U.S. Department of Transportation
Federal Highway Administration
1200 New Jersey Avenue, SE
Washington, DC 20590
202-366-4000
The Federal Highway Administration (FHWA) is responsible for assuring that adequate highway transportation data and systems performance information is available to support its functions and responsibilities, as well as those of the Administration and United States Congress. The Highway Performance Monitoring System (HPMS) is used for reporting these metrics. Additionally, HPMS data are widely used throughout the transportation community, including other governmental entities, business and industry, institutions of higher learning for transportation research purposes, and the general public. HPMS data may also be used for performance measurement purposes in national, State, and local transportation decision-making to analyze trade-offs among the different modes of transportation as part of the metropolitan and statewide transportation planning process.
The HPMS Field Manual (FHWA) provides a comprehensive overview of the HPMS program and describes in detail the data collection and reporting requirements for HPMS. The HPMS Field Manual includes detailed information on technical procedures, a glossary of terms, and various tables to be used as reference by those collecting and reporting HPMS data. Information related to the use of the HPMS software web application is contained in a separate document.
Users of this Guide are encouraged to refer to the latest revision of the HPMS Field Manual, as traffic data requirements may have changed.
This chapter provides guidance to States in meeting the traffic reporting requirements of the HPMS program since traffic data comprise a significant portion of the HPMS data submission. Although most traffic monitoring programs include the collection of volume, classification, weight, and speed data, the primary focus of the guidance in the Highway Field Manual is on volume and classification data. The traffic data reported in HPMS should match the data managed by the State's traffic monitoring program so that information published by the State and FHWA are as similar as possible. This goal is best achieved when HPMS traffic data are developed in a cooperative process among the State's HPMS, traffic monitoring, and traffic demand modeling personnel.
A limited amount of background information is provided here to offer an overview of how the HPMS is organized. The main difference between traffic monitoring data collection and HPMS data submission is that HPMS-based traffic data elements, including VMT, are reported by road sections to correlate with road inventory data. HPMS data are reported by full extent, sample panel, or partial extent.
The following definitions for each of these types of data are from the HPMS Field Manual (FHWA).
Full extent data refers to a limited set of data items that are reported for an entire road system such as the National Highway System (NHS) or all public roads. AADT is an example of traffic data that should be reported on a full extent basis and reported for ramps at grade-separated interchanges.
Sample panel data consist of data items added to the full extent data that are reported for a select portion of the total roadway system length. K-FACTOR and D-FACTOR are examples of traffic data that should be reported on a sample panel basis.
Partial extent data refer to those data items that are reported on a full extent basis for some functional systems and on a sample panel basis for other functional systems. AADT_SINGLE_UNIT (truck volumes) and AADT_COMBINATION (truck volumes) are examples of traffic data that should be reported on a partial extent basis.
The purpose of sampling is to provide a statistically valid representation of the public road network for the State, without imposing additional data collection burdens. Within HPMS, these samples are expanded for a statistically valid representation of the public road network for the State.
The State's HPMS program provides the location of sample sections to the traffic monitoring program as new sections are added or removed for each HPMS data collection year. The addition of these sections, which may require additional traffic data collection effort, is determined by using the sample management process within the HPMS system. This iterative process allows the traffic monitoring program to either establish permanent count stations at those locations or take short-term coverage counts at specific locations to provide count data for use with HPMS.
For sampling purposes, HPMS uses the Table of Potential Samples (TOPS) as the sampling frame. HPMS sample sections are selected from the TOPS. The TOPS includes all Federal-aid highways, which are highways on the NHS and all other public roads not classified as local roads or rural minor collectors.
Five critical data items are used to establish the TOPS. One of these data items is AADT. The four additional items are functional system, through lanes, urban code, and facility type (used to identify ramps). TOPS sections are defined where the values for these five items remain unchanged (or are homogenous) for a section of road along the full extent of the road. Figure 5-1 illustrates the TOPS sections for a given route (Route ABC) based on the five homogenous data items. The potential TOPS sections are labeled as A, B, C, D, and E on the bottom row of the figure.
AADT |
62000 |
90000 |
70000 |
||
|---|---|---|---|---|---|
FUNCTIONAL SYSTEM |
2 |
1 |
2 |
||
THROUGH LANES |
6 |
8 |
6 |
||
URBAN CODE |
9645 |
||||
FACILITY TYPE |
2 |
||||
ROUTE ABC TOPS |
A |
B |
C |
D |
E |
DISTANCE |
0 MILE 8 MILE |
10 MILE 20 MILE |
22 MILE |
26 MILE |
Source: HPMS Field Manual.
Figure 5-1. HPMS TOPS Development Process
Out of the five data elements listed above, States are typically organized such that the AADT comes from the traffic data program, and the other four data elements come from the road inventory data program. Working across these two programs to produce the HPMS statistics can be challenging. The following is an example of this challenge.
HPMS requires combining tabular traffic data attributes with geospatial linear referencing system attributes.
For example, the combination of point roadway traffic count data with the location (GIS point and linear features) provides information about where exactly along a traffic segment the original point traffic data are applicable.
However, State DOTs are sometimes technically and administratively challenged with integrating GIS line and point features.
The AADT statistic is created by the travel monitoring program staff. In some States, the AADT attribute is stored in the roadway inventory, and in other states, the AADT attribute is stored with the travel monitoring data. States should establish business rules to synchronize roadway inventory and traffic data to support management of these data layers.
The HPMS Field Manual (FHWA) contains additional information on TOPS. The remainder of this chapter includes the following sections:
5.2 HPMS Requirements – This section describes traffic data reporting requirements for HPMS.
5.3 Guidelines for Collecting Traffic Data to Support HPMS – This section provides guidance about how to acquire the traffic data needed to meet the HPMS requirements.
5.4 Calculation of Data Items – This section provides guidance about how to compute the HPMS data items and includes references.
While traffic data are collected and reported on a full extent, sample, and partial extent basis for HPMS, State DOTs may not need to physically conduct traffic counts at all locations. In some cases, States may rely on local governments to collect and supply the traffic data for use with HPMS. In other cases, procedures such as ramp balancing can be used to estimate traffic volumes on roads where portable counts cannot be performed safely.
In all cases, State DOTs are responsible for the quality, completeness, and accuracy of all HPMS-related traffic data within their State boundaries.
Specific emphasis is placed on the collection of vehicle classification data on HPMS sample sections, since these data are used in many nationally significant analyses. While not reported at the section level within the HPMS submittal, vehicle classification data on motorcycle, bus, and light truck percentages are also required by State highway agencies in order to compute the HPMS vehicle summary table.
When this table is computed, State highway agencies should account for the different monthly travel patterns of each class of vehicles when the percentage of travel is being annualized. To accurately compute the fraction of statewide VMT by class, it is also necessary to account for the functional classification and location of these counts when they will be used to estimate total VMT by vehicle class and functional classification of roadway. FHWA has provided online training on preparing HPMS Vehicle Summary Data, available through its knowledge center found at https://www.fhwa.dot.gov/policyinformation/knowledgecenter/vmt_training/.
These volume data are also used to support the assessment of the Nation's transportation system and help to ensure a fair distribution of Federal funds to maintain that system.
The HPMS Data Model is a logical abstraction of the data elements contained within the HPMS and includes thirteen traffic data items, seven of which are provided by the States' traffic monitoring program. The additional six items may be provided by other areas of the agency, including operations and/or other sections of the states' planning division. The traffic elements listed in Table 5-1 are defined in the HPMS data catalog.
Item Number |
Data Item |
Data Format |
Example Value |
|---|---|---|---|
21 |
AADT |
Numeric |
100,000 |
22 |
AADT_SINGLE_UNIT |
Numeric |
10,000 |
23 |
PCT_DH_SINGLE_UNIT |
Decimal to nearest 0.01% (one-hundredth) |
2.12 |
24 |
AADT_COMBINATION |
Numeric |
30,000 |
25 |
PCT_DH_COMBINATION |
Decimal to nearest 0.01% (one-hundredth) |
0.33 |
26 |
K_FACTOR |
Numeric (2-digit) |
1-99 (represents 1%-99%) |
27 |
DIR_FACTOR |
Numeric (2-digit) |
1-99 (represents 1%-99%) |
28 |
FUTURE_AADT |
|
|
29 |
SIGNAL_TYPE |
|
|
30 |
PCT_GREEN_TIME |
|
|
31 |
NUMBER_SIGNALS |
|
|
32 |
STOP_SIGNS |
|
|
33 |
AT_GRADE_OTHER |
|
|
AADT — is the Annual Average Daily Traffic and represents all days of the reporting year for traffic on a section of road and is required for all Federal-aid highways and grade-separated interchange ramps.
AADT_SINGLE_UNIT — is the Annual Average Daily Traffic for single-unit trucks and buses and is required for all NHS and Sample Panel sections (HFM 4.4). This item requires detailed vehicle classification data and includes FHWA vehicle classes 4-7.
PCT_DH_SINGLE_UNIT — Percent Design Hour Single-Unit Trucks and Buses is the Design Hour single-unit truck and bus volume as a percentage of the applicable roadway section's Design Hour volume rounded to the nearest hundredths of a percent (0.01%). This percent shall not be rounded to the nearest whole percent or to zero percent if minimal vehicles exist. The Design Hour is considered to be the 30th largest hourly volume for a given calendar year.
AADT_COMBINATION — is the Annual Average Daily Traffic for Combination Trucks and must be reported for the entire NHS and all Sample Panel sections. This item requires detailed vehicle classification data and includes FHWA vehicle classes 8-13.
PCT_DH_COMBINATION — Percent Design Hour Combination Trucks is the Design Hour combination truck volume as a percentage of the applicable roadway section's Design Hour volume rounded to the nearest hundredths of a percent (0.01%). This percent shall not be rounded to the nearest whole percent or to zero percent if minimal vehicles exist. The Design Hour is considered to be the 30th largest hourly volume for a given calendar year.
K_FACTOR — is the design hour volume (i.e., 30th highest hourly volume) expressed as a percentage of total AADT. This item is needed for all Sample Panel sections. It is best developed from hourly ATR data. The different methods used for developing short-term and continuous count K-FACTORs are described in more detail in Chapter 3.
DIR_FACTOR — is the percent of design hour volume flowing in the peak direction and is required for all Sample Panel sections.
Section 5.4 provides additional information for calculating values for each of these elements.
Further guidance for items 21 through 27 can be found in TMG Chapter 3. HPMS traffic data items 28 through 33 are not collected by the State's traffic monitoring program.
The standard HPMS reporting requirements for traffic data include the following topics, which are addressed in the subsequent paragraphs:
AADT data are reported in HPMS for both mainlines and ramps on Federal aid facilities. The FHWA HPMS Field Manual provides the following guidelines.
Four approaches can be used to conduct ramp counts where needed:
Additionally, the following approach may be used for estimating ramp counts:
Refer to Appendix K for typical ramp and interchange configurations and computational examples. Travel Estimates for Local Roads and Rural Minor Collectors:
Instead of reporting AADT values for local roads and rural minor collectors, VMT estimates are reported for these functional classes. These estimates should be produced by the States using a documented statistically valid procedure based on monitored traffic. The estimated VMT is summarized by States and is reported in the Statewide Summaries dataset, which is stored in the Summaries catalog of the HPMS database.
Each State is encouraged to select the best approach for collecting or estimating local road data and rural minor collectors that meets their business needs.
The TMG does not recommend using a fixed percent of traffic growth method or using the result of calculating statewide total VMT minus highway systems VMT to produce the estimates for local roads and rural minor collectors.
Other methods can be used to estimate counts and include the following:
The following example explains the use of these four methods to estimate current year counts based on previous year actual counts.
In this example, a location in an urban area on a principal arterial roadway does not have a current year counted traffic volume. The AADT from the previous year was 44,500. The current year traffic can be estimated using one of the four methods or a combination of these methods.
Using the first method, a linear projection is performed based on historical data from the same site. If the growth rate is -3% per year, the current year traffic volume estimate would then be 43,165, which can be rounded to 43,000.
Using the second method, it has been determined that one or more permanent sites on similar routes exhibit a growth rate of -3.7%. The current year traffic volume estimate would then be 42,854, rounded to 43,000.
The third approach uses the previously determined urban system growth rate of -3.6% based on all permanent counters in urban areas. The current year traffic volume estimate is therefore 42,898, which is rounded to 43,000.
The fourth approach is based on a regional growth rate of -3.8% from all permanent counters in the region, yielding a current year traffic volume estimate of 42,809. This value is rounded to 43,000.
In the above example, all four methods yield the same value. Use method number one first to obtain estimate counts. If site-specific growth is not available, then use route-specific growth; if route-specific growth is not available, use systems growth; and finally if systems growth is not available, regional growth should be used.
The following guidance should be followed regarding rounding of AADTs:
When sufficient data are available to develop a reasonable AADT estimation from permanent continuous counters for the current year, rounding is not recommended. Rounding can be used to estimate AADT for HPMS purposes when there is no current year data available from permanent continuous counters, as discussed in the four previous examples.
The rounding of AADTs is acceptable for HPMS purposes when following the scheme recommended by the AASHTO Guide. The TMG does not recommend this unless it is common practice for the State to round all traffic data in its traffic monitoring database and 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 data have been made and should NOT be performed when calculating percent single-unit and combination trucks. Low volume counts (e.g., 0.2%) should not be rounded to report zero as a volume or as a percent since this will not accurately represent the presence of the minimal volumes and will also show no change in trends. A zero should only be reported when the actual count is zero.
Accurate motorcycle counting may require unique procedures and equipment. More information is provided on this topic in Chapter 3. Some limitations exist regarding the use of technology in properly measuring motorcycle counts. More information on the type of equipment used for these counts is found in Appendix D.
Vehicle classification data are needed in HPMS to determine the accurate percentage of truck traffic on the roadway during peak travel hours as well as off-peak travel hours. Both truck volume (AADT_SINGLE_UNIT and AADT_COMBINATION) and truck percentage data are reported for the various types of records in HPMS. These data are used to analyze the impact of truck traffic on pavement deterioration and also for reporting in summary tables in HPMS.
Since classification counts are required by HPMS for many road sections, it will likely be too costly to maintain permanent traffic classifiers on all of these sections. Therefore, a combination of permanent and portable classifiers will be needed to meet the requirement. This will entail adjusting portable classification counts by the permanent classifiers as further described in TMG Chapter 3.
The AADT for trucks is required for the entire NHS and all HPMS Sample Panel Sections. Two types of truck AADT are reported in HPMS: AADT_SINGLE_UNIT (which is the single-unit truck and bus AADT for vehicle classes 4 through 7) and AADT_COMBINATION (which is the combination truck AADT for vehicle classes 8 through 13).
Appendix A provides additional information on the 13-vehicle classifications.
In addition to truck AADT for single and combination trucks, two additional types of truck data are required. These are the percentage of single-unit trucks and buses (PCT_DH_SINGLE_UNIT) and percentage of combination trucks (PCT_DH_COMBINATION) traveling on a section of road during the design hour.
Estimates of travel by vehicle type are required for HPMS and are summarized by Area Type (AT) and Functional System (FS) group. While there are seven functional systems, there are only three FS groups. The three FS groups are combined with two area types, rural and urban, for six combined AT and FS groups as shown in Table 5-2.
HPMS is designed as a random sample stratified by traffic volume groups. To the extent that vehicle class counts reflect this design, they may be averaged to estimate the distribution of VMT by vehicle type. Estimating the VMT by vehicle type to meet this requirement is not necessary.
Area Type and Functional System |
Group |
|---|---|
Rural Interstate |
1 |
Rural Other Arterial (includes Other Freeways and Expressways, Other Principal Arterials, and Minor Arterials) |
2 |
Rural Other (includes Major Collectors, Minor Collectors, and Locals) |
3 |
Urban Interstate |
4 |
Urban Other Arterial (includes Other Freeways and Expressways, Other Principal Arterials, and Minor Arterials) |
5 |
Urban Other (includes Major Collectors, Minor Collectors, and Locals) |
6 |
The estimates of travel by vehicle type are reported as percent values for the type(s) of vehicles in each AT-FS group, such as percent of motorcycles (PCT MC), percent of passenger cars (PCT CARS), and percent of single-unit trucks (PCT SU TRUCKS).
These estimated values are reported in the Vehicle Summaries dataset and are stored in the Summaries catalog of the HPMS database. This information can be derived from the vehicle classification and WIM programs.
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.
High- and low-volume sites are specific to each State, and engineering judgment is required to determine the values for these for each State individually. 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 (i.e., traffic counts are same for the length of the sections) as determined by prior counts or knowledge of local traffic conditions, more than one section may be represented by a single traffic count station as long as traffic does not vary more than 10%. In this scenario, local traffic monitoring offices may know of no major traffic generators or significant enough development to cause changes in the traffic volumes within HPMS sections. This situation can result in more than one HPMS section using the same traffic count station. HPMS sections exist for reasons other than fluctuations in traffic volumes, as noted in the discussion of TOPS sections. Selection of count locations should be based on previous count experience on the section or adjacent sections, recent land use development, and the existence of uncounted sections along the route.
Metadata for traffic are also reported in HPMS and are used to further explain any variability in the collection and/or reporting of traffic, such as: whether the AADT is adjusted for DOW or for number of axles; if the traffic data are reported from the State traffic database only; or if the data are reported from the State traffic database and local governments.
The metadata provide additional information about the following:
Additional information on the reporting of traffic metadata in HPMS can be found in Chapter 3 of the HPMS Field Manual.
The traffic data supplied for HPMS use are derived from the State's regular traffic monitoring program with adjustments (such as aggregating data for short/long samples or using weighted averages for HPMS sections) to meet specific HPMS requirements. Collection of HPMS-specific traffic data should be fully integrated into the normal traffic monitoring program. As stated in Chapter 3, measures should be taken to ensure the quality of all data within the traffic monitoring program.
For HPMS reporting purposes, metadata tied with the Annual Average Daily Traffic (AADT), the Single-Unit Truck & Bus (AADT_SINGLE_UNIT), and the Combination Truck AADT (AADT_COMBINATION) have the following definitions regarding data sources:
Code A: Derived directly from actual short-term or continuous counts consistent with procedures outlined in the
TMG by a State or local government agency.
Code B: Derived not directly from actual short-term or continuous counts (even though short-term count or continuous counts may be used for method calibration or validation data) through methods such as travel demand modeling, statistical trending analysis, or cellular data modeling by a State or local government agency.
Code C: Derived directly from actual short-term or continuous counts consistent with procedures outlined in the
TMG that are purchased or acquired from a private business or non-governmental entity.
Code D: Derived not directly from actual short-term or continuous counts (even though short-term count or continuous counts may be used for method calibration or validation data) through methods such as travel demand modeling, statistical trending analysis, or cellular data modeling purchased or acquired from a private business or non-governmental entity.
Code E: Other: Data are developed or acquired using a method not identified in A, B, C, or D.
Code |
Source |
Type |
Method |
|---|---|---|---|
A |
State or local government agency |
Actual count |
Consistent with short-term count factoring procedures outlined in the TMG |
B |
State or local government agency |
Travel demand model output, statistical trend analysis, cellular data modeling, or similar |
Alternative methods not identified in the TMG |
C |
Private business or non-governmental agency |
Actual count |
Consistent with short term count factoring procedures outlined in the TMG |
D |
Private business or non-governmental agency |
Travel demand model output, statistical trend analysis, cellular data modeling, or similar |
Alternative methods not identified in the TMG |
E |
Data are developed or acquired using a method not identified in A, B, C, or D |
||
Several guidelines should be followed when collecting and processing traffic data to ensure that the highest quality traffic data are provided to HPMS. This section describes the following guidelines:
States should provide at least one continuous counter on each major (as defined by HPMS) Principal Arterial System (PAS)/NHS highway route, where possible. HPMS requires at least one counter; however, States are encouraged to use engineering judgment. The NHS is defined in 23 U.S.C. 103(b) and includes the Interstate System and over 117,000 miles of other roads and connections to transportation facilities serving major population centers and intermodal facilities. 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 editing process, with documentation of the edits performed based on historic trends.
The TMG recommends that the short-term counts used for HPMS reporting purposes be fully integrated with the agency's coverage count program. This means using the same personnel, procedure, equipment, and counting schedule used for coverage and other traffic counts.
Highway agencies should be aware of the potential for geographic and temporal bias when scheduling counts and counteract it by devising strategies to distribute counts as much as feasible.
The HPMS sample and full extent sections are located within the traffic volume segments defined in the coverage count program. Traffic counts taken to meet the HPMS requirements are taken the same way as other short-term traffic volume counts. These are described in Chapter 3. The main difference is that the HPMS has specified nationally standardized criteria for the collection and term of the counts. The HPMS Coordinator should request those additional counts needed for HPMS sufficiently in advance (i.e., prior to scheduling of traffic counts for the data collection year) to allow them to be included in the regular coverage count program. Whenever possible, coverage counts taken within a defined traffic count roadway section should be taken within an HPMS section.
Since HPMS sections within the TOPS may change over time, this may require counts to be added or eliminated as needed for the traffic count roadway section.
One third of the HPMS full extent (NHS/PAS) and sample sections should be included in each current year coverage sample to ensure that, at a minimum, each of these HPMS full extent/sample sections are counted once every 3 years.
While short-term traffic counts can be taken for anywhere from just a few hours to more than a week, the TMG recommends a minimum of a 24-hour monitoring period for roads with traffic volumes of greater than 5,000 AADT and a 48-hour monitoring period for lower-volume roads and any effort involving the collection of vehicle classification data. The 48-hour minimum count duration is recommended for smaller roads and classification counts because traffic variability is high for both low-volume roads and for most truck counts. The additional
24 hours of counting increases the statistical reliability of the AADT estimates computed from these more variable counts. This is particularly important for the HPMS because common data collection periods from all States ensure similar levels of accuracy and precision for all volume data in the HPMS database.
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. No other factors (such as equipment error factors) should be applied; only daily, seasonal, and axle correction factors should be used.
A minimum of one count every 6 years is required for ramps.
At a minimum, 48-hour ramp counts should be adjusted with axle correction factors as needed.
The same procedures used to develop AADTs on all HPMS sections should be used to develop ramp AADTs. 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. Good judgment and experience should be applied regarding factor use. Additional information on developing adjustment factors is found in Chapter 3. 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. If a State has a traffic modeling office, ramp traffic estimates may be computed as part of the modeling process.
Vehicle classification counts reported in HPMS should follow the guidelines outlined in Chapter 3 of the TMG and the latest HPMS Field Manual. Counts should be performed for a minimum of 48 hours and should contain at least six vehicle classes: Motorcycles, Passenger cars, Light trucks, Buses, Single-Unit trucks, and Combination trucks. Hourly vehicle classification data by direction should be used for all the truck related data items, including PCT_DH-SINGLE_UNIT (trucks) and PCT_DH_COMBINATION (trucks).
The State should ensure that data collection equipment is calibrated and tested in the field and that the results are validated for accuracy prior to use for HPMS reporting. More information on equipment calibration procedures is found in Appendix D.
The traffic data items reported for HPMS are derived from the traffic data collection activities, which are part of the State's traffic monitoring program. These data items include the following:
The calculation methods for these data items are described in the following paragraphs.
AADT calculations are defined in Chapter 3. The following quality control (QC) checks on AADT data will be performed manually by FHWA staff or will be checked by the HPMS submittal software and may indicate an error with the AADT data:
AADT for Single Unit Trucks – This value represents all single-unit truck and bus activity based on vehicle classification count data from both the State's and other agency's traffic monitoring programs over all days of the week and all seasons of the year. Single-unit trucks are defined as vehicle classes five through seven, and buses are defined as vehicle class four (based on the FHWA 13 category system). AADT_SINGLE_UNIT is reported as the volume for all single-unit activity over all days of the week and seasons of the year in terms of the AADT. The following QC checks will be performed by the HPMS submittal software and may indicate an error with the AADT_SINGLE_UNIT data:
PCT_ DH_SINGLE_UNIT is the single-unit truck and bus volume during the design hour shown as the percentage of the section AADT, to the nearest hundredth of a percent (0.01%). For example, if the section AADT is 3,000 and the volume of single-unit trucks and buses in the design hour is 65, then the PCT_DH_SINGLE_UNIT data item is shown as 2.17%. This percent should not be rounded to the nearest whole percent or to zero percent if minimal trucks and buses exist. The following QC check will be performed by the HPMS submittal software and may indicate an error with the PCT_DH_SINGLE_UNIT data:
If (PCT_DH_SINGLE_UNIT/100) x AADT > AADT_SINGLE_UNIT, there is an error.
AADT for Combination Trucks represents all combination truck activity based on vehicle classification count data from both the State's and other agencies' traffic monitoring programs over all days of the week and all seasons of the year. Combination trucks are defined as vehicle classes eight through thirteen. AADT_COMBINATION is reported as the volume for combination-unit truck activity over all days of the week and seasons of the year in terms of the AADT. The following QC checks will be performed by the HPMS submittal software and may indicate an error with the AADT_COMBINATION data:
PCT_DH_COMBINATION is the percent of design combination trucks during the design hour. The percent of peak combination trucks is the combination truck traffic volume during the design hour shown as the percentage of section AADT, to the nearest hundredth of a percent (0.01%). For example, if the section AADT is 5,000 and the volume of combination trucks in the design hour is 164, then the PCT_DH_COMBINATION trucks is shown as 3.28%. This percent should not be rounded to the nearest whole percent or to zero percent if minimal trucks exist. The following QC check will be performed by the HPMS submittal software and may indicate an error with the PCT_DH_COMBINATION data:
If (PCT_DH_COMBINATION/100) > AADT_COMBINATION, there is an error.
K_FACTOR is the design hour volume expressed as a percent of AADT. The K_FACTOR conveys the design hour volume or the 30th highest hourly volume, as a percent of total AADT. The value for K_FACTOR is reported to the nearest percent. For example, if the traffic volume during the design hour or 30th highest hourly volume is 10% of the AADT for a section of road, then the K_FACTOR is reported as 10 for that section. The following QC checks will be performed by the HPMS submittal software and may indicate an error with the K_FACTOR data:
DIR_FACTOR the percent of design hour volume flowing in the peak direction. The DIR_FACTOR is reported as the percentage of design hour volume (30th highest hour) flowing in the peak direction. For example, a DIR_FACTOR of 60 indicates that 60 percent of the design hour volume is flowing in the peak direction. A value of 100 is used for one-way facilities when reporting this value in HPMS. The following QC checks will be performed by the HPMS submittal software and may indicate an error with the DIR_FACTOR data:
FUTURE_AADT may not be an item reported as part of a State's traffic monitoring program, although it is reported as a data item in HPMS. The estimates for FUTURE_AADT are usually developed from statewide modeling programs and on input provided by MPOs as appropriate. If data from statewide modeling programs are not available, then population growth or gasoline tax growth can be used to estimate traffic growth. The FUTURE_AADT is a 20-year forecast AADT, which may cover a period of 18 to 25 years from the date of the HPMS data year submittal. The following QC checks will be performed by the HPMS submittal software and may indicate an error with the FUTURE_AADT data:
The FHWA Travel Monitoring Analysis System (TMAS) serves as the national traffic data repository and offers broad ranges of analytical functions. The current TMAS enables the production of the monthly Traffic Volume Trends (TVT) report and various outputs associated with the Vehicle Travel Information System (VTRIS).
TMAS processes data from all 50 States and District of Columbia monthly. Currently there are over 6,000 volume, 2,800 classification, and 600 weigh-in-motion permanent site data in TMAS. The TVT functionality estimates vehicle miles traveled by functional classification by utilizing both HPMS (yearly) and TMAS (monthly) data. TMAS provides a national consistent process and QC approach to all TMG-formatted data. A complete list of QC codes and QC methods for each data type is provided in Appendix B. Data from other public entities other than State highway agencies can also be uploaded, processed, and stored with TMAS. To gain access rights to TMAS or data available from TMAS, please contact the Office of Highway Policy Information.
The purpose of TMAS is to provide an online method for States to submit their station, volume, classification, and weight data to FHWA. This section of the TMG provides all the necessary FHWA TMAS data requirements for ensuring the highest quality traffic dataset. Developing and maintaining a quality data program is the most critical program activity that agencies perform and requires careful data evaluation and continuous data checking.
Maintaining a quality data program helps agencies to provide customers with a quality dataset and helps to establish and ensure program resources are available for the data program.
TMAS is FHWA's data uploading, processing, validating, storing, and reporting traffic volume software system. TMAS has many customers and users organized into three categories including data providers, data users, and system administrators. The TMAS data requirements are critically important to State DOTs, as well as other data providers to TMAS. The most important report that TMAS supplies data to on a monthly basis is the TVT report that provides traffic volume data that are summarized by geographic regional trends across the United States.
TMAS provides FHWA with a national traffic volume dataset. All traffic data currently provided from TMAS users and contributors comes from continuous counting stations that also supply information to HPMS. Within the HPMS reporting requirements, TMAS traffic volume datasets allow for the calculation of many traffic volume statistics such as AADT), K-FACTOR (design hour volume), and D-FACTOR (directional distribution) traffic volume statistics. HPMS reporting allows FHWA to calculate Federal highway funding formulas that allocate funds to State DOTs based on statewide traffic volumes and linear miles of roadway.
FHWA has developed TMAS to automatically provide feedback to the user using the most efficient and expeditious electronic methods possible. Providing feedback is critically important to ensuring the necessary collaborative communication between FHWA and the agency. For example, feedback to the data provider is automatically generated and sent to the data provider once data files are submitted and data files are processed in TMAS. The agency can print and save this feedback, helping the data provider keep track and demonstrate agency compliance with FHWA submittal requirements (e.g., showing the submittal of data was completed by the 25th day of every month). This feedback loop is also important for all agencies so that communication across Federal, State, and other agencies continually occurs. TMAS historically has demonstrated that, as the TMAS features and communication tools are enhanced over time, more data are submitted that are higher quality and pass more quality checks.
Several reports can be generated using the TMAS system. For example, a daily volume report provides all the hours within a day of data that are loaded into the system to be displayed and formatted in a report that can be printed. Reports are organized by daily, monthly, or annual reporting and can be generated for any site that contains data that passed all TMAS system checks.
State DOTs collect traffic volume data and perform validation processing (quality assurance and quality checking – QA/QC) of the data from continuous counting stations. These data can be collected, stored, and processed by individual vehicle record recording every event of a vehicle or a total number of vehicles by hour. After performing validation processing, the data are uploaded to FHWA's TMAS software for further evaluation, data processing, storage, and reporting.
State DOTs upload daily traffic volume data that are then averaged to create a Monthly Average Daily Traffic (MADT) statistic. MADTs are used in the TVT report to calculate vehicle miles traveled by month. All TVT reports are organized by month of the year and are available to State DOTs.
State DOTs collect daily and monthly traffic volume data that are then analyzed and processed for annual statistical calculations such as the K-factor (design hour that is typically the 30th highest hourly volume of the year). Although the TVT report does not report annual traffic volume statistics, the TVT provides all monthly traffic volume data by year.
Traffic Volume Trends is a monthly report based on hourly traffic count data reported by the States. These data are collected at approximately 5,000 continuous traffic counting locations nationwide and are used to estimate the percent change in traffic for the current month compared with the same month in the previous year. Estimates are re-adjusted annually to match the vehicle miles of travel from the HPMS and are continually updated with additional data. All Travel Volume Trend reports can be accessed via the Office of Highway Policy Information website.
