IEEE Open Journal of Intelligent Transportation Systems

Scope & Guideline

Unlocking Potential in Intelligent Transport Engineering.

Introduction

Delve into the academic richness of IEEE Open Journal of Intelligent Transportation Systems with our guidelines, detailing its aims and scope. Our resource identifies emerging and trending topics paving the way for new academic progress. We also provide insights into declining or waning topics, helping you stay informed about changing research landscapes. Evaluate highly cited topics and recent publications within these guidelines to align your work with influential scholarly trends.
LanguageEnglish
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PublisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Support Open AccessNo
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AbbreviationIEEE OPEN J INTEL TR / IEEE Open J. Intell. Transp. Syst.
Frequency1 issue/year
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Address445 HOES LANE, PISCATAWAY, NJ 08855-4141

Aims and Scopes

The IEEE Open Journal of Intelligent Transportation Systems focuses on advancing the field of intelligent transportation through innovative research and the application of emerging technologies. The journal seeks to address the complexities of modern transportation systems by integrating various disciplines such as machine learning, automation, and data analytics.
  1. Intelligent Transportation Systems (ITS) Development:
    Research that enhances the efficiency, safety, and sustainability of transportation systems through the integration of advanced technologies such as IoT, AI, and machine learning.
  2. Autonomous Vehicle Technologies:
    Exploration of technologies and methodologies related to the development and deployment of autonomous vehicles, focusing on perception, decision-making, and control systems.
  3. Traffic Management and Optimization:
    Studies aimed at improving traffic flow and reducing congestion through innovative modeling, simulation, and optimization techniques.
  4. Public Transportation Innovations:
    Research focusing on enhancing public transport systems through data-driven approaches, smart technologies, and user-centric designs.
  5. Cybersecurity in Transportation Systems:
    Investigating the resilience and security of transportation networks against cyber threats, ensuring safe operation of connected and automated vehicles.
  6. Sustainability and Environmental Impact:
    Research aimed at understanding and mitigating the environmental impacts of transportation systems, including studies on electrification and eco-friendly transportation solutions.
The IEEE Open Journal of Intelligent Transportation Systems is currently witnessing several emerging trends that reflect the evolving landscape of transportation research. These themes highlight the journal's commitment to addressing contemporary challenges in transportation systems.
  1. Machine Learning and AI Applications:
    An increase in research applying machine learning and artificial intelligence to various aspects of transportation, including traffic prediction, autonomous vehicle control, and intelligent transportation system design.
  2. Connected and Cooperative Vehicle Technologies:
    A growing focus on the development of connected vehicle technologies that enable communication between vehicles and infrastructure for improved safety and efficiency.
  3. Digital Twins and Simulation Models:
    Research on digital twins and simulation approaches for real-time monitoring and management of transportation systems is gaining prominence, reflecting the industry's move towards data-driven decision-making.
  4. Sustainable Transportation Solutions:
    Emerging themes around sustainability, including electric and shared mobility solutions, are increasingly prevalent as researchers seek to address climate change and urbanization challenges.
  5. Cybersecurity in Intelligent Transportation Systems:
    As transportation systems become more interconnected, there is a rising emphasis on ensuring cybersecurity and resilience against potential threats, reflecting the importance of safe operations in modern ITS.

Declining or Waning

In recent years, certain themes within the IEEE Open Journal of Intelligent Transportation Systems have shown a decline in prominence. This may indicate a shift in the research focus of the journal or a maturation of previously emerging areas.
  1. Traditional Traffic Engineering Methods:
    There has been a noticeable decline in papers focusing on conventional traffic engineering techniques, as the field shifts towards more data-driven and technology-based approaches.
  2. Basic Vehicle Safety Systems:
    Research on fundamental vehicle safety technologies, such as anti-lock braking systems or basic collision avoidance systems, appears to be waning, with a focus now on more integrated and intelligent systems.
  3. Static Traffic Modeling:
    The use of static traffic models that do not incorporate real-time data or adaptive algorithms is becoming less common, as dynamic and data-driven models gain traction.
  4. Manual Traffic Management Techniques:
    With the rise of automation and intelligent systems, traditional manual management strategies for traffic control are seeing reduced emphasis in favor of automated and adaptive solutions.

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