IEEE Transactions on Intelligent Transportation Systems

Aims & Scope

The theoretical, experimental and operational aspects of electrical and electronics engineering and information technologies as applied to Intelligent Transportation Systems (ITS).

Intelligent Transportation Systems are defined as those systems utilizing synergistic technologies and systems engineering concepts to develop and improve transportation systems of all kinds.

The scope of this interdisciplinary activity includes the promotion, consolidation and coordination of ITS technical activities among IEEE entities, and providing a focus for cooperative activities, both internally and externally.

View Aims & Scope

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Metrics & Ranking

Impact Factor

Year	Value
2025	8.4
2024	7.90

Journal Rank

Year	Value
2024	906

Journal Citation Indicator

Year	Value
2024	46481

SJR (SCImago Journal Rank)

Year	Value
2024	2.589

Quartile

Year	Value
2024	Q1

h-index

Year	Value
2024	224

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Abstracting & Indexing

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

• Scopus
• Google Scholar
• Web of Science

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Subjects & Keywords

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

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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.

• T-GCN: A Temporal Graph Convolutional Network for Traffic Prediction

  Citation: 2343

  Authors: Ling, Yujiao, Chao, Yu, Pu, Tao, Min, Haifeng

• Detecting Stress During Real-World Driving Tasks Using Physiological Sensors

  Citation: 1620

  Authors: J.A., R.W.

• Data-Driven Intelligent Transportation Systems: A Survey

  Citation: 1499

  Authors: Junping, Fei-Yue, Kunfeng, Wei-Hua, Xin, Cheng

• Deep Reinforcement Learning for Autonomous Driving: A Survey

  Citation: 1410

  Authors: B Ravi, Ibrahim, Victor, Patrick, Ahmad A. Al, Senthil, Patrick

• A Review of Motion Planning Techniques for Automated Vehicles

  Citation: 1287

  Authors: David, Joshue, Vicente, Fawzi

• The Impact of Cooperative Adaptive Cruise Control on Traffic-Flow Characteristics

  Citation: 1229

  Authors: Bart, Cornelie J. G., Ruben

• ERFNet: Efficient Residual Factorized ConvNet for Real-Time Semantic Segmentation

  Citation: 1227

  Authors: Eduardo, Jose M., Luis M., Roberto

• Automatic Road Crack Detection Using Random Structured Forests

  Citation: 1191

  Authors: Yong, Limeng, Zhiquan, Fan, Zhensong

• Travel-Time Prediction With Support Vector Regression

  Citation: 1165

  Authors: C.-H., J.-M., D.T.

• Deep Architecture for Traffic Flow Prediction: Deep Belief Networks With Multitask Learning

  Citation: 1012

  Authors: Wenhao, Guojie, Haikun, Kunqing

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