AI-Driven Transportation Systems: Innovations, Challenges, and Future Mobility

A special issue of Systems (ISSN 2079-8954). This special issue belongs to the section "Artificial Intelligence and Digital Systems Engineering".

Deadline for manuscript submissions: 20 November 2025 | Viewed by 1395

Special Issue Editors


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Guest Editor
Faculty of Maritime and Transportation, Ningbo University, Ningbo, China
Interests: autonomous driving; traffic demand forecasting; mixed traffic flow modelling and simulation; traffic state estimation; multimodal vehicle trajectory; deep learning
Faculty of Maritime and Transportation, Ningbo University, Ningbo, China
Interests: transportation big data analysis; autonomous driving simulation model; parking planning and design; transportation and energy integration; emergency logistics; transportation safety analysis
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
School of Transportation and Civil Engineering and Architecture, Foshan University, Foshan, China
Interests: modeling and simulation of complex traffic systems; intelligent network transportation

Special Issue Information

Dear Colleagues,

The integration of artificial intelligence (AI) into transportation systems has revolutionized the development of next-generation vehicles and mobility ecosystems. This Special Issue focuses on cutting-edge research leveraging AI to enhance the safety, efficiency, and sustainability of transportation systems. Topics include autonomous driving algorithms, AI-optimized traffic flow prediction, human–machine interactions in intelligent vehicles, energy management for electric/hybrid vehicles, digital healthcare engineering (DHE), and AI-enabled predictive maintenance for transport infrastructure. Emerging challenges such as edge computing for real-time decision-making, explainable AI in safety-critical scenarios, and the ethical implications of AI-driven mobility will also be explored. Submissions are encouraged to address multimodal transportation integration, including aerial drones, maritime vessels, and hyperloop systems, with an emphasis on system-level interoperability. Additionally, we welcome studies on digital twin frameworks, federated learning for distributed transportation networks, and AI applications in reducing carbon footprints. This Issue aims to bridge theoretical advancements with practical implementations, fostering discussions on regulatory frameworks and the societal acceptance of AI-powered transportation.

Prof. Dr. Rongjun Cheng
Dr. Xiaofei Ye
Dr. Cong Zhai
Guest Editors

Manuscript Submission Information

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Keywords

  • intelligent transportation systems
  • trajectory prediction
  • ship performance calculation and ship path planning
  • crew health system
  • traffic accident reconstruction
  • digital twin technology
  • deep learning
  • intelligent parking systems
  • transportation and energy integration emergency logistics
  • application of large language models in the transportation field

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Published Papers (1 paper)

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Review

20 pages, 8834 KiB  
Review
Human Digital Healthcare Engineering for Enhancing the Health and Well-Being of Seafarers and Offshore Workers: A Comprehensive Review
by Meng-Xuan Cui, Kun-Hou He, Fang Wang and Jeom-Kee Paik
Systems 2025, 13(5), 335; https://doi.org/10.3390/systems13050335 - 1 May 2025
Viewed by 826
Abstract
With over 50,000 merchant vessels and nearly two million seafarers operating globally, more than 12,000 maritime incidents in the past decade underscore the urgent need for proactive safety measures to ensure the structural integrity of aging ships and safeguard the well-being of seafarers, [...] Read more.
With over 50,000 merchant vessels and nearly two million seafarers operating globally, more than 12,000 maritime incidents in the past decade underscore the urgent need for proactive safety measures to ensure the structural integrity of aging ships and safeguard the well-being of seafarers, who face harsh ocean environments in remote locations. The Digital Healthcare Engineering (DHE) framework offers a proactive solution to these challenges, comprising five interconnected modules: (1) real-time monitoring and measurement of health parameters, (2) transmission of collected data to land-based analytics centers, (3) data analytics and simulations leveraging digital twins, (4) AI-driven diagnostics and recommendations for remedial actions, and (5) predictive health analysis for optimal maintenance planning. This paper reviews the core technologies required to implement the DHE framework in real-world settings, with a specific focus on the well-being of seafarers and offshore workers, referred to as Human DHE (HDHE). Key technical challenges are identified, and practical solutions to address these challenges are proposed for each individual module. This paper also outlines future research directions to advance the development of an HDHE system, aiming to enhance the safety, health, and overall well-being of seafarers operating in demanding maritime environments. Full article
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