Integration of Heterogeneous Traffic Data to Address Mobility Challenges in the City of El Paso

Daniel Michael Mejia, University of Texas at El Paso


Transportation performance measures are defined as quantitative and qualitative indicators that rely on data or information to explain mobility, traffic congestion, safety, environmental sustainability and other factors. Although performance measures have been used for freeways and other highways, not many have been specified and applied to the freight transportation system. Under the Fixing America’s Surface Transportation Act (FAST Act), state transportation agencies and metropolitan planning organizations in the United States are implementing freight performance measurement systems for performance assessment. This research aims to expand the existing limited freight performance measures and organize them into a comprehensive framework that can be reused for Smart Mobility. The proposed framework consists of four criteria: safety, mobility, traffic congestion, and environmental sustainability. Each criterion consists of several qualitative and quantitative indicators. To address the challenge of integrating freight data of different sources and formats, an ontology-based approach has been proposed, demonstrated and evaluated using ontology evaluation techniques. The ontology was created using a bottom-up, data-driven approach, that included an initial concept map used to verify the conceptualization with domain experts before formalizing it in an ontology. The proposed ontology framework addresses specific metrics for the U.S.–Mexico border in El Paso, TX. However, the proposed framework is sufficiently generic and can be extended to integrate and aggregate data on a larger scale such as a state or country. This work also expands on the idea that a generic framework can be implemented beyond a single year of measurement. Data spanning over three years will also be used to determine the potential use of expanded ontologies in Smart Cities, specifically in Smart Mobility. By increasing the data set and adding external non-related heterogeneous data, this work proposes a generic ontology that can be reused in multiple environments and scenarios. Freight Performance is a foundational piece of Smart Mobility, and by integrating heterogeneous data, it provides a way to evaluate and improve services in Smart Cities.

Subject Area

Computer science

Recommended Citation

Mejia, Daniel Michael, "Integration of Heterogeneous Traffic Data to Address Mobility Challenges in the City of El Paso" (2017). ETD Collection for University of Texas, El Paso. AAI10283749.