Multi-Resolution Modeling

Texas A&M Transportation Institute
4050 Rio Bravo Drive
Suite 212
El Paso, TX 79902
(915) 521-8107
[email protected]

Eric Nava is an Associate Research Scientist at the Texas A&M Transportation Institute (TTI), where he specializes in multi-resolution modeling, dynamic traffic assignment (DTA), traffic simulation, and intelligent transportation systems (ITS). With more than 16 years of experience, Eric has worked extensively on network-wide simulation modeling, traffic signal operations, integrated corridor management, and advanced traffic operations planning. His career includes leading strategic transportation studies and supporting regional stakeholders in optimizing traffic management and ITS infrastructure.

Eric’s work has spanned numerous high-profile projects across the United States. In Texas, he developed VISSIM and DynusT models to evaluate lane-tapering strategies and road user costs during major construction on the I-35 corridor in Waco, helping TxDOT minimize delays and improve work zone safety. In Arizona, he led ITS capability assessments and traffic signal management strategies during the $615 million I-10 Broadway Curve reconstruction, implementing innovative approaches to mitigate congestion and maintain mobility. He also guided the development of diversion route playbooks and signal timing strategies for the I-10 Integrated Corridor Management Planning Study, which provided agencies with actionable tools for managing freeway closures. Earlier in his career, Eric spearheaded regional DTA deployments and staff training for agencies such as the Maricopa Association of Governments, DRCOG, DVRPC, EPMPO, and Portland Metro, advancing the application of dynamic network modeling across multiple regions.

Eric holds a B.S. in Civil Engineering from the University of Texas at El Paso and an M.S. in Civil Engineering from the University of Arizona. His work continues to push the boundaries of transportation modeling by integrating mesoscopic and microscopic simulation tools to improve mobility, safety, and operational efficiency.