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Title: High Performance Computing Traffic Simulations for Real-Time Traffic Control of Mobility in Chattanooga Region

Abstract

In 2019, highway congestion wasted over 3 billion gallons of fuel and caused 8.8 billion hours of lost productivity.1 Research has shown that introducing near-real time traffic controls can significantly reduce congestion. Validated and calibrated traffic simulations enable the modeling of transportation systems and the evaluation of different traffic control actions and schemes given a variety of circumstances that represent likely future scenarios. The developed scenarios can inform the deployment of controls in near real-time to improve freight and passenger vehicle congestion and energy use. In this work, we present simulations used to model the traffic in the Chattanooga, Tennessee, metropolitan area. Simulations were constructed and calibrated using a variety of local, data science enhanced, data sources utilizing open source software including the Simulation of Urban Mobility (SUMO) simulator. High-Performance Computing (HPC) provides a scalable platform with enough computing for the high-fidelity simulation of many scenarios and the application of advance data science especially for large-scale systems. Our simulations include microscopic simulations at a corridor level for traffic signal control, and mesoscopic simulations to evaluate regional operational controls and infrastructure.

Authors:
 [1];  [1];  [1];  [2];  [2];  [2];  [1];  [2];  [1]; ORCiD logo [1];  [2];  [2];  [1];  [2];  [1];  [2]
  1. National Renewable Energy Laboratory (NREL), Golden, CO (United States)
  2. Oak Ridge National Laboratory
Publication Date:
Research Org.:
National Renewable Energy Lab. (NREL), Golden, CO (United States)
Sponsoring Org.:
USDOE Advanced Research Projects Agency - Energy (ARPA-E), Energy Efficient Mobility Systems Program
OSTI Identifier:
1605709
Report Number(s):
NREL/PO-2C00-75009
DOE Contract Number:  
AC36-08GO28308
Resource Type:
Conference
Resource Relation:
Conference: Presented at the 2019 Tennessee Sustainable Transportation Forum & Expo, 1-2 October 2019, Knoxville, Tennessee
Country of Publication:
United States
Language:
English
Subject:
97 MATHEMATICS AND COMPUTING; traffic simulation; real-time traffic control; high performance computing; HPC

Citation Formats

Ugirumurera, Juliette, Severino, Joseph A, Wang, Qichao, Ravulaparthy, Srinath, Berres, Anne, Nugent, Philip, Sorensen, Harry, Moore, Alex, Todd, Austin, Nag, Ambarish, Tennille, Sarah, Peterson, Steven, Potter, Kristin C, Xu, Haowen, Jones, Wesley B, and Sanyal, Jibonananda. High Performance Computing Traffic Simulations for Real-Time Traffic Control of Mobility in Chattanooga Region. United States: N. p., 2020. Web.
Ugirumurera, Juliette, Severino, Joseph A, Wang, Qichao, Ravulaparthy, Srinath, Berres, Anne, Nugent, Philip, Sorensen, Harry, Moore, Alex, Todd, Austin, Nag, Ambarish, Tennille, Sarah, Peterson, Steven, Potter, Kristin C, Xu, Haowen, Jones, Wesley B, & Sanyal, Jibonananda. High Performance Computing Traffic Simulations for Real-Time Traffic Control of Mobility in Chattanooga Region. United States.
Ugirumurera, Juliette, Severino, Joseph A, Wang, Qichao, Ravulaparthy, Srinath, Berres, Anne, Nugent, Philip, Sorensen, Harry, Moore, Alex, Todd, Austin, Nag, Ambarish, Tennille, Sarah, Peterson, Steven, Potter, Kristin C, Xu, Haowen, Jones, Wesley B, and Sanyal, Jibonananda. Mon . "High Performance Computing Traffic Simulations for Real-Time Traffic Control of Mobility in Chattanooga Region". United States. https://www.osti.gov/servlets/purl/1605709.
@article{osti_1605709,
title = {High Performance Computing Traffic Simulations for Real-Time Traffic Control of Mobility in Chattanooga Region},
author = {Ugirumurera, Juliette and Severino, Joseph A and Wang, Qichao and Ravulaparthy, Srinath and Berres, Anne and Nugent, Philip and Sorensen, Harry and Moore, Alex and Todd, Austin and Nag, Ambarish and Tennille, Sarah and Peterson, Steven and Potter, Kristin C and Xu, Haowen and Jones, Wesley B and Sanyal, Jibonananda},
abstractNote = {In 2019, highway congestion wasted over 3 billion gallons of fuel and caused 8.8 billion hours of lost productivity.1 Research has shown that introducing near-real time traffic controls can significantly reduce congestion. Validated and calibrated traffic simulations enable the modeling of transportation systems and the evaluation of different traffic control actions and schemes given a variety of circumstances that represent likely future scenarios. The developed scenarios can inform the deployment of controls in near real-time to improve freight and passenger vehicle congestion and energy use. In this work, we present simulations used to model the traffic in the Chattanooga, Tennessee, metropolitan area. Simulations were constructed and calibrated using a variety of local, data science enhanced, data sources utilizing open source software including the Simulation of Urban Mobility (SUMO) simulator. High-Performance Computing (HPC) provides a scalable platform with enough computing for the high-fidelity simulation of many scenarios and the application of advance data science especially for large-scale systems. Our simulations include microscopic simulations at a corridor level for traffic signal control, and mesoscopic simulations to evaluate regional operational controls and infrastructure.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2020},
month = {3}
}

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