A Geospatial Framework for Dynamic Route Planning Using Congestion Prediction in Transportation Systems

The goal of this research is to develop an end-to-end data-driven system, dubbed TransDec (short for Transportation Decision-Making), to enable decision-making queries in transportation systems with dynamic, real-time and historical data. With TransDec, the report will particularly address the challenges in visualization, monitoring, querying and analysis of dynamic and large-scale spatiotemporal transportation data. TransDec fuses a variety of transportation related real-world spatiotemporal datasets including massive traffic sensor data, trajectory data, transportation network data, and points-of-interest data to create an immersive and realistic virtual model of a transportation system. Atop such a system, TransDec allows for processing a wide range of customized spatiotemporal queries efficiently and interactively. The successful implementation of the TransDec infrastructure in the previous stages of the project has facilitated the infrastructure and knowledge base for two fundamental research lines. The first aims at devising an algorithm for compact and efficient data representation. Compact suggests that the data stored requires as little storage space as possible. The compactness of the data becomes a critical issue as the amount of data stored increases. Efficient representation means that, query times of the data are minimal and allow to work with the system in an interactive fashion. Then, exploiting the results of these lines of research, a new paradigm is presented. In this new storage paradigm the single point of storage, thus the single database server is traded for a cloud computing. This has many advantages, both in terms of storage scalability and maintenance and in terms of the availability of the data to all users as soon as it stored. It is expected that this new paradigm will dominate the research in geospatiotemporal databases in the near future and believe that the seeds presented within this research will play a significant role in it.

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• Record URL:
  https://rosap.ntl.bts.gov/view/dot/23270
• Supplemental Notes:
  • This research was sponsored by the U.S. Department of Transportation, University Transportation Centers Program.
• Corporate Authors:

  METRANS Transportation Center

  University of Southern California
  Los Angeles, CA  United States  90089-0626

  California Department of Transportation

  1120 N Street
  Sacramento, CA  United States  95814

  Research and Innovative Technology Administration

  1200 New Jersey Avenue, SE
  Washington, DC  United States  20590
• Authors:
  • Shahabi, Cyrus
• Publication Date: 2011-1

Language

• English

Media Info

• Media Type: Digital/other
• Edition: Final Report
• Features: Figures; Maps; References;
• Pagination: 35p

Subject/Index Terms

• TRT Terms: Advanced traffic management systems; Databases; Decision making; Integrated systems; Intelligent transportation systems; Real time information; Traffic congestion
• Uncontrolled Terms: Geospatial information; Route planning; Spatiotemporal analysis
• Subject Areas: Data and Information Technology; Highways; Operations and Traffic Management; Planning and Forecasting; Public Transportation; I72: Traffic and Transport Planning;

Filing Info

• Accession Number: 01353910
• Record Type: Publication
• Report/Paper Numbers: METRANS Project 09-26
• Files: UTC, NTL, TRIS, USDOT, STATEDOT
• Created Date: Oct 12 2011 12:54PM