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IEEE Transactions on Intelligent Transportation Systems is a peer-reviewed journal published by IEEE, covering Traffic control and management, Autonomous Vehicle Technology and Safety, Traffic Prediction and Management Techniques. Over its lifetime it has published 12,206 papers, which have received 518,813 citations.
| Publisher | IEEE |
|---|---|
| Reference style | Numbered (IEEE) Numbered — [1], [2] in the text [1] A. Smith, B. Jones, and C. Lee, "A representative article title," IEEE Transactions on Intelligent Transportation Systems, vol. 12, no. 3, pp. 45–58, 2023.
Formats any DOI in IEEE Transactions on Intelligent Transportation Systems style. No sign-up. |
| Abbreviation (ISO-4) | TITS |
| Publishes research in | Traffic control and management Autonomous Vehicle Technology and Safety Traffic Prediction and Management Techniques Transportation Planning and Optimization Vehicular Ad Hoc Networks (VANETs) |
| ISSN | 1524-9050 |
| Citation impact (2-yr) | 7.11 |
| h-index | 263 |
| i10-index | 7,555 |
| Top institutions publishing here | Beijing Jiaotong University |
| Journal website | ieeexplore.ieee.org |
| You get | A submission-ready PDF and the editable LaTeX source — ready to submit. |
Citations each year’s papers have accumulated so far — the most recent years are still building up.
Accurate and real-time traffic forecasting plays an important role in the intelligent traffic system and is of great significance for urban traffic planning, traffic management, and traffic control. However, traffic forecasting has always been considered an “open” scientific issue, owing to the constraints of urban road network topological structure and the law of dynamic change…
Accurate and timely traffic flow information is important for the successful deployment of intelligent transportation systems. Over the last few years, traffic data have been exploding, and we have truly entered the era of big data for transportation. Existing traffic flow prediction methods mainly use shallow traffic prediction models and are still unsatisfying for many…
This paper presents methods for collecting and analyzing physiological data during real-world driving tasks to determine a driver's relative stress level. Electrocardiogram, electromyogram, skin conductance, and respiration were recorded continuously while drivers followed a set route through open roads in the greater Boston area. Data from 24 drives of at least 50-min duration were collected…
For the last two decades, intelligent transportation systems (ITS) have emerged as an efficient way of improving the performance of transportation systems, enhancing travel security, and providing more choices to travelers. A significant change in ITS in recent years is that much more data are collected from a variety of sources and can be processed…
Intelligent vehicles have increased their capabilities for highly and, even fully, automated driving under controlled environments. Scene information is received using onboard sensors and communication network systems, i.e., infrastructure and other vehicles. Considering the available information, different motion planning and control techniques have been implemented to autonomously driving on complex environments. The main goal is…
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