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Home / Policy Information / Highway Performance Monitoring System (HPMS) / Chapter 5

Office of Highway Policy Information
March 2014

Field Manual

5.1 Overview

The purpose of this chapter is to provide additional guidance on the reporting of Functional System, Traffic, and Pavement data. This information is a supplement to the data item requirements discussed in Chapter 4.

5.2 Functional Classification System Descriptions and Groupings

FHWA focuses scarce national resources on the most important roads and highways in the Nation for condition and performance improvement purposes. This practice has been in existence on a national level since the 1960s. In order to ensure that the State Departments of Transportation (DOTs) have information needed to support this effort, FHWA disseminates Functional Classification guidance documentation on a periodic basis. The most recent comprehensive Functional Classification Guidance Document was published in 2013 and can be accessed online at: https://www.fhwa.dot.gov/policyinformation/hpms/hfcccp.cfm. This document should be used by the State DOTs as guidance for the purpose of updating and maintaining their respective FC Systems.

Functional classification is the process by which streets and highways are grouped into classes, or systems according to several factors that contribute to the overall importance of a given roadway to a region or area. All streets and highways are grouped into one of seven classes, depending on the character of the roadway and the degree of land access that they allow. The seven functional classes are represented by a one-digit code and are used to represent a specific classification of road regardless of whether it is located in an urban or rural area. These classifications are as follows:

Code Description
1 Interstate
2 Principal Arterial - Other Freeways and Expressways
3 Principal Arterial - Other
4 Minor Arterial
5 Major Collector
6 Minor Collector
7 Local

The U.S. Census-based Urban Area (UA) Boundaries are an important part of the FC system. Traditionally, the Census Bureau releases new Urban Area Boundaries two years after the initial Decennial Census as a byproduct of that effort. Since these boundaries are developed primarily through automated methods, they are often coarse and irregular, generally not reflective of transportation facilitates. While a State may choose to use the unadjusted original Census boundaries as part of the overall FC program, it is advisable to adjust these polygons to efficiently account for the highway system.

The aforementioned FC codes and the Census-defined UA Boundary codes must be reported for all Federal-aid roadways to accurately reflect their location with respect to UAs. See Chapter 4, Sec. 4.4 for specifications and requirements pertaining to the reporting of the ‘Functional System’ and ‘Urban Code’ data items. Spatial Analysis should be used by the States to relate the FC code to the UA code for HPMS reporting purposes.

5.3 Traffic Monitoring Procedures


Traffic monitoring data are a key component of the HPMS. They are some of the most analyzed and used data elements and must be of high quality to accurately represent conditions in all States. Traffic data are used for a variety of work program objectives which include the following:

Traffic monitoring data are also key inputs for the development and maintenance of the HPMS data set. Traffic data drive the HPMS sample stratification and selection process by assigning roadway sections into volume groups and for statistical analysis to develop the sample panel as further discussed in Chapter 6. The validity of the entire HPMS sample panel and the development of the sample expansion procedure depends on the proper maintenance of a comprehensive traffic monitoring program.

A State traffic monitoring program that is developed following the guidance contained in the Traffic Monitoring Guide (TMG) will provide data that meets the needs of HPMS. The AASHTO Guidelines for Traffic Data Programs (AASHTO Guide) provides another reference for developing and maintaining a State Traffic Data Program. Since HPMS is a key driver for State's traffic monitoring programs, States should use a combination of guidance from the TMG, HPMS Field Manual, and other sources such as the AASHTO Guide to develop their traffic program.

The traffic data reported in HPMS must be the same data the State uses for their own purposes as contained in their traffic monitoring system. Using the same data provides assurance that it was collected and processed following the State's traffic monitoring program and not processed independently for HPMS. If the same data are used, then products from the HPMS data submittal are approximately the same as the State's traffic data products such as VMT. In summary, the specific travel data needs for HPMS can be accommodated with minor adjustments and implementation of good practices as presented in the TMG and in the AASHTO Traffic Data Guidelines.

This section provides specific guidance for traffic monitoring procedures to meet the HPMS requirements and builds on the recommendations provided in the TMG. It is important to recognize that this Field Manual refers to traffic data in several sections: Sections 3.3, 4.3, etc. Stakeholders involved in collecting, analyzing and reporting on traffic data for HPMS should refer to this section as well as the other references to traffic monitoring throughout the Field Manual.

This section is presented in three parts:

(1) General, high level requirements for the traffic monitoring program,

(2) Volume Group Assignments for HPMS, and

(3) More detailed traffic monitoring program guidelines.

State Traffic Monitoring Data Program

General Requirements

State maintenance of a comprehensive traffic monitoring data program to provide quality, timely, and complete traffic volume and vehicle classification data is important for meeting HPMS requirements. This section describes the fundamental macro-level requirements of a State Traffic Data Program for HPMS. Specific guidance is contained in the TMG and readers are encouraged to refer to the TMG for more detail.

While traffic data are collected at points on the highway system, HPMS is oriented toward highway sections. So an initial step is for the State to segment their highways into sections with consistent traffic. As highways evolve and traffic patterns change, these traffic monitoring sections may need to be revised. An advantage of the new HPMS data model is that States may submit section-level data for these traffic monitoring sections without having to match any sections in HPMS.

Count Cycles and Coverage

A State should have minimum count cycles and coverage as follows:

Minimum 3-year count cycle - The State's traffic monitoring program shall cover all NHS, Interstate, Principal Arterial, and HPMS sample sections on a three-year cycle or better; at least one-third should be counted each year. The remaining two-thirds counts must be estimated based on a documented process in accordance with the TMG and the Field Manual. The State shall cover all roads on these systems, not just State-owned roads, so data provided by MPOs, cities, or counties should be included in the count cycle.

Minimum 6-year count cycle - The State shall also have a traffic count program on a six-year cycle or better for all sections that are neither samples nor NHS but are on the minor arterials and collectors (except for rural minor collectors). Traffic data for ramps, as defined in Chapter 4, are also to be collected on a six-year cycle or better.

All traffic data for HPMS shall be based on a minimum of 48 hours of monitoring for volume and vehicle classification, which is referred to as short term monitoring. If a State has a duration of monitoring that is less than 48 hours, they must be able to demonstrate no loss in quality of data based on documented statistical analysis provided to FHWA.

The program should provide for a sufficient number of automatic traffic recorder (ATR) volume and automatic vehicle classification (AVC) stations to permit factoring of short term counts for estimates of annual average daily traffic (AADT). If there are insufficient ATRs for statistical accuracy in a factor group, use of statewide factors is encouraged. Day of week, seasonal, axle correction, weekday and weekend, and annual (growth) adjustment factors are the only factors to be used as necessary to keep all AADTs current to the year for which they are being reported.

The HPMS traffic data needs should be conveyed to the traffic monitoring office within the State in a timely manner that allow enough time to develop and schedule the State's comprehensive traffic monitoring program. Areas of the State selected for counting in a program year should be selected on a random basis. Highways with high variability should be counted more often than those with low variability, and highways with high traffic volume should be counted more extensively than those with low volume. To make the most of available resources, an area traffic count plan may consider using cluster count techniques whereby several counts are taken in the same general area. Counts scheduled and obtained under other programs may be incorporated into the count plan to avoid duplication of monitoring sites.

Sources of Data

Automatic traffic recorders provide continuous monitoring of existing traffic conditions around the State. Travel on freeways, expressways and other multilane facilities can be monitored by route. Travel can also be monitored by area through statewide, or MPO freeway management or travel surveillance programs, which are often referred to as Intelligent Transportation System (ITS) deployments. Other highway functional systems, both State and off-State, can be monitored by geographic area, such as by county or highway district. Traffic information in a comprehensive count program should be compiled from all available sources -- State, MPO, ITS, city, and county.

Coordination and cooperation with local governments to implement a comprehensive count program is highly desirable; however, the State ultimately maintains responsibility for ensuring that these data meet minimum collection and quality requirements. To meet these responsibilities, the State should have a comprehensive quality assurance program that includes data collection, the conversion of traffic counts into current year AADT values, routine equipment testing provisions, and routine traffic count calibration procedures.

The following list of standards from ASTM International provides detailed guidance on traffic monitoring techniques and technologies:

E17.52 Traffic Monitoring Committee

AADT Calculation

The development of section AADT estimates from traffic monitoring data using continuous or short term volume, vehicle classification, or truck weight data must include the use of adjustment factors if the data does not cover all months. The AADT estimates reported to the HPMS for all sections not counted during the current year must be updated to current year AADT estimates by use of annual (growth) adjustment factors.

The rounding of AADTs is acceptable for HPMS following the scheme recommended by the AASHTO Guide but is not encouraged unless it is common practice for the State to round all traffic data in their traffic monitoring database and the practice is applied to all traffic data consistently. This applies to the reporting of volume and vehicle classification data. Rounding should be performed after all adjustments to the raw count have been made and should not be performed when calculating percent single unit and combination trucks. Low volume counts must not be rounded to report zero as a volume or as a percent since this will not accurately represent the presence of minimal volumes and will also show no change in trends. Zeros should only be reported when the actual count is zero.

Volume Group Assignments

The State’s comprehensive traffic count program should be used to develop traffic volume group assignments for all road sections in a program that adequately monitors both high and low volume roads, including those off the State system. To facilitate this process, count station locations should be selected to represent expected AADT volume group breakpoints for the volume ranges of all required samples. This may require locating count stations at one per several miles in rural areas and more closely in urban areas. If there are homogeneous traffic sections as determined by prior counts or engineering judgment, more than one section may be represented by a single traffic count station as long as traffic does not vary more than 10%. Selection of count locations should be based on previous count experience on the section or adjacent sections, recent land use developments, and the existence of uncounted sections along the route.

Traffic Monitoring Program Elements

A detailed discussion of recommended procedures for developing, collecting, and processing travel monitoring data is contained in the Traffic Monitoring Guide (TMG). However, a general discussion of some elements of a typical traffic monitoring program and their applicability to the HPMS follows.

Count Cycle

A minimum of one-third of all NHS, Interstate, Other Freeways and Expressways, Other Principal Arterials, and HPMS sample sections shall be counted each year; all other monitoring should be on a minimum six-year cycle. The sections to be counted should be randomly selected from each sample stratum (volume group), with minor adjustments as necessary for strata with numbers of sections not divisible by three or having less than three samples. A single count may be used for several sections between adjacent interchanges on controlled access facilities.

Continuous Counts

Automatic Traffic Recorders (ATRs) are used to provide continuous traffic count coverage for every day of the year at a limited number of locations using automated procedures. ATR data are also used to develop seasonal, day-of-week, axle correction, weekday and weekend, and annual (growth) adjustment factors which are then used to factor short term counts to an AADT. Analytical procedures to determine the appropriate level of effort and to develop the needed traffic estimates are described in the TMG.

Continuous count data are essential for converting short term counts to AADT. The State’s documentation of its continuous count program should identify the number of continuous counters on the rural and urban portions of the PAS/NHS system and the rest of the highway network. The process used to develop adjustment factors and their application should be thoroughly documented as well. Whenever possible, the State should have at least one continuous counter on each major PAS/NHS highway route. At a minimum, each continuous counter should have at least one full day of data for each day of the week for each month provided the State has an adequate automatic edit process based on the historic trend.

Short Term Counts

Short term counts cover lesser time periods than continuous ATRs, 48-hour counts (two full 24-hour days) are required for all HPMS Full Extent and sample data including those off the State highway system. Where axle correction factors are needed to adjust raw counts, they should be derived from facility-specific vehicle classification data obtained on the same route or on a similar route with similar traffic in the same area. Factors that purport to account for suspected machine error in high traffic volume situations shall not be applied to traffic counts used for HPMS purposes, including volume group assignment. In high volume situations and on controlled access facilities, it may be more appropriate to use continuous or short term ramp counts in conjunction with strategic mainline monitoring than to use short term counts on all mainline locations (see “ramp balancing” in the TMG for details).

Ramp Counts

Traffic counts are required on all Federal-aid highways including ramps associated with grade-separated interchanges. Ramp counts are important because many bottlenecks occur at major interchanges around the country and large amounts of Federal funds are expended to address these congestion issues. A minimum of one count every six years is required for ramps.

The same procedures used to develop AADTs on all HPMS sections should be used to develop ramp AADTs. It is important that this volume data be an AADT for comparison to other AADTs and for reasonable trend analysis. States are encouraged to use adjustment factors developed based on either entrance or exit travel patterns or on the functional class of the ramp and to use this procedure consistently statewide. For example, the factors used for the mainline road with subordinate flow may be appropriate for use on the ramp. In other cases, the factors from intersecting roads connected to the ramp may be more appropriate for use. Good judgment and experience should be applied regarding factor use. As a minimum, 48-hour ramp counts should be adjusted with axle correction factors as needed.

Ramp counts should be available from freeway monitoring programs that continuously monitor travel on ramps and mainline facilities. Ramp balancing programs implemented by States on ramp locations and on high volume roadways could also be used to provide AADTs. In the case where no ramp counts are available, a State may use traffic matrix estimation. The State’s traffic modeling office may compute ramp traffic estimates as part of their modeling process.

Vehicle Classification

Data reported in the HPMS should reflect the use of automatic vehicle classification equipment to accurately report truck data, vehicle classification summaries, and develop seasonal and day of week vehicle class adjustment factors. Summary vehicle classification data reporting requirements are outlined in Chapter 3. Percent trucks data in Items 23 and 25 and truck AADTs in Items 22 and 24 are reported for each HPMS sample section as discussed in Chapter 4. Vehicle classification information is also reported in the summary travel data as discussed in Chapter 2.

The State’s vehicle classification program shall include:

Data representative of all functional systems, both on and off the State system.

Monitoring sessions for at least 48 hours to account for the changes in vehicle mix from day to day. Data for less than 24 continuous hours is not acceptable. At locations where vehicle class is not consistent throughout the week, such as on weekends, counts longer than 48 hours may be necessary to determine appropriate days to counts and to accurately represent average vehicle class data.

Monitoring frequency shall be at a minimum, over a three-year cycle with one-third of the counts per year for the NHS, all PAS, and HPMS sample sections. All other locations should be monitored on no longer than a six-year cycle.

Data reported in HPMS shall represent data for the reporting year. Prior year classification counts shall be adjusted with annual adjustment factors to represent current year data and to accurately develop percent trucks and truck travel trends.

Monitoring activities should include all lanes in both directions.

The Axle Class Algorithm used should be consistent among different equipment and vendors, and should be checked annually to ensure that it is working properly for all vehicle types.

Axle correction factors are to be developed based on data that represents all seasons of the year. They should be applied to all counts that are based on axle sensors. The factor groups could be the same as for other adjustment factors or can be for each functional class and are to be updated each year based on that year’s vehicle classification data.

Vehicle classification programs shall be set up following the guidance in the TMG for monitoring homogenous section with one monitoring location. The limits of a homogenous traffic section for one vehicle class may differ from the limits of a different vehicle class.

Vehicle classification data used to report truck AADTs for HPMS shall be adjusted to represent average conditions for the entire year following the recommendations in the TMG. Adjustments to vehicle classification data should be based on factors developed using data from a permanent continuous vehicle classification monitoring program established following the guidance in the TMG. As States fully develop and implement vehicle classification programs to provide sufficient and accurate data to develop adjustment factors this should be an integral component of a comprehensive traffic monitoring program. States that do not have a complete program are still required to adjust raw count data using interim procedures they have developed. These interim procedures could focus on using data from traffic volume programs to develop adjustment factors if considered reasonable to represent truck travel patterns until more specific vehicle classification data becomes available.

The goal of developing a comprehensive vehicle classification program to provide truck AADTs based on truck characteristics is of utmost importance since various studies have concluded that truck travel oftentimes varies considerably from total traffic patterns and has different trends statewide and by functional class. All other vehicle types are also important and should receive the attention they deserve. Motorcycles in particular are a small percent of travel but have significant safety issues that require attention for estimating their travel exposure.

Vehicle Miles of Travel (VMT)

Estimates of Daily Vehicle Miles of Travel (DVMT) are developed by direct computation for all Federal-aid Highway functional systems. This is generated by the HPMS software which multiplies the section AADT by the section length and sums the result to the HPMS aggregation level desired (functional system, total rural, etc.). A comprehensive traffic monitoring program, good traffic volume procedures and practices, a well-distributed HPMS sample, and appropriate AADT estimation techniques will result in highly reliable DVMT estimates.

Specific HPMS requirements for reporting VMT are found in Section 3.3 of this manual. Examples of good state practices for estimating VMT on non-Federal-aid highways are:

One method which is not recommended is to use the residual of the statewide total VMT minus the highway system VMT because this obscures all other traffic data collected. Another discouraged method is the use of fixed percent of traffic growth (e.g. zero or one percent).

The monthly Traffic Volume Trends report is published by the FHWA based on a sample of traffic data from ATRs in the States. Annual VMT growth rates by functional system derived from these reports are used to validate HPMS traffic data. The goal is that all traffic information published by the FHWA and the States is valid and consistent.

5.4 Pavement Data Guidance


In order to provide a measure of pavement surface condition that has nationwide consistency and comparability and is as realistic and practical as possible, a uniform, calibrated roughness measurement for paved roadways is required by the HPMS.

R-43 defines roughness as follows: roughness—according to ASTM E 867, “the deviation of a surface from a true planar surface with characteristic dimensions that affect vehicle dynamics and ride quality.” After a detailed study of various methodologies and road profiling statistics, the International Roughness Index (IRI) was chosen as the HPMS standard reference roughness index. The summary numeric (HPMS data reporting unit) is the IRI in inches/mile. The primary advantages of the IRI are:

  1. It is a time-stable, reproducible, mathematical processing of the known profile;
  2. It is broadly representative of the effects of roughness on vehicle response and user’s perception over the range of wavelengths of interest, and is thus relevant to the definition of roughness;
  3. It is a zero-origin scale consistent with the roughness definition;
  4. It is compatible with profile measuring equipment available in the U.S. market;
  5. It is independent of section length and amenable to simple averaging; and
  6. It is consistent with established international standards and able to be related to other roughness measures.

HPMS Roughness Measurement Procedure

The reference method for obtaining IRI data for the HPMS can be found in the AASHTO Standard Practice for Determination of International Roughness Index for Quantifying Roughness of Pavements, AASHTO R 43-07. This Standard Practice calls for the use of a longitudinal profile measured in accordance with ASTM E 950 as a basis for estimating IRI. Roughness is reported for HPMS in IRI units of in/mi.

Roughness data should be reported in IRI units for all sections in accordance with Data Item 47 International Roughness Index (IRI) and IRI Date. IRI should be measured on an annual cycle for the NHS and on a 2-year maximum cycle for all other required sections. Existing IRI values should continue to be reported until they are replaced by new measured values. The lower functional systems (minor arterial in urban areas and collector in any area) have been placed in the “optional” category since there are situations where it may not be possible to obtain meaningful roughness measurements with profiling equipment. Major obstacles may include:

Speed restrictions Traffic congestion
Short section lengths Pavement treatments
Numerous traffic signals Intersection treatments

However, some of these obstacles can be overcome by collecting roughness data during non-peak hours or at night, where speed, traffic, and safety are less of a problem. There are situations where it also may not be possible to obtain meaningful roughness measurements on some Urban Other Principal Arterial sections.

For purposes of national-level data consistency, IRI sections reported in HPMS should not exceed 0.10 mile in length. It is understood and acceptable that sections less than 0.10 mile be reported in HPMS which can result from short collection sections, route termini, and intersections, etc.

All equipment must be operated within manufacturer’s specifications and quality assurance guidelines outlined in AASHTO R 43-07 must be followed. Each State should document and retain records of its quality assurance procedures. FHWA field offices should monitor adherence to these procedures as part of roughness data process reviews.

Additional Recommendations for Collection of Roughness Data

The following field survey guidelines are recommended for State use in addition to the AASHTO Standard Practice:

Where roughness data are collected in both directions, the State should use the “inventory direction” selected in accordance with the discussion in this chapter for reporting IRI data and should use this same direction for all future HPMS reporting.

For multilane facilities, roughness data for the outside (right) lane should be reported. However, if this is not practical, whichever lane is measured should be used for all future HPMS reporting.

Roughness data collection should be performed when the pavement is in stable condition. Data should not be collected during winter (frost/freeze or freeze/thaw) or wet base conditions. Data collection should be performed during good weather conditions when wind conditions will not affect equipment stability and on dry pavement. All equipment manufacturers’ recommended procedures should be observed. Good general practice rules include:

Temperature: Between 40 and 100 F;

Wind: Data collection should not be performed when wind conditions affect the stability of the equipment/vehicle; and

Surface: Data collection should preferably be performed when the roadway surface is dry.

Data should only be collected at the speeds that correspond to the manufacturer’s recommended speed range. Constant speeds should be maintained for all measurements within specified ranges.

The impacts of bridge approaches and railroad crossings (or other localized discontinuities) are to be included in the roughness measurement for the roadway.

Roughness measurements should be taken over the entire length of a roadway section. However, in order to achieve equipment and speed stability, a minimum run-in length, consistent with the manufacturer’s specification, may be required prior to the beginning of the measurement area. If this minimum cannot be met prior to the start of the Sample Panel section, a shorter portion of the HPMS section may be measured, but that same portion should always be measured in future roughness data collection activities. Short HPMS sections also may be included in slightly longer roughness test sections for measurement and reporting purposes. However, the same longer sections should always be measured in future data collections.


Rutting is defined as a longitudinal depression in the wheelpath(s) of a paved surface measured between the width limits of the lane. (Note that there may also be associated transverse displacements). For HPMS reporting purposes, it is recommended that AASHTO Standard Practice R 48-10 along with the LTPP Distress Identification Manual be followed as a guide to reporting rutting in flexible (AC) pavement types. These include composite pavements where AC pavement types are the surface layer. Also for HPMS reporting, the average rut depth to the nearest tenth of an inch (0.1”) should be reported for the section.


Faulting is defined for HPMS purposes as the absolute value of the difference in elevation across a joint in a jointed concrete (PCC) paved surface. It is recommended that AASHTO Standard Practice R 36-04 along with the LTPP Distress Identification Manual be followed as a guide to reporting faulting in jointed, rigid (PCC) pavement types. These include un-bonded jointed concrete overlays on PCC pavement and bonded PCC overlay of jointed PCC. For HPMS purposes, report the average joint faulting value for the section to the nearest tenth on an inch (0.1”). Faulting that occurs in other areas of the paved section away from the joint should be ignored for HPMS.

Cracking Length

Cracking Length is defined for HPMS purposes as the total length in ft/mi on a paved asphalt concrete (AC) section for transverse or reflective type cracks. It is recommended that AASHTO Provisional Protocol PP 67-10 and the LTPP Distress Identification Manual be followed as a guide to reporting these types of cracks. Transverse and reflective cracks are generally perpendicular to the pavement centerline and all severity levels should be considered for reporting in HPMS. Both automated and manual surveys for the collection and reporting of these data in HPMS are acceptable. Reflective cracks can be present in composite, asphalt surfaced pavements when it overlays a jointed rigid (PCC) pavement and is manifested on the surface similar to transverse cracks but appear over the underlying joints. Both types of cracks should be reported in HPMS for AC surfaced paved sections, whether composite or not.

Cracking Percent

Cracking Percent is defined for HPMS purposes as the percent area to the nearest 5 percent (at a minimum) for fatigue type cracking in AC and percent cracked slabs to the nearest 5 percent (at a minimum) for jointed PCC and CRCP surfaced paved sections. All severity levels should be considered for HPMS reporting. Both automated and manual surveys for the collection and reporting of these data in HPMS are acceptable. Fatigue type cracks generally occur in areas of the paved surface subjected to repeated traffic loadings. It is recommended that AASHTO Provisional Protocol PP 67-10 and the LTPP Distress Identification Manual be followed as a guide to reporting these types of cracks.

Pavement Data Collection Coordination with Other Activities

One of the goals of HPMS is to avoid duplicate data collection efforts. States are encouraged to coordinate roughness measurement activities, where possible, such that the same equipment, verification sites, and measurements are used for multiple purposes. Therefore, HPMS activities should be coordinated with other State activities such as the Strategic Highway Research Program (SHRP)/Long Term Pavement Performance (LTPP) and the State Pavement Management Systems (PMS).

The LTPP activities monitor pavement performance and use in detail for approximately 1,500 pavement sections nationwide as part of SHRP. The pavement and traffic monitoring data collected on LTPP sections should be used for the HPMS Full Extent or Sample Panel sections where possible. In addition, efforts should be made to utilize the LTPP established sections/profiles as multiple-use verification sections in each State.

Many State and some local transportation agencies have operational or are developing a PMS to guide program development, improve life-cycle costs, and help select the most effective pavement improvement strategies. The HPMS pavement data reporting should make full use of existing PMS data and collection activities. Data collected by others (cities, counties, MPO’s, etc.) should be subjected to the same AASHTO quality assurance guidelines before incorporation into the HPMS.


Additional guidance and information on the collection of various pavement data items can be found in the following standards, specifications, and documented procedures:


AASHTO Standard R 43-07 (Quantifying Roughness of Pavements)

ASTM Standard E 950 (Standard Test Method for Measuring the Longitudinal Profile of Traveled Surfaces with an Accelerometer Established Inertial Profiling Reference)

NCHRP 20-24(37B) Comparative Performance Measurement: Pavement Smoothness

Sayers, M.W., On the Calculation of International Roughness Index from Longitudinal Road Profile, Transportation Research Record 1501, Transportation Research Board, Washington, DC, 1995.

ASTM Standard E1926 Standard Practice for Computing International Roughness Index of Roads from Longitudinal Profile Measurements

AASHTO MP 11-08 (2008) (Inertial Profiler)


AASHTO R 48-10 (Determining Rut Depth in Pavements) specifications and the LTPP Distress Identification Manual

AASHTO PP 69-10 (Determining Pavement Deformation Parameters and Cross-Slope from Collected Transverse Profiles)

AASHTO PP 70-10 (Collecting the Transverse Pavement Profile)


AASHTO R 36-04 (Evaluating Faulting of Concrete Pavements) specifications and the LTPP Distress Identification Manual

Cracking Percent

AASHTO R 55-10 (Quantifying Cracks in Asphalt Pavement Surface) specifications and the LTPP Distress Identification Manual

AASHTO PP 67-10 (Quantifying Cracks in Asphalt Pavement Surfaces from Collected Images Utilizing Automated Methods)

AASHTO PP 68-10 (Collecting Images of Pavement Surfaces for Distress Detection)

Cracking Length

AASHTO R 55-10 (Quantifying Cracks in Asphalt Pavement Surface) specifications and the LTPP Distress Identification Manual

AASHTO PP 67-10 (Quantifying Cracks in Asphalt Pavement Surfaces from Collected Images Utilizing Automated Methods)

AASHTO PP 68-10 (Collecting Images of Pavement Surfaces for Distress Detection)


AASHTO M 328-08 Standard Equipment Specification for Inertial Profiler (for construction quality control)

AASHTO R 57-07 Operating Inertial Profilers and Evaluating Pavement Profiles (for construction quality control)

AASHTO MP 11-08 (2008) (Inertial Profiler)

The above references can be accessed at the following web site locations:




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