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U.S. Department of Transportation U.S. Department of Transportation Icon United States Department of Transportation United States Department of Transportation

Data Analysis

Long-Term Bridge Performance (LTBP) InfoBridge

January 2019 marked the release of the Long-Term Bridge Performance (LTBP) Program’s InfoBridge™ web portal, a newly developed website for dissemination and visualization of bridge data, information, and products developed by the LTBP Program. The portal’s main purpose is to leverage the analytical capability of the highway bridge research community, and fulfill the Federal Highway Administration’s (FHWA’s) responsibility to provide transparency and ready access to data collected through Federal research programs. InfoBridge also enables bridge owners with no or limited access to bridge asset management software to manage their bridge inventories through a seamless user interface that incorporates state of the art querying and visualization tools. For more information visit

Source: FHWA

Bridge Performance Transition Forecast

The Bridge Performance Transition Forecast tool in InfoBridge™ provides a list of bridges that may transition from one condition state to another over a user-specified period. Under Performance Forecast, select the Bridge Performance Transition Forecast tab to access the tool.

The starting year for the forecast is set to the latest year for which the National Bridge Inventory (NBI) data are available. For selected bridges, users can specify the condition in the start year and the desired condition in a later year. Users may also input the minimum probability of occurrence for the forecast. Users select one of two deterioration models—the proportional hazards deterioration model or the machine learning model—to perform the calculations.

The resulting list of bridges, and a few pertinent NBI items, are displayed on screen and can also be exported into an Excel® spreadsheet.

"Figure. Screenshot. This figure is a screen capture of the Bridge Performance Transition Forecast tool on the Long-Term Bridge Performance InfoBridge™ website. In this screen capture, two tabs are shown: “Network Performance Forecast” and “Bridge Performance Transition Forecast.” Bridge Performance Transition Forecast is selected. In the top left corner, below the tabs, is a blue drop-down menu labeled “Network Performance Forecast Models.” There are also options to select condition states and years, which are shown as four dropdown menus labeled, from left to right, “Condition Going From,” “In Year,” “To,” and “In Year.” On the same line, there is a text box labeled “Probability of Occurrence (percent) Greater Than Or Equal To.” Next to these selections, there is a blue button labeled “Display Results.” There is a solid gray header that separates the selection area from the results. The heading reads “Bridge Performance Transition Forecast,” which corresponds with the name of the selected tab. In the same header, on the right side of the page, is an “Export Table” link. Below this heading is a light blue display bar that shows the user selections in sentence form, including the selected year, condition state, and selected model. The main body of the screen capture shows a table containing the user-selected list of bridges. The table is arranged in columns and rows. The column headings correspond with various National Bridge Inventory (NBI) fields, and the rows contain the NBI records for each bridge. The following NBI fields are shown as column headings in this table: “State Name,” “Structure Number,” “Owner Agency,” “Deck Area (square feet),” “Year Built,” “Main Design Material Type Value,” “Main Construction Design Value,” and “Probability of Occurrence (percent).” Below the table, there are navigation controls to change the page numbers and to increase or decrease the number of rows per page."Source: FHWA

LTBP Deterioration Condition Forecast Models

Bridge condition forecast models are an essential component for implementing a data-driven bridge asset management program by optimizing the funding allocation that is associated with bridge replacement, rehabilitation, repairs, maintenance, or preservation. The LTBP Program developed three deck condition forecast models (Base Models, Survival Models, and Machine Learning Models) and implemented them in the January 2020 LTBP InfoBridge release.

The three models represent three levels of modeling complexities. Base Models are statistically deterministic and compute the time-in-condition for each bridge type from historical National Bridge Inventory (NBI) data and apply those to each bridge for deck condition forecasting. Survival models derive condition rating transition probabilities from survival-analysis curves and use Markov chain probabilistic methods to forecast future condition ratings. Machine-learning models are developed by mining the historical NBI and climate data using a deep learning approach. The three models are being further refined to improve their accuracy. Over 335,000 bridges have at least one model associated with them. For more information visit

Source: FHWA

Last updated: Tuesday, November 16, 2021