Data-driven intelligent transportation systems: A survey

Junping Zhang, Fei Yue Wang, Kunfeng Wang, Wei Hua Lin, Xin Xu, Cheng Chen

Research output: Contribution to journalReview articlepeer-review

734 Scopus citations

Abstract

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 into various forms for different stakeholders. The availability of a large amount of data can potentially lead to a revolution in ITS development, changing an ITS from a conventional technology-driven system into a more powerful multifunctional data-driven intelligent transportation system (D2ITS): a system that is vision, multisource, and learning algorithm driven to optimize its performance. Furthermore, D2ITS is trending to become a privacy-aware people-centric more intelligent system. In this paper, we provide a survey on the development of D2ITS, discussing the functionality of its key components and some deployment issues associated with D2ITS. Future research directions for the development of D2ITS is also presented.

Original languageEnglish (US)
Article number5959985
Pages (from-to)1624-1639
Number of pages16
JournalIEEE Transactions on Intelligent Transportation Systems
Volume12
Issue number4
DOIs
StatePublished - Dec 2011

Keywords

  • Data mining
  • data-driven intelligent transportation systems (DITS)
  • machine learning
  • microblog
  • mobility
  • visual analytics
  • visualization

ASJC Scopus subject areas

  • Automotive Engineering
  • Mechanical Engineering
  • Computer Science Applications

Fingerprint Dive into the research topics of 'Data-driven intelligent transportation systems: A survey'. Together they form a unique fingerprint.

Cite this