Big Data Analytics in Intelligent Transportation Systems: A Survey

By Li Zhu, F. Yu, Yige Wang, Bin Ning, Tao Tang. IEEE transactions on intelligent transportation systems (Print), 2019

869 citations recorded by the source corpus.

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.

Subfields: Building and Construction, Information Systems and Management, Signal Processing

View Paper: https://www.semanticscholar.org/paper/dbabab9bf5955558f73a37644f4bb626106a6d73

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In Building and Construction

In Information Systems and Management

Mubashir Husain Rehmani

In Signal Processing

Citations in the corpus

Differential Privacy Techniques for Cyber Physical Systems: A Survey (2018, background): “Since the beginning of 1970s, ITSs have been developing in various forms and are now considered to be the future of transportation systems [223].”
A Survey on Blockchain for Big Data: Approaches, Opportunities, and Future Directions (2020, background): “Big data analytics have also found applications in smart grid and intelligent transportation systems, and representative surveys can be found in [27, 28].”
A Survey on Modern Deep Neural Network for Traffic Prediction: Trends, Methods and Challenges (2020, background): “[11] provides another up-to-date survey of the field.”
Deep Learning for Intelligent Transportation Systems: A Survey of Emerging Trends (2020, background): “[120], who outline the use of big-data within ITS.”
Process (2020, background): “Most of the previous works [10, 11, 12, 13, 14, 15, 16, 17, 18, 19] on traffic modeling focus on predicting speed, volume, density and travel time, which have achieved remarkable success in this field.”
A Review of Fault Detection and Diagnosis for the Traction System in High-Speed Trains (2020, background): “If there is no high demand on the real-time ability of fault diagnosis, the recent artificial intelligent techniques-based fault diagnosis methods are promising for high-speed trains, such as deep learning [53], big data [6], and reinforcement learning [121].”