Intelligent Transportation

Intelligent Transportation (IT) project is a real-world datadriven framework which enables real-time visualization, querying, and analysis of dynamic transportation systems.

With IT, we particularly address the fundamental data management and visualization challenges in effective management of dynamic and largescale transportation data, and efficient processing of real-time and historical spatiotemporal queries on transportation networks.

The latest developments in wireless technologies as well as the widespread usage of sensors have led to the recent prevalence of Intelligent Transportation Systems (ITS) for realistic and effective monitoring, decision-making, and management of the transportation systems. Considering the large size of the transportation data, variety of the data (different modalities and resolutions), and frequent changes of the data, the integration, visualization, querying and analysis of such data for large-scale real-time systems are intrinsically challenging data management tasks. Due to these challenges, current ITS applications only support limited data monitoring and analysis capabilities.


At IMSC we developed a real-world datadriven Intelligent Transportation framework, dubbed TransDec (short for Transportation Decision Making), which enables real-time visualization, querying, and analysis of dynamic transportation systems. We build TransDec with a three-tier architecture (presentation tier, query-interface tier, and data tier) that allows users to create customized spatiotemporal queries through an interactive webbased map interface. With this architecture, we particularly address the fundamental data management and visualization challenges in 1) effective management of dynamic and largescale transportation data, and 2) efficient processing of real-time and historical spatiotemporal queries on transportation networks.

TransDec fuses a rich set of real transportation data obtained from RIITS (Regional Integration of Intelligent Transportation Systems) and NAVTEQ. The RIITS dataset is collected by various organizations based in Los Angeles County including Caltrans D7, Metro, LADOT, and CHP. This dataset includes both inventory and real-time data (with update rate as high as every 1 minute) for freeway and arterial congestion, bus location, events, and CCTV snapshots. Moreover, in order to support diverse ITS applications, TransDec contains the transportation network of the entire US, as well as a wide variety of point-of-interest data provided by NAVTEQ.

Subprojects


Year 2011 - 2012

  • Urban Goods Movement
  • Lead by Prof. James Elliott Moore, II (Civil and Environmental Eng.)
  • Develop efficient methods to optimize delivery of goods in urban areas and evaluate impacts across the supply chain.
  • Traffic Sensor Data Analysis and Corridor Monitoring
  • Lead by Prof. Genevieve Giuliano and Prof. Lisa Schweitzer
  • Analyze real-time and historical traffic sensor data to develop new policies towards enhancing the efficacy of the transportation systems, with emphasis on corridor management and congestion pricing.
  • Realtime Traffic Video Analysis
  • Joint work with Prof. Jonathan Taplin (Annenberg Innovation Lab) and Intel Corp.
  • Develop vision-based algorithms to extract traffic flow data from traffic monitoring video streams using Intel's coprocessor.
  • Detailed slides can be found here.
  • General introductory presentation.

  • Technical demo presentation.