Students built on a prior capstone project that had developed a methodology called LAMP (Locate, Analyze, Measure, and Prioritize) which established a dashboard that identified the type and frequency of disruptions experienced by communities within a city. Data was obtained from DOT road/lane closures, accidents, 311 data, and weather events. Students used Streetlight Data to monitor transportation GPS data. Students' work contributed to the development of a model to better consider the social and economical costs of failed infrastructure into urban planning, in a nearly automated manner. The Quantifying Urban Infrastructure Economic and Transit Disruptions (QUIETeD) methodology helped to build on the datasets identified in LAMP to provide a structured, approach to quickly evaluate the transit and partial Social Costs in a format that allows for growth in future versions.

Keywords: Modelization, Civil Engineering, Urban Planning