Application of Artificial Intelligence in Traffic Management

Special Issue Editors

Special Issue Information

Dear Colleagues,

This Special Issue calls for original research and review articles focusing on the transformative role of Artificial Intelligence (AI) in addressing the challenges and complexities of modern traffic management systems. AI technologies are transforming how transportation networks operate, offering innovative solutions to enhance efficiency, safety, and sustainability. This Special Issue aims to explore (i) the development and application of advanced AI technology in optimizing and controlling road and waterway transportation, (ii) the integration of AI with intelligent transportation systems (ITSs) to improve decision making and real-time traffic operations, and (iii) AI’s potential in promoting sustainable, intelligent, and resilient urban transportation systems, as well as ocean-going transportation systems.

This Special Issue will complement the existing literature by providing a comprehensive, cross-sectoral perspective on AI applications in waterway and road traffic management. The topics of interest include, but are not limited to, the following:

  • AI-driven traffic forecasting and congestion management;
  • AI-based systems for sustainable transportation planning;
  • AI in traffic safety analysis and accident prevention;
  • AI in ocean-going vessels’ decision making;
  • AI in maritime management;
  • Big data analytics for shipping and traffic monitoring.

Dr. Weihao Ma
Prof. Dr. Dongfang Ma
Guest Editors

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Keywords

  • artificial intelligence
  • traffic management
  • maritime management
  • intelligent transportation systems
  • adaptive traffic control
  • traffic forecasting and optimization
  • ocean-going vessel

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Published Papers (1 paper)

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Research

20 pages, 3787 KiB  
Article
Joint Optimization of Route and Speed for Methanol Dual-Fuel Powered Ships Based on Improved Genetic Algorithm
by Zhao Li, Hao Zhang, Jinfeng Zhang and Bo Wu
Big Data Cogn. Comput. 2025, 9(4), 90; https://doi.org/10.3390/bdcc9040090 - 8 Apr 2025
Viewed by 288
Abstract
Effective route and speed decision-making can significantly reduce vessel operating costs and emissions. However, existing optimization methods developed for conventional fuel-powered vessels are inadequate for application to methanol dual-fuel ships, which represent a new energy vessel type. To address this gap, this study [...] Read more.
Effective route and speed decision-making can significantly reduce vessel operating costs and emissions. However, existing optimization methods developed for conventional fuel-powered vessels are inadequate for application to methanol dual-fuel ships, which represent a new energy vessel type. To address this gap, this study investigates the operational characteristics of methanol dual-fuel liners and develops a mixed-integer nonlinear programming (MINLP) model aimed at minimizing operating costs. Furthermore, an improved genetic algorithm (GA) integrated with the Nonlinear Programming Branch-and-Bound (NLP-BB) method is proposed to solve the model. The case study results demonstrate that the proposed approach can reduce operating costs by more than 15% compared to conventional route and speed strategies while also effectively decreasing emissions of CO2, NOx, SOx, PM, and CO. Additionally, comparative experiments reveal that the designed algorithm outperforms both the GA and the Linear Interactive and General Optimizer (LINGO) solver for identifying optimal route and speed solutions. This research provides critical insights into the operational dynamics of methanol dual-fuel vessels, demonstrating that traditional route and speed optimization strategies for conventional fuel vessels are not directly applicable. This study provides critical insights into the optimization of voyage decision-making for methanol dual-fuel vessels, demonstrating that traditional route and speed optimization strategies designed for conventional fuel vessels are not directly applicable. It further elucidates the impact of methanol fuel tank capacity on voyage planning, revealing that larger tank capacities offer greater operational flexibility and improved economic performance. These findings provide valuable guidance for shipping companies in strategically planning methanol dual-fuel operations, enhancing economic efficiency while reducing vessel emissions. Full article
(This article belongs to the Special Issue Application of Artificial Intelligence in Traffic Management)
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