Development and Validation of Pavement Deterioration Models and Analysis Weight Factors for the NCDOT Pavement Management System Project Kickoff Meeting May 13, 2011 UNC-Charlotte Research Team: Don Chen, Ph.D. Tara Cavalline, P.E. Vincent Ogunro, Ph.D. Darren Thompson
Agenda Background/Research Needs Research Objectives Methodology Proposed Work Schedule Resources from NCDOT
Background/Research Needs NCDOT uses its PMS to conduct funding and performance analyses Key components of PMS: Deterioration models Cost-Benefit Analysis (CBA) Decision trees Research needs: Accuracy and suitability of deterioration models Appropriate weight factors/values for CBA Appropriate trigger points on http://www.ncdot.org/doh/pmu/organization/PMS.html decision trees
Research Objectives Check and validate accuracy and suitability of existing deterioration models, and to develop and validate new models if necessary Select appropriate types of weight factors and their values for cost-benefit analysis Review trigger points on treatment selection decision trees Develop a clear and concise method to evaluate and update deterioration models and weight factors
Research Methodology – Deterioration Models
Research Methodology – Deterioration Models Field data collection
Research Methodology – Cost Benefit Analysis Important to assure appropriate weight factors be chosen to meet departmental condition goals & priorities Obtain expert opinions & executive level input Select prominent types of weight factors & weight values
Research Methodology – Decision Trees Important to consider any new decision variables when selecting models and grouping pavements Obtain input from NCDOT Review trigger points to assure appropriate treatment selection
Proposed Work Schedule
Resources from NCDOT Access to pavement distress data Assistance with roadway identification/selection Information about Cost-Benefit Analysis and Decision Trees Pavement condition survey training Access to selected roadway sections and traffic control
UNCC Project Research Team Don Chen, Ph.D. (PI) Tara Cavalline, PE (Co-PI) Assistant Professor Faculty Associate Vincent Ogunro, Ph.D. (Co-PI) Darren Thompson, (RA) Associate Professor M.S. student
Thank You!
Recommend
More recommend