IEEE Transactions on Intelligent Transportation Systems· 2018Q1· Review
Big Data Analytics in Intelligent Transportation Systems: A Survey
- 1,069citations
- Q1SCImago
- 2018year
Short summary
This survey reviews the history, characteristics, and framework of big data analytics in Intelligent Transportation Systems (ITS), highlighting applications like accident analysis, traffic flow prediction, and public transport planning.
AI-generated from the title and abstract; the full text is not read.
Key points
- Big data analytics is a flourishing field within Intelligent Transportation Systems (ITS).
- The paper reviews the history, characteristics, and a framework for big data analytics in ITS.
- Key application categories include road traffic accidents analysis, traffic flow prediction, and public transportation planning.
- Several case studies demonstrate the practical implementation of big data analytics in ITS.
- Open challenges in applying big data analytics to ITS are discussed.
AI-generated from the title and abstract; the full text is not read.
Abstract
Big data is becoming a research focus in intelligent transportation systems (ITS), which can be seen in many projects around the world. Intelligent transportation systems will produce a large amount of data. The produced big data will have profound impacts on the design and application of intelligent transportation systems, which makes ITS safer, more efficient, and profitable. Studying big data analytics in ITS is a flourishing field. This paper first reviews the history and characteristics of big data and intelligent transportation systems. The framework of conducting big data analytics in ITS is discussed next, where the data source and collection methods, data analytics methods and platforms, and big data analytics application categories are summarized. Several case studies of big data analytics applications in intelligent transportation systems, including road traffic accidents analysis, road traffic flow prediction, public transportation service plan, personal travel route plan, rail transportation management and control, and assets maintenance are introduced. Finally, this paper discusses some open challenges of using big data analytics in ITS.
The authors' abstract, as published at the source. IEEE Transactions on Intelligent Transportation Systems, 2018 · DOI ↗
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