Big Data Analytics in Transportation publishes high-quality original research and reviews in a wide range of topics where data driven methods and AI play a central role in transportation.  The goal of the journal is to showcase the latest methodological advances and applications of big data methods in transportation and appropriate implications for policy making. The journal is also interested in the significant impact that these fields are beginning to have on other scientific disciplines as well as many aspects of society and industry. There are countless opportunities where big data intelligence  can augment other methods in transportation systems planning, operations, freight, safety analysis, transit, safe and sustainable cities and emergency management. There are many emerging questions of relevance on ethical, social and privacy, that are also relevant in this domain. The focus is primarily on analytical data driven methods, high quality application based studies will also be considered. BDAT provides a platform to discuss these wide implications — encouraging a cross-disciplinary dialogue — with original research articles, review papers and commentary articles.

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  • Satish V Ukkusuri
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Hybrid (Transformative Journal). How to publish with us, including Open Access

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60 days
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15,043 (2021)

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  1. ACM Digital Library
  2. Baidu
  4. CNKI
  6. Dimensions
  7. EBSCO Discovery Service
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  10. Japanese Science and Technology Agency (JST)
  11. Naver
  12. OCLC WorldCat Discovery Service
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  14. ProQuest-ExLibris Primo
  15. ProQuest-ExLibris Summon
  16. TD Net Discovery Service
  17. Transport Research International Documentation(TRID)
  18. WTI AG
  19. Wanfang
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