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Thematic series on Big Traffic Data Analysis for Intelligent Transportation

Journal of Big Data welcomes submissions to the new thematic series on Big Traffic Data Analysis for Intelligent Transportation.

With the popularity of the application of large-scale traffic sensors and surveillance cameras in traffic network analysis and resources allocation, the Intelligent Transportation Systems (ITS) have collected a large amount of structured/unstructured traffic data. This large amount of data provide a good platform to develop new paradigms and strategies in system design, system development, information processing, and performance evaluation in Intelligent Transportation Systems. In the past a few years, extensive research efforts have been dedicated to computational models that analyze and process these large-scale data, but effective tools to manipulate them are still at their infancy. A few key technical challenges are as follows: 1) the difficulty to efficiently and effectively discover low-level and high-level visual features for large-scale traffic data analysis; 2) the challenge to implement a real-time surveillance system that accurately track different vehicles and pedestrians; and 3) the necessity to build an intelligent system that dynamically visualizes the statistics of the large-scale traffic data. This special issue will focuses on the most recent technical progresses on the big data driven applications for ITS, e.g., data processing methods, data-driven computing techniques, and application-oriented system models. The primary objective is to foster focused attention on the latest research progress in this important area. We aim to seek for original contribution of work which addresses the challenges from big data driven ITS. We target the researchers and practitioners from both the industry and academia.

Potential topics include, but are not limited to:

  • Methodologies for big traffic data acquisition and preprocessing
  • Learning techniques for content-concept-based visual retrieval
  • Supervised/Semi-supervised learning methods for traffic data analysis
  • Visual event detection in big visual data
  • Learning visual semantic for online social media content
  • Large scale visual content indexing for traffic data retrieval
  • Learning methods for traffic data harvesting in big data
  • Learning methods for visual knowledge base construction
  • Data mining techniques in traveler information systems
  • Application-oriented big traffic data processing methods
  • High performance computing systems for big data processing
  • Institutional issues with collection, utilization, and storage of big data
  • Data driven control in intelligent transportation networks
  • Advanced technologies for data privacy protection in ITS
  • Big data for transportation planning and system design
  • Transportation communication systems supporting big data
  • Visual semantic understanding in 2D/3D traffic data
  • Computational quality models for large-scale traffic data retrieval
  • Effective and efficient indexing/hashing approaches for traffic data
  • Methodologies for data visualization in large-scale traffic data
  • Big data in transport safety analysis and its applications
  • Reliability and robustness in transportation data analysis
  • Big data for multi-modal transportation analysis
  • Real-time surveillance techniques for large-scale real-world traffic systems
  • Datasets, benchmarks and validation of traffic data analysis

Submission instructions
Before submitting your manuscript, please ensure you have carefully read the Instructions for Authors for Journal of Big Data. The complete manuscript should be submitted through the Journal of Big Data submission system. To ensure that you submit to the correct thematic series please select the appropriate section in the drop-down menu upon submission. In addition, indicate within your cover letter that you wish your manuscript to be considered as part of the thematic series on Big Traffic Data Analysis for Intelligent Transportation. All submissions will undergo rigorous peer review and accepted articles will be published within the journal as a collection.

Deadline for submissions
1 March, 2015

Lead Guest editor
Luming Zhang, National University of Singapore, Singapore

Guest editor
Yingjie Xia, Zhejiang University, China

Submissions will also benefit from the usual advantages of open access publication:

  • Rapid publication: Online submission, electronic peer review and production make the process of publishing your article simple and efficient
  • High visibility and international readership in your field: Open access publication ensures high visibility and maximum exposure for your work - anyone with online access can read your article
  • No space constraints: Publishing online means unlimited space for figures, extensive data and video footage
  • Authors retain copyright, licensing the article under a Creative Commons license: articles can be freely redistributed and reused as long as the article is correctly attributed

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