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Use of PMS Data for Performance Monitoring with Superpave as an Example

3. Database Requirements

3.1. General

If good pavement design methods are to be used and improved it is essential to provide engineers and technicians the ability to monitor the performance characteristics of various paving materials and methods. Pavements fail in several ways. For example rutting and cracking are related to structural failure; friction is needed to assure safety; smoothness is a substantial concern to the highway user. These pavement characteristics must be measured in some manner. Protocols to define these methods have been developed by AASHTO and ASTM. It is important that these or similar standards be employed by skilled technicians. In turn, this will permit the needed exchange and meaningful reporting of performance information, now and in the foreseeable future, to build a historical database.

Pavement performance is integrally tied to the composition of the pavement layers specified, as well as the placement methods employed. If either is improper then the pavement may fail prematurely. Therefore, it is imperative that such data be integrated into the database for future use and analysis. Modern electronic technology provides the capability to link design information with mix details, and subsequently with specific construction and placement data. In turn, the annual monitoring and testing including traffic data, can be linked and used by maintenance forces, designers and others to evaluate the effectiveness under traffic of specific design concepts, construction methods and materials.

This continuum of data can provide top executives with the data required to manage their highway networks. The data can be reported at several levels within a DOT to focus on the operational needs of the DOT. Specific conditions, unique to the DOT or an environmental region, can be documented and successful treatments selected. In summary, the database should link design, materials, construction, loads (traffic) and performance data. These data should be managed and used to select and use the most cost-effective pavement materials and methods.

3.2. Classes of Data Required

One objective of pavement management is to coordinate all activities required for providing pavement structures in a cost-effective manner. These activities, for virtually all divisions of the highway agency, have impacts of varying degrees on a comprehensive pavement management system.

A comprehensive PMS uses data from a variety of sources. The classes of data needed include the following [Haas 91]:

  • Section Description
  • Performance Related Data
  • Historic Related Data
  • Policy Related Data
  • Geometry Related Data
  • Environment Related Data
  • Cost Related Data

All but the policy and cost related data classes provide background information required for the analysis and modeling of pavement performance. In large state transportation departments, each class of data may be the responsibility of a different section. Hence, there is a need for effective coordination and cooperation. In smaller agencies, a staff of one or two engineers and technicians may handle these functions. However, it is always necessary to organize, acquire, and record the data in a systematic and accessible manner.

3.3. The Importance of Construction and Maintenance History Data

In order to fulfill its purpose, a PMS must follow through from planning, programming and design to implementation, including construction, maintenance and rehabilitation [Hudson 94].

Pavement data collected over time can also provide the basis for developing, updating and assessing pavement performance models used in planning and programming and in design [TRDI 97]. Data on the construction and maintenance of the pavement are essential to such model development. Pavement construction data include information on the as-built quality of the materials, such as concrete strength tests and asphalt concrete densities. All pavement maintenance activities that can affect the performance of the pavement such as crack sealing, patching, and surface seals should be recorded.

3.4. The Importance and Consistency of Pavement Evaluation Data

Performance related pavement evaluation is critical to PMS. Four key measures are used to characterize or define the condition of the pavement:

  1. Roughness (as related to serviceability or ride comfort)
  2. Surface distress
  3. Deflection (as related to structural adequacy)
  4. Surface friction (as related to safety)

These four performance measures, along with maintenance and user costs can be viewed as the "outputs" of the pavement, that is, they are the variables that can be measured to determine whether or not the pavement is behaving satisfactorily. These outputs are originally predicted at the design stage and then periodically evaluated during the life of the pavement. The service life of the pavement is reached when the measures reach a minimum (or maximum, depending on the measure) acceptable level.

Consistent and repeatable condition data are an essential requirement of evaluation. Some pavement evaluation schemes rely on the judgment and opinion of a human rater. While this provides useful insight into condition, such evaluations may lack uniformity and generally lose meaning over time as the attitude and ability of the rater changes and/or new personnel are added to the process. In order to reduce human error, evaluations should preferably be performed with automated systems. New equipment, which can objectively measure pavement distress, is becoming more widely accepted. Improvements in this automated distress evaluation technology have great potential to stabilize data consistency. But also these systems require a regular calibration of the instruments used.

The pavement evaluation and measurement protocol previously developed under FHWA auspices, and currently being reviewed for adoption by AASHTO, would provide excellent tools for use in data collection for performance evaluation [TRDI 00].

In conclusion, engineering evaluation of pavements requires a well-documented set of practices and procedures, consistent techniques, calibrated equipment plus good training.

3.5. Data Integration and Centralization

A good database is the foundation from which all pavement management and decision support is derived. The accuracy and completeness of required data is paramount to the success of the PMS. Therefore, it is vital that the PMS database be linked with databases from other functions in a "Data Warehouse" in order to access and use key information from all pertinent components of the agency.

Data must be integrated and accessible for a successful analysis of such data. In most cases the PMS database is centrally available in electronic format, but other related data such as material properties, construction information and QA/QC data may be stored separately in other locations, and not available in electronic format. This can lead to serious delays when such data are required for an engineering analysis.

One objective of a well-designed database is to catalog and index all available data throughout the agency and allow easy access by the PMS. It should allow users to analyze that data in any appropriate way to produce information for decision support both at the pavement management technical level and for strategic planning and management at the executive level within an overall asset management approach. Thus, it is important to distinguish the difference between data integration and systems integration. They are different layers in both pavement management and an overall asset management framework. We will therefore focus our discussions on how raw data can and should be integrated at the base level to feed information and decision support at the technical level. The output from the technical level in turn feeds asset management at the strategic level.

The following issues related to this subject will be discussed next:

  • Integrated data;
  • Integrated systems;
  • Integration methods and tools;
  • Analysis of database;
  • Statistical analyses.
3.5.1. Integrated Data

Integrated data implies that raw data (with appropriate prescreening and cleansing) can be accessed and used by all authorized personnel throughout the agency who are responsible for any aspect of managing the pavement network. It is not necessary to create integration by putting all required data in one comprehensive database, because there are often problems in managing a very large database. A better approach is to have separate databases for various components, each managed by an owner who is responsible for its upkeep, placed on a centralized server and linked through referential keys for access by all potential users.

At the data integration level a precise definition of the data is of extreme importance. Take data on location as an example. The basis of a definition is some type of basic referencing and naming system to completely identify locations and interrelationships of each of the data relative to known points on the earth. For pavements a uniform method of linear referencing, relative to the centerline of the roadway, is needed for these features.

3.5.2. Linear Referencing System

The basis of a linear referencing system is location on the roadway. How that is defined by each agency varies widely throughout. NCHRP project 20-27(2) is focusing on the basic definition of linear referencing and provides a good foundation for agencies to build or improve on their existing referencing methodology [Opiela 97]. In general, the lowest level of referencing should be handled spatially in a two-dimensional x-y coordinate space. The technology for easily handling this type of special information is readily available through GIS (Geographical Information Systems) tools, which are readily available to be used with PMS and in the overall asset management function.

The basic location of each pavement feature is accurately positioned on an interactive map, which completely defines the roadway network and all features to be managed, relative to each other and their known locations on earth. The conversion to a specific linear referencing system suitable for referring to locations on a particular agency's roadway network becomes a matter of preference. NCHRP Research Results Digest Number 218 accurately describes several available and suitable methodologies for linear referencing, which can be accommodated and utilized by PMS and other roadway related assets [Opiela 97].

3.5.3. Integrated Systems

The primary concept associated with integrated systems is that shared information can maximize the availability of important information to decision makers. At the data integration level discussed above, the raw information is related and made suitably accessible throughout the agency for decision support analysis. At the systems integration level the user interface and reporting functions become the important components in sharing the results of the detailed analysis among various organizational units within an agency. As with the data at the data integration level, the flow of information is two-way. Pavement management receives reports and information packets from other management areas which affect their decisions and operations and the PMS provides results and information from its analysis to other management areas and to upper level administrators and decision makers responsible for dividing limited budgets among various asset categories owned by an agency.

System integration requires design and analysis of all aspects of system scope. Design of database interactions and relationships relative to the central linear referencing and features inventory as well as the other technical details within a component system and between other systems that manage other asset components is important. Good design based on a sound foundation of linear referencing is a key to success in providing for adequate exchange of data and information within the overall integrated systems concept.

3.5.4. Integration Methods and Tools

The tools for sharing integrated data across an organization must be carefully planned, designed, developed, and tested. The administrative procedures for accessing such data should be simple and straightforward but with adequate security to protect the valuable data. However, blocking access should not be considered security. "Read only" access should be provided to all. Security should involve data cleansing and changes. When the organization is spread over several locations a suitable network must be established. The linear referencing system discussed above acts to coordinate all information relative to location.

The integrated database should be made available on a server in a central location with strong technical support provided. For use over a wide area network, fast network lines are strongly recommended. Alternatively, architectures such as terminal emulation services, distributed databases covering only certain regions, replicated databases, or others can be used in a workable integration solution.

In most state agencies, database and system integration are controlled by or at least strongly influenced by a computer and information services division (ISD) or information technology (IT) department. These divisions typically provide the hardware infrastructure and the technical support structure required for such enterprise-wide systems to succeed. It is important for the owners of the PMS to establish a good working relationship with their ISD or IT function in order to evolve into an integrated system.

3.5.5. Analysis of Database and Data Mining

In some cases, the PMS database and the PMS-related databases may not be designed for engineering applications although they may have engineering data components. Sometimes an entire set of needed data items such as weather or traffic data may be missing. In such a situation, it is possible to use a surrogate variable, e.g. "geography" as a substitute for "weather". When that proves to be useful and if "weather" shows to be significant, then it is possible to gather and add weather data and strengthen the analysis in subsequent years.

At other times there may be gaps in the database that must be filled. Certain key sections must contain all of the data items needed to analyze the trends being observed clearly. It may then be necessary to go back to the construction records, back to the traffic section, or wherever necessary to fill missing data elements in the database for subsequent analysis.

Data mining is the process of cross-referencing, querying, and interrelating an agency-wide database analytically in order to extract valuable information. Modern computer tools for querying and reporting from large databases are available to facilitate this process. However, such analyses also require a great deal of human thought and effort in experiment design, statistical analysis, review comparison, and revaluation of results.

The pavement management database and the related construction and materials databases generally contain a gold mine of information. That information is not perfect and may not be complete but it can and should be used.

3.5.6. Statistical Analyses

Performance data in PMS databases normally show a lot of scatter. Consequently, when carrying out an engineering analysis using such data, the results need proper scrutiny to assess whether they are statistically significant. Statistical analyses can help to quantify the significance of a conclusion or a trend. The reader is referred to professional textbooks, such as Statistics in Research [Ostle 74], Design of Experiments for Industrial Engineers [Anderson 82], and Practical Business Statistics [Siegel 90].

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Updated: 06/01/2015
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