TY  - SER
AU  - Ukkusuri,Satish V.
AU  - Ludovic,Leclercq
AU  - Sharma,Anuj
ED  - SpringerLink (Online service)
TI  - Journal of Big Data Analytics in Transportation
SN  - 2523-3564
CY  - Singapore
PB  - Springer Nature Singapore, Imprint: Springer.
KW  - Transportation engineering
KW  - Traffic engineering
KW  - Computational intelligence
KW  - Data mining
KW  - Transportation Technology and Traffic Engineering
KW  - Computational Intelligence
KW  - Data Mining and Knowledge Discovery
N2  - 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
UR  - http://link.springer.com/journal/42421
ER  -