster Resistance: Robust design strategies, advanced materials, protective technologies for enhancing infrastructure resistance.
• In-disaster Adaptability: Real-time condition monitoring, adaptive traffic management, responsive emergency management.
• Post-disaster Recovery: Rapid damage assessment, network recovery strategies, structural repair and reinforcement technology.
• AI-Resilience Synergy: AI-enhanced resilience assessment and modeling, multi-objective optimization, AI-driven decision-making, reinforcement learning in mobility systems.

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: Resilience, AI and Optimization”, otherwise your submission will be handled as a regular manuscript. Manuscripts should adhere to the journal's Author Guidelines.

Submission deadline: 31 August 2025

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.

Guest editors:

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

2) Zhao Zhang, Ph.D., Professor, Beihang University, China (zhaozhang@buaa.edu.cn)

3) Daniel Sperling, Ph.D., Professor, University of California, the USA (dsperling@ucdavis.edu)

4) John Harvery, Ph.D., Professor, University of California, the USA (jtharvey@ucdavis.edu)

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