Project: #198 Proactive management of mobility impact of interdependent subsurface utility and roadway construction through incentives Progress Report - Reporting Period Ending: Sept. 30, 2019 Principal Investigator: Burcu Akinci Status: Active Start Date: Jan. 1, 2018 End Date: June 30, 2020 Research Type: Applied Grant Type: Research Grant Program: FAST Act - Mobility National (2016 - 2022) Grant Cycle: 2017 Mobility21 UTC Progress Report (Last Updated: Oct. 1, 2019, 7:08 a.m.) % Project Completed to Date: 20 % Grant Award Expended: 20 % Match Expended & Document: 20 USDOT Requirements Accomplishments In the past six months, we were developing a general infrastructure failure model that predicts the probability of failure for infrastructure, with the specific applications to both gas pipelines and bridges. We were using the historical pipeline leak records, pipeline characteristics data, and traffic flow data to develop a pipeline leak prediction model using Negative Binomial model. We were also using records of bridge maintenance, historical bridge inspection information, and historical traffic flow data to model probabilistic bridge failure and the associated maintenance cost using Random-effects Censored model. These two models provided insights for predicting deterioration of pipeline and bridges, particularly its failure, as well as their associated maintenance cost and social costs. We also used dynamic traffic simulation tools to predict traffic flow impacts provided with maintenance disruptions in traffic networks. We used MAC-POSTS, developed by the Co-PI Qian under another UTC project ‘Mobility Data Analytics’, that encapsulates the impacts to two classes of vehicles, cars and trucks, under right-of-way construction projects (i.e. constructions on bridges or pipelines) In the remainder of the project period, we will test our predictive using real-world data in terms of accuracy and validate our model with industry experts’ opinions. A real-world road network setting in the Pittsburgh region will be used to test those models. This project has supported one phd research assistant. We have discussed the initial outcomes with PennDOT. Impacts 1. This project, if successful, would be able to provide a fundamental knowledge to understand infrastructure failures and their associated costs (both maintenance cost and social costs) from analyzing real-world data, and help optimally design maintenance schedules and strategies. 2. Part of the research was presented to students at Carnegie Mellon University, which has great potential to educate the next generation of engineers, economists and scientist. 3. The initial outcomes from this research have been shared with PennDOT through emails and phone discussions, with Cranberry Township through in-person meetings, and Peoples' Gas Other 1. A database contains Pennsylvania bridge issues repaired by maintenance, with related weather, traffic flow, and bridge inspection information. 2. A database contains pipeline characteristics, and gas leak events in Great Pittsburgh area. 3. Statistical models to predict pipeline gas leak and bridge failures. Outcomes New Partners n/a Issues n/a