Pavement Management Systems: Putting Data to Work (2017) / Chapter Skim
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Pages 9-26
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10 Overview In the recently published Pavement Asset Management, the authors documented the progression of pavement management from "early rudimentary efforts in the 1960s to a comprehensive technology, economic, and business-based process" today (Haas et al.
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11 of different formats. The final component of a pavement management system, the feedback loop, is intended to ensure that the projects and performance trends from the field are input back into the pavement management system to keep the database current and to update the analysis parameters.
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12 assessment models, and network optimization models (Zimmerman and ERES 1995)
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13 The short- and long-term needs included in the Pavement Management Roadmap were organized into the following four themes: • Theme 1 -- Use of Existing Technology and Tools: The problem statements in this area include recommendations for technology and tools to support traditional applications of pavement management. • Theme 2 -- Institutional and Organizational Issues: The recommendations in this theme address issues related to workforce development, communication, contracting, and organizational structure.
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14 At the time this synthesis was written, the final rules had not been issued for either of the NPRMs. Therefore, some of the minimum requirements listed previously may change; however, the overall intent of the rules is not expected to change significantly.
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15 typically provide more flexibility in terms of configuring the database, the analysis parameters, and the reporting features. The additional flexibility is often accompanied by more sophisticated modeling approaches; however, these additional features come at a higher cost than the public domain software programs.
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16 that they are currently using automated and semi-automated processes for collecting and reporting pavement condition information (excluding friction) , as shown in Figure 3 (http://www.fhwa.dot.
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17 state-provided data, local agencies may elect to collect pavement condition data for their own road network independently. Transportation agencies have taken a variety of approaches to address data quality efforts.
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18 FIGURE 6 Quality management activities suggested during each stage of data collection (Flintsch and McGhee 2009)
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19 trends in Prediction Modeling The AASHTO Pavement Management Guide describes several characteristics associated with pavement performance modeling that reflect general trends in the industry. These trends indicate that the following practices are used commonly in pavement management (AASHTO 2012)
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20 from the differences in the state's pavement condition survey procedures and the distress definitions that served as the basis for the MEPDG models. Another trend in pavement performance modeling involves the incorporation of uncertainty into pavement management performance modeling.
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FIGURE 8 Decision tree used by the Minnesota DOT for asphalt and asphalt over concrete pavements (http://www.dot.state.mn.us/materials/pvmtmgmtdocs/Bituminous_ Decision_Tree_07-01-12.pdf)
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22 Utah DOT is an example of an agency that has developed decision trees in its pavement management system to guide the selection of preventive maintenance treatments. Figure 9 illustrates the factors that differentiate the type of seal coat recommended on asphalt roads maintained by Utah DOT (FHWA 2008b)
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23 into long-term effectiveness. It also found that evaluations focused only on cost or effectiveness yield biased results, so that methods that consider both factors (such as cost-effectiveness and economic efficiency)
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24 found that, internationally, agency cultures supported a long-term view for managing pavements in which agency priorities were known and agency personnel were held accountable for their actions (Zimmerman et al.
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25 selection of funded projects. In some instances, especially where an agency's districts or regions are fairly autonomous, there may be significant differences between the pavement management recommendations and the agency's improvement program.
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FIGURE 12 Estimated backlog and pavement condition index under three different funding scenarios (Romell and Tan 2010)
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27 FIGURE 14 A portion of the Performance Measurement Report Card developed by the North Dakota DOT (http://www.dot.nd.gov/ divisions/exec/docs/pm-rpt-cd.pdf)
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