Transportation Research Part D

The maritime industry accounts for the transportation of over 80% of international trade by volume. Despite the recent progress, the maritime sector faces significant sustainability challenges, ranging from greenhouse gas emissions, environmental pollution to energy inefficiency. The emergence of machine learning (ML) offers a diverse toolkit to confront these challenges. This Special Issue aims to provide a platform for interdisciplinary research to enhance sustainability of the maritime transportation in practice. We therefore invite contributions utilizing ML techniques to achieve the goal with empirical insights and policy implications.


We are interested in reviews and original research on the following topics, but are not limited to:

• Monitoring, assessing, predicting, and mitigating environmental impacts of maritime transportation, including emissions of greenhouse gases, pollutants, and noise, using ML approaches;

• ML-driven methods in reducing ship fuel consumption and improving efficiency;

• Integration of carbon-neutral technologies using ML frameworks;

• Exploring the use of renewable energy sources such as wind and solar power for operations of ports and ships, using ML approaches;

• ML applications for gaining empirical insights and practical contribution of sustainable maritime transportation.


Guest editors:

Jasmine Siu Lee Lam, Ph.D., Chair Professor, Technical University of Denmark, Denmark (

Xiwen Bai, Ph.D., Associate Professor, Tsinghua University, China (

Zhong Shuo Chen, Ph.D., Assistant Professor, Xi'an Jiaotong-Liverpool University, China (

Maohan Liang, Ph.D., Research Fellow, National University of Singapore, Singapore (


Manuscript submission information:

All submissions must be original and may not be under review elsewhere. All manuscripts will be submitted via the Transportation Research Part D (TRD) 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: Machine Ln. Maritime", otherwise your submission will be handled as a regular manuscript.


Author Guidelines: All submitted papers should address significant issues pertinent to the theme of this issue and fall within the scope of TRD. 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.


Submission deadline: 28 Feb 2025


KeywordsMaritime sustainability, maritime decarbonization, machine learning, sustainable shipping and port, intelligent sustainable maritime logistics

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