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Forecasting Performance After Bridge Management Actions


Federal and state policies are increasingly directing bridge owners to manage the performance of their structural assets and networks. Performance management is a discipline that quantifies all of the many performance expectations which stakeholders may have for the transportation system, and evaluates projects, programs, and policies in light of performance outcomes. Bridge management systems are being developed and upgraded to support multi-objective forecasting and optimization in support of performance management.

For most aspects of transportation system performance, quantitative measures can be observed to change over time. For example, physical condition of infrastructure assets will deteriorate. Traffic growth and land use patterns will cause congestion to increase and mobility to decline. A combination of deterioration and traffic growth causes safety to decline. Global climate change causes risks to increase as facilities are subject to forces outside their sites’ historical experience. Research studies by NCHRP, SHRP, OECD, state governments, and others have begun to quantify the changes in performance, yielding forecasting models that may be useful in bridge management systems.

When performance is measured or forecast to move outside of acceptable levels, or when preventive or mitigative needs are identified, agencies apply corrective actions. The consequences of these actions can be broadly grouped into two categories: immediate improvements in performance that occur because of the action; and changes in the rate of future performance degradation as a result of the action. Quantitative knowledge of both of these effects is necessary for accurate justification of investments and for optimizing the scope and timing of treatments.

AASHTO, state governments, and international agencies have begun to develop bridge management systems that can apply multi-objective analysis to a broad range of agency actions affecting different aspects of transportation system performance. These systems require quantitative forecasting models to predict immediate and long-term changes in performance that might occur because of the projects that are generated or described in these systems. Such forecasts impact customer and stakeholder satisfaction, or utility. By affecting the timing of future actions, they also affect life cycle costs.


The objective of this research project is to develop quantitative models for predicting the immediate and long-term performance effects of the kinds of actions typically modeled in bridge management systems. Long term effects may include risk reduction, delaying future expenditures, level of service, or increasing useful asset life.

This objective considers condition, safety, mobility, risk, life cycle cost, and all other relevant aspects of performance. The products should rely, to the greatest extent possible, on available data in the National Bridge Inventory, in the AASHTO Guide Manual for Bridge Element Inspection (2010 version), and on other data likely to become available in bridge management systems.

Potential benefits

Multi-objective optimization is defined and discussed in great detail in NCHRP Report 590, and is being implemented in active projects by AASHTO, state governments, and other agencies. All of these systems require forecasting capabilities for the objectives to be considered. A few agencies have these forecasting capabilities in one form or another, often embedded in written guides or in custom-developed spreadsheet models. Most agencies have no such capability at the present time. Existing ad hoc methods lack the ability to be applied to the broad range of bridge management system users without a considerable amount of additional research.

Many states lack the resources or expertise to perform such research. As a result, they lack the ability to fully implement the multi-objective analysis in new bridge management systems. The proposed research will save as much of 90-95% of the effort that would otherwise be required for each state to develop its own performance forecasting models. It is envisioned that the proposed research will be sufficiently general, and offer sufficient implementation guidance to agencies, that they may be able to shorten or avoid independent research efforts to develop the necessary action effectiveness models.

Relationship to existing body of knowledge

Existing research studies, including NCHRP Report 590 and the FHWA Long-Term Bridge Program, have identified lists of relevant performance measures and applicable actions, but have not quantified the effectiveness of such actions. AASHTO, NCHRP, SHRP, and state governments have developed design guidelines for maintenance, rehabilitation, functional improvement, and risk mitigation treatments that sometimes quantify expected effects. However, such information is often expressed in terms of defects, characteristics, or measurement units that are not generally recorded in bridge management systems.

The proposed research will need to rely on existing publications and on data sets that may be available in some of the bridge owner agencies. It is believed that suitable models are not currently available from any source, but that they can be developed by simplifying and generalizing existing information sources to fit the data available in bridge management systems.


It is envisioned that the research will involve at least the following tasks:

  1. Gather and synthesize the performance measures relevant to bridge management systems, including domestic and international practice. The research should consider measures that may become possible with the completion of the FHWA long-term performance program, and measures that may be broadly applicable across asset management.
  2. Gather and synthesize descriptions of maintenance, rehabilitation, improvement, and mitigation treatments as typically practiced in bridge owner agencies. Such treatments may be applicable to multiple structure materials and design types as typically found in agency inventories.
  3. Gather and synthesize design guides and other documentation prepared by NCHRP, AASHTO, SHRP, and bridge owner agencies, that may be helpful in quantifying the immediate or long-term effects of bridge treatments. Identify the data requirements of these methods and assess the potential of modifying such methods to fit data routinely available, or likely to become available, in bridge management systems.
  4. For actions and performance measures where no existing publications are relevant, assess the potential for estimation of effectiveness models from agency-collected performance data and maintenance records. Identify agencies that can supply the data, obtain the data, and develop the effectiveness models using statistically valid methods.
  5. Develop a uniform format for documenting the new methods, suitable for use by agencies and by bridge management system designers for incorporating the models into bridge management systems. Complete the documentation of the recommended methods in this format.
  6. Develop guidance for agencies to use in adapting the recommended models to best fit their own maintenance and operating practices, climate, and other local conditions.
  7. Prepare a Manual for Forecasting Performance after Bridge Management Actions, as a user-friendly but formal guide to help agencies establish the models in their bridge management systems.

Implementation activities

This research is envisioned to feed directly into existing efforts to develop multi-objective optimization models in bridge management systems. It will provide default models and methods each agency can use as it customizes BMS models for its own use. Continued FHWA and AASHTO support for bridge management systems, and in general for asset management and performance management, will help to ensure successful and widespread implementation.

Estimated funding requirements

This research is estimated to cost $500,000 and require 36 months to complete, including the Final Report.


Sponsoring Committee:AKT50, Bridge and Structures Management
Date Posted:06/11/2012
Date Modified:06/18/2012
Index Terms:Bridge management systems, Service life, Level of service, Inspection, Asset management, Forecasting, Life cycle costing,
Cosponsoring Committees: 
Administration and Management
Maintenance and Preservation
Bridges and other structures

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