Date of Award


Document Type


Degree Name

Master of Science


Department of Systems Engineering and Management

First Advisor

William E. Sitzabee, PhD.


The United States roadway system has deteriorated over time due to its age, increasing delays in completing preventative maintenance, and the lack of timely repairs following damage to the infrastructure. Proper asset management drives the need for generalized methods to integrate new sensing capabilities into existing Intelligent Transportation Systems in a time efficient and cost effective manner. In this thesis, we present a methodology for the deployment of new sensors into an existing ITS system. The proposed methodology employs a three phase approach that incorporates data modeling, spatial analysis in Geographic Information Systems, and cost optimization to provide enhanced decision support when deploying new sensing capabilities within an existing ITS. Additionally, we also demonstrate the usefulness of computing while integrating these new sensors using a guardrail sensor case study and focusing on data modeling. The results of the three phase methodology demonstrate an effective means for planning new sensor deployments by analyzing tradeoffs in equipment selection yielding the minimum cost solution for a given set of requirements. Furthermore, the results of the data models demonstrate necessary considerations that must be made with a systems engineering method. The data models accomplish this while accounting for asset management principles taking a systematic approach and incorporating engineering principles.

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DTIC Accession Number