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71 Figure B.4. Example METIS screen. using a pavement quality index), minimizing delay, minimizing (typically the AASHTO Pontis BMS), FHWA's HERS-ST, the number of structurally deficient bridges, and mitigating seis- and AASHTO's AssetManager. Where an agency does not mic risk. As is the case for AssetManager, METIS uses analysis re- have a management system implemented to predict future sults generated from other systems to support its projections. IHS conditions, one can use HERS-ST as an alternative for The end user reviews each solution, selecting one solution to predicting pavement conditions, and FHWA's NBIAS for rule out at each analysis step, and the system uses this informa- predicting bridge needs. tion to narrow in on an optimal allocation of resources between 3. It is feasible to predict measures related to other structure- assets for best meeting the competing objectives. related risk using available tools, and supplemental analy- ses, provided an agency has compiled data on these risks. B.4 Conclusions One of the three pilot participants had the data available The research team developed the following conclusions on to support such an exercise. Chapter 4 describes available the basis of the pilot analysis: tools for assessing structure-related risks. 4. The three pilot participants had sufficiently detailed data 1. IHS owners typically have data readily available concern- and tools to support analysis of pavement and bridge con- ing highway inventory and traffic, pavement conditions, ditions. They had data on some other assets besides pave- bridge conditions, crashes, rest areas and planned projects. ments and bridges, but generally lacked analytical tools or IHS owners have limited data available on other structures models for predicting conditions of these assets over time. besides bridges, as well as on roadside assets. Further, IHS Chapter 4 describes data and tools needed for modeling owners typically lack at least some of the data required to needs of these assets. support the risk analysis approach recommended as part of 5. It is feasible to use a utility maximization approach to ap- the Interstate Asset Management Framework. proximate the optimal allocation of resources between 2. It is feasible to predict basic measures of pavement condi- different IHS assets to achieve a set of objectives. However, tion, bridge condition, mobility, and safety for IHS assets supplemental analysis outside of existing tools available using readily available data and tools. Key analytical tools from AASHTO and FHWA is needed to implement such for such an exercise include an agency's PMS and BMS an approach.