CV

Graduate Research Assistant

Florida International University

Development of pavement performance models, artificial intelligence applications, teaching assistance, writing of research articles

• Pavement Management

Staff Engineer I

Nichols Consulting Engineers (NCE)

Assited in the enhacement of the pavement management software (PMS) StreetSaver developed by the Metropolitan Transportation Commission in California.

• Pavement Management

Undergraduate Research Assistant

Center for Transportation Infrastructure Systems (CTIS)

Assisted with tasks related to engineering education, research writing, and enhancements to the pavement management software StreetSaver..

• Pavement Management

Treasurer

Florida Engineering Society (FES) at FIU

Helped with the writing of reports, management of finances, and organized events.

Treasurer

National Honor Society at UTEP

Helped in the organization of events, manage finances.

PhD

Florida International University (FIU)

Civil Engineering

BSc

University of Texas at El Paso (UTEP)

Civil Engineering

How to Estimate IRI Based on PCI Values to Report the Pavement Condition of Local Roads

Springer

Transportation agencies need performance indicators to report the pavement condition. Many local transportation agencies use the Pavement Condition Index (PCI) to report the pavement condition. In 1986, the World Bank developed the International Roughness Index (IRI) to measure the irregularity of the road surface. IRI is an indicator of roughness for straight horizontal road segments simulating a quarter-car travelling at 50 mi/h. In the United States, the Federal Highway Administration (FHWA) has established criteria to report a pavement in good, fair, or poor condition. IRI, percentage of cracking, and rutting thresholds are established by the FHWA to assess the pavement condition. Local roads represent, in terms of mileage, the largest percentage of all roads in the U.S. IRI is not typically measured on local roads due to speed restrictions, short section lengths, traffic signals, traffic congestion, intersection treatments, and geometry characteristics. PCI and IRI represent different concepts and measure different aspects of pavement performance. Despite these differences, there is a need to report the pavement condition of local roads in a consistent manner. PCI and IRI datasets from a total of 25,229 asphalt surfaced pavement sections were analyzed using statistical descriptive analysis and expert knowledge to develop transfer equations. The product of this hybrid modeling approach is a best-fit sigmoidal equation presented in this paper to estimate the IRI value from the PCI value, and recommended threshold equivalent values to report the pavement condition.

Artificial Intelligence Applications for Efficient Road Asset Management Practices

International Road Federation

The paper summarizes trends and current research performed in the field of Artificial Intelligence for Efficient Road Asset Management Practices.