TransDec: A Data-Driven Framework for Decision-Making in Transportation Systems

In this paper, we present 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, we 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 virtual system, TransDec allows for processing a wide range of customized spatiotemporal queries efficiently and interactively. TransDec has a three-tier architecture, including a multimodal spatiotemporal database, an expressive and efficient query-engine and an interactive map-mashup presentation tier. With this paper, first we describe the components of the TransDec architecture. Subsequently, as proof-of-concept we present a number of decision-making queries enabled by TransDec.


Issue Date:
2009-03
Publication Type:
Conference Paper/ Presentation
PURL Identifier:
http://purl.umn.edu/207726
Total Pages:
15




 Record created 2017-04-01, last modified 2017-08-28

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