Journal of Advanced Transportation

Aims & Scope

The Journal of Advanced Transportation (JAT) is a fully peer reviewed international journal in transportation research areas related to public transit, road traffic, transport networks and air transport.

It publishes theoretical and innovative papers on analysis, design, operations, optimization and planning of multi-modal transport networks, transit & traffic systems, transport technology and traffic safety.

Urban rail and bus systems, Pedestrian studies, traffic flow theory and control, Intelligent Transport Systems (ITS) and automated and/or connected vehicles are some topics of interest.

Highway engineering, railway engineering and logistics do not fall within the aims and scope of JAT.

Metrics & Ranking

Abstracting & Indexing

Journal is indexed in leading academic databases, ensuring global visibility and accessibility of our peer-reviewed research.

• Scopus
• Google Scholar
• Directory of Open Access Journals (DOAJ)
• Web of Science

Subjects & Keywords

Journal’s research areas, covering key disciplines and specialized sub-topics in Business, Management and Accounting, Computer Science, Economics, Econometrics and Finance and Engineering, designed to support cutting-edge academic discovery.

Licensing & Copyright

This journal operates under an Open Access model. Articles are freely accessible to the public immediately upon publication. The content is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0), allowing users to share and adapt the work with proper attribution.

Copyright remains with the author(s), and no permission is required for non-commercial use, provided the original source is cited.

Policy Links

This section provides access to essential policy documents, guidelines, and resources related to the journal’s publication and submission processes.

• Aims scope
• Homepage
• Oa statement
• Author instructions
• License terms
• Review url
• Board url
• Copyright url
• Plagiarism url
• Preservation url
• Apc url
• License

Plagiarism Policy

This journal follows a plagiarism policy. All submitted manuscripts are screened using reliable plagiarism detection software to ensure originality and academic integrity. Authors are responsible for proper citation and acknowledgment of all sources, and any form of plagiarism, including self-plagiarism, will not be tolerated.

For more details, please refer to our official: Plagiarism Policy.

APC Details

The journal’s Article Processing Charge (APC) policies support open access publishing in Business, Management and Accounting, Computer Science, Economics, Econometrics and Finance and Engineering, ensuring accessibility and quality in research dissemination.

This journal requires an Article Processing Charge (APC) to support open access publishing, covering peer review, editing, and distribution. The current APC is 2,630.00 USD. Learn more.

Explore journals without APCs for alternative publishing options.

Most Cited Articles

The Most Cited Articles section features the journal's most impactful research, based on citation counts. These articles have been referenced frequently by other researchers, indicating their significant contribution to their respective fields.

• Acceptance of Driverless Vehicles: Results from a Large Cross-National Questionnaire Study

  Citation: 235

  Authors: Sina, Joost, Miltos, Bart, Riender

• Driver Distraction Identification with an Ensemble of Convolutional Neural Networks

  Citation: 233

  Authors: Hesham M., Yehya, Mohamed H., Mohamed N.

• A capacity related reliability for transportation networks

  Citation: 228

  Authors: Anthony, Hai, Hong K., Wilson H.

• Street network theory of organization in nature

  Citation: 216

  Authors: Adrian

• Studying the Safety Impact of Autonomous Vehicles Using Simulation-Based Surrogate Safety Measures

  Citation: 216

  Authors: Mark Mario, Qingyun, Long T., Hai L.

• Efficient planning of berth allocation for container terminals in Asia

  Citation: 204

  Authors: Akio, Ken'Ichiro, Chan Weng

• Spatiotemporal Traffic Flow Prediction with KNN and LSTM

  Citation: 200

  Authors: Xianglong, Danyang, Yu, Shengrui

• An AI‐based approach for transit route system planning and design

  Citation: 200

  Authors: M. Hadi, Hani S.

• A Review of Traffic Congestion Prediction Using Artificial Intelligence

  Citation: 190

  Authors: Mahmuda, Sara

• DSRC versus 4G-LTE for Connected Vehicle Applications: A Study on Field Experiments of Vehicular Communication Performance

  Citation: 186

  Authors: Zhigang, Xiaochi, Xiangmo, Michael H., Zhongren