Computing Community Consortium Blog

The goal of the Computing Community Consortium (CCC) is to catalyze the computing research community to debate longer range, more audacious research challenges; to build consensus around research visions; to evolve the most promising visions toward clearly defined initiatives; and to work with the funding organizations to move challenges and visions toward funding initiatives. The purpose of this blog is to provide a more immediate, online mechanism for dissemination of visioning concepts and community discussion/debate about them.

Research Data Exchange (RDE) Adds More Data Environments for Download!

December 1st, 2016 / in Announcements, research horizons, Research News / by Helen Wright

Research Data Exchange logoThe Research Data Exchange (RDE) is a web-based data resource provided by the USDOT Intelligent Transportation Systems (ITS) Program. It collects, manages, and provides access to archived and real-time multi-source and multi-modal data to support the development and testing of ITS applications.

The following new data environments are now available for download:

  • Intelligent Network Flow Optimization Simulation (INFLO SIM) is a VISSIM simulation model for the US 101 freeway corridor in San Mateo, CA. This model is used to assess the impacts of the INFLO Prototype Dynamic Speed Harmonization (SPD-HARM) application. This set of performance measure files was calculated based on the VISSIM outputs of 24 scenarios runs of the SPD-HARM application. The models covered various market penetration rates, incident durations and weather conditions.
  • Seattle I-405 was generated by the Trajectory Conversion Algorithm Version 2.3 (TCA) using the SAE J2735 Basic Safety Message (BSM) based on the I-405 corridor in Seattle, Washington. This data environment was generated to provide data files for a variety of operational conditions, market penetrations and communication strategies in order to examine the effectiveness of advanced analytical techniques in using connected vehicle data to predict congestion in a way that enables a transportation system manager to take steps to mitigate potential bottlenecks.
  • AMS San Mateo Testbed was used to model and simulate mobility applications including INFLO (queue warning, speed harmonization, and cooperative adaptive cruise control) and MMITSS (intelligent traffic signal systems). Four baseline scenarios, combining different levels of demand, incident, and weather conditions were used for testing the performance effects of these applications and feature four types of datasets: Cluster Analysis Data, Calibration Data, Network Files and Simulation Output.
  • AMS Dallas Testbed was used to test several Active Transportation and Demand Management (ATDM) strategies including Dynamic Shoulder Lane, Dynamic Signal Timing, Dynamic Routing, Ramp Metering and Dynamic Priced Parking. The Testbed is developed using the DIRECT software (Dynamic Intermodal Routing Environment for Control and Telematics), which was developed by researchers at Southern Methodist University (SMU) and features four types of datasets: Cluster Analysis Data, Calibration Data, Testbed Files and Simulation Results.
Researchers, application developers, and others are invited to visit the RDE website to explore how they may use the available data and resources.
Research Data Exchange (RDE) Adds More Data Environments for Download!

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