“AI-Driven Modelling and Enhancement for Transportation Resilience under Disasters”

Call for Papers – Special Issue: “AI-Driven Modelling and Enhancement for Transportation Resilience under Disasters”

Journal: Transportation Research Part D: Transport and Environment
Publisher: Elsevier
Submission deadline: 12 February 2027

Overview

This special issue—published by Elsevier—focuses on leveraging Artificial Intelligence (AI) and data-driven methodologies to enhance the resilience of transportation systems in the face of natural and human-made disasters. As climate change and urbanization increase the frequency of disruptions, the ability to predict, assess, and recover from these events is critical. This issue seeks research that operationalizes AI across the three pillars of resilience management: pre-event vulnerability prediction, post-event real-time assessment, and adaptive emergency response.

Key Research Themes

• Pre-Event Prediction: AI and machine-learning models designed to forecast system resilience and identify structural or operational vulnerabilities before a disruption occurs.

• Post-Event Assessment: Data-driven and sensing-based approaches for real-time monitoring of network performance, damage assessment, and structural integrity following a disaster.

• Adaptive Response: AI-driven decision-making frameworks for real-time traffic management, emergency resource deployment, and optimized recovery workflows.

• Resilient Optimization: Data-informed network design and optimization to ensure transport systems can maintain core functionality under stress.

• Technological Integration: Synergizing big data, IoT sensing, and autonomous decision systems to mitigate disaster impact.

Submission Details

• Submission deadline: 12 February 2027.

• Submission portal: https://submit.elsevier.com/TRD

• Special Instructions: You must select the article type “AI-Driven Resilience” during the submission process. Failure to select this exact type will result in your paper being handled as a regular manuscript.

• Submission Standards: The journal invites original research that demonstrates high scientific standards, originality, and significant contribution to transportation resilience. All submissions must fall within the scope of Transportation Research Part D and adhere to the Author Guidelines.

Guest Editor Team

• Dr. Zhao Zhang, Beihang University (zhaozhang@buaa.edu.cn)

• Dr. Xiangdong Xu, Tongji University (xiangdongxu@tongji.edu.cn)

• Dr. Jiangping Zhou, The University of Hong Kong (zhoujp@hku.hk)

• Dr. Albert Solé Ribalta, Universitat Oberta de Catalunya (asolerib@uoc.edu)

Why This Issue Matters

Transportation systems are the lifelines of modern society. When these systems fail during disasters, the consequences are catastrophic. This special issue provides a vital research hub for scholars pushing the boundaries of AI, seeking not just to "manage" traffic, but to create intelligent, self-healing networks capable of surviving and recovering from the unprecedented disruptions of our time.

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