Long-Term Pavement 

Performance Pavement Loading 

User Guide (LTPP PLUG)

PUBLICATION NO. FHWA-HRT-13-089 OCTOBER 2013

Research, Development, and Technology

Turner-Fairbank Highway Research Center

6300 Georgetown Pike

McLean, VA 22101-2296
FOREWORD 

This guide addresses the selection and use of axle loading defaults for Mechanistic-Empirical 

Pavement Design Guide (MEPDG) applications. The defaults were developed based on weighin-motion (WIM) data from the Long-Term Pavement Performance (LTPP) Special Pavement 

Study (SPS) Transportation Pooled Fund Study (TPF). The guide consists of two parts. The first 

part provides guidelines for selecting and using LTPP SPS TPF axle loading defaults with the 

MEPDG and DARWin-ME software. These defaults provide a source of axle loading 

information for pavement analysis for locations where site-specific axle load spectra are not 

available. The second part of the guide provides practical guidelines that States and LTPP can 

use to generate additional MEPDG traffic loading defaults based on their own WIM data or for 

specific analysis purposes. In addition, this guide contains an operator’s manual that supports the 

use of the LTPP PLUG software. This software helps users select site-specific or default axle 

loading conditions from its traffic loading library and produces axle load distribution input files 

for use with the MEPDG or DARWin-ME software. The software can be used to store, view, and 

group multiple normalized axle load spectra (NALS) and to develop MEPDG inputs and defaults 

using agency-provided data. 

 Jorge E. Pagán-Ortiz 

 Director, Office of Infrastructure 

 Research and Development 

Notice

This document is disseminated under the sponsorship of the U.S. Department of Transportation 

in the interest of information exchange. The U.S. Government assumes no liability for the use 

of the information contained in this document. 

The U.S. Government does not endorse products or manufacturers. Trademarks or 

manufacturers’ names appear in this report only because they are considered essential to the 

objective of the document. 

Quality Assurance Statement

The Federal Highway Administration (FHWA) provides high-quality information to serve 

Government, industry, and the public in a manner that promotes public understanding. Standards 

and policies are used to ensure and maximize the quality, objectivity, utility, and integrity of its 

information. FHWA periodically reviews quality issues and adjusts its programs and processes to 

ensure continuous quality improvement. 
TECHNICAL REPORT DOCUMENTATION PAGE 

1. Report No. 

FHWA-HRT-13-089 

2. Government Accession No. 3. Recipient’s Catalog No. 

4. Title and Subtitle 

Long-Term Pavement Performance Pavement Loading User 

Guide (LTPP PLUG) 

5. Report Date 

October 2013 

6. Performing Organization Code 

7. Author(s) 

O.I. Selezneva and M. Hallenbeck 

8. Performing Organization Report No. 

9. Performing Organization Name and Address 

Applied Research Associates, Inc. 

7184 Troy Hill Drive, Suite N 

Elkridge, Maryland 21075-7056 

10. Work Unit No. (TRAIS) 

11. Contract or Grant No. 

DTFH61-02-C-00138 

12. Sponsoring Agency Name and Address 

Office of Infrastructure Research and Development 

Federal Highway Administration 

6300 Georgetown Pike 

McLean, Virginia 22101-2296 

13. Type of Report and Period Covered 

Guide 

14. Sponsoring Agency Code 

15. Supplementary Notes 

Contracting Officer’s Technical Representative (COTR): Larry Wiser, HRDI LTPP Data Analysis Contract 

16. Abstract 

This guide addresses the selection and use of axle loading defaults for Mechanistic-Empirical Pavement Design 

Guide (MEPDG) applications. The defaults were developed based on weigh-in-motion (WIM) data from the LongTerm Pavement Performance (LTPP) Special Pavement Study (SPS) Transportation Pooled Fund Study (TPF). The 

guide consists of two parts. The first part provides guidelines for selecting and using LTPP SPS TPF axle loading 

defaults with the MEPDG and DARWin-ME software. These defaults provide a source of axle loading information 

for pavement analysis for locations where site-specific axle load spectra are not available. The second part of the 

guide provides practical guidelines that States and LTPP can use to generate additional MEPDG traffic loading 

defaults based on their own WIM data or for specific analysis purposes. In addition, this guide contains an 

operator’s manual that supports the use of the LTPP PLUG software. This software helps users select site-specific 

or default axle loading conditions from its traffic loading library and produces axle load distribution input files for 

use with the MEPDG or DARWin-ME software. The software can be used to store, view, and group multiple 

normalized axle load spectra (NALS) and to develop MEPDG inputs and defaults using agency-provided data. 

17. Key Words 

Long-term performance, Transportation Pooled Fund 

Study, Mechanistic-Empirical Pavement Design 

Guide, weigh-in-motion, load spectra 

18. Distribution Statement 

No restrictions. This document is available to the public 

through the National Technical Information Service, 

Springfield, VA 22161. 

19. Security Classif. (of this report) 

Unclassified 

20. Security Classif (of this page) 

Unclassified 

21. No. of Pages 

98 

22. Price 

Form DOT F 1700.7 (8-72) Reproduction of completed page authorized 
ii 
iii 

TABLE OF CONTENTS 

INTRODUCTION......................................................................................................................... 1

BACKGROUND ....................................................................................................................... 1

PURPOSE AND SCOPE OF THIS GUIDE ........................................................................... 2

ORGANIZATION OF THE GUIDE ...................................................................................... 2

PART I—GUIDELINES FOR USING LTPP SPS TPF AXLE LOADING DEFAULTS ..... 3

WHEN AXLE LOADING DEFAULTS SHOULD AND SHOULD NOT BE USED ........ 3

MEPDG TRAFFIC LOADING DEFAULTS BASED ON LTPP SPS TPF WIM 

SITES ................................................................................................................................... 4

Overview of Traffic Loading Defaults Based on SPS TPF WIM Data .................................. 5

Global Axle Loading Defaults Based on LTPP SPS TPF Sites (Tier 1) ................................ 5

Axle Load Spectra Defaults Representing Alternative Loading Conditions (Tier 2) ............. 6

Characteristics and Recommended Use of Tier 2 NALS Clusters ....................................... 10

Description of APC Defaults ................................................................................................ 25

Description of Wheelbase and Axle Spacing Defaults ......................................................... 25

Description of Default Axle Spacings for Multi-Axle Groups ............................................. 27

GUIDELINES FOR SELECTING AXLE LOAD SPECTRA FOR THE MEPDG ........ 27

Knowledge of Local Traffic Loading Conditions ................................................................. 27

Determination of the Dominant Truck Classes ..................................................................... 28

Applying What the Analyst Has Learned About Truck Loads ............................................. 29

MEPDG Sensitivity Test ....................................................................................................... 31

Limitations of Loading Cluster NALS Defaults ................................................................... 32

MEPDG TRAFFIC INPUTS BEYOND AXLE LOAD SPECTRA .................................... 32

PART II—GUIDELINES FOR DEVELOPING AXLE LOADING DEFAULTS .............. 33

INTRODUCTION .................................................................................................................. 33

HOW TO CAPTURE DIFFERENCES IN AXLE LOADING IN DEFAULTS .............. 34

APPROACH FOR DEVELOPMENT OF AXLE LOADING DEFAULTS ..................... 35

DATA SELECTION AND DEVELOPMENT OF RANALS FOR INDIVIDUAL 

SITES ................................................................................................................................. 36

Data Selection Criteria for Development of Site-Specific Representative NALS ................ 37

Procedure for Development of RANALS Estimates ............................................................ 39

DEVELOPMENT OF GLOBAL NALS DEFAULTS (TIER 1) ........................................ 39

Overview ............................................................................................................................... 39

Procedure for Development of Global NALS Defaults (Tier 1) ........................................... 40

DEVELOPMENT OF ALTERNATE NALS DEFAULTS REPRESENTING 

ALTERNATIVE AXLE LOADING CONDITIONS (TIER 2) .................................... 40

Methodology for Grouping WIM Sites With Similar Loading Conditions .......................... 40

Procedure for Development of NALS Defaults Representing Different Loading 

Conditions ....................................................................................................................... 41

DEVELOPMENT OF REPRESENTATIVE SITE-SPECIFIC AND DEFAULT 

AXLE-PER-CLASS COEFFICIENTS ........................................................................... 46

Overview ............................................................................................................................... 46

Procedure to Develop Site-Specific and Default APC Coefficients ..................................... 47

DEVELOPMENT OF DEFAULT AXLE SPACING AND WHEELBASE VALUES .... 47

Average Axle Spacing and Wheelbase for JPCP Model ...................................................... 47
iv 

Procedure to Compute Average Axle Spacing and Wheelbase ............................................ 48

Procedure to Compute Axle Spacing for Multi-Axle Groups .............................................. 49

USE OF AXLE LOADING DEFAULTS WITH DARWIN-ME ....................................... 49

APPENDIX A. LTPP PLUG SOFTWARE OPERATOR’S MANUAL................................ 51

PURPOSE AND APPLICABILITY ..................................................................................... 51

STARTING THE APPLICATION ....................................................................................... 51

Microsoft® Access Reference Libraries ............................................................................... 51

FUNCTIONALITY DESCRIPTION .................................................................................... 52

Select Actions from the Main Menu ..................................................................................... 52

Import Traffic Summaries to LTPP PLUG Database ........................................................... 54

Select NALS Source for MEPDG Use ................................................................................. 56

Select Site-Specific NALS for MEPDG Use ........................................................................ 57

Select Default NALS for MEPDG Use—Manual Selection ................................................ 59

Select Default NALS for MEPDG Use—Assisted, Interactive NALS Assignment ............ 61

Select User-Defined NALS for MEPDG Use ....................................................................... 63

Generate MEPDG NALS Input Files.................................................................................... 65

View, Group, and Combine NALS from Multiple WIM Sites ............................................. 65

Compute and Record User-Defined NALS for Groups of Sites ........................................... 67

APPENDIX B: LTPP PLUG DATABASE DATA DICTIONARY ....................................... 71

REFERENCES ............................................................................................................................ 89

 
v 

LIST OF FIGURES 

Figure 1. Equation. Computation of RPPIF statistics ................................................................... 42

Figure 2. Screen capture. Selection of necessary library references ............................................. 52

Figure 3. Screen capture. Main menu for selecting different actions ........................................... 53

Figure 4. Screen capture. Data import form for importing traffic data summaries ...................... 55

Figure 5. Screen capture. Select NALS source form for selecting loading inputs for MEPDG 

use ........................................................................................................................................... 56

Figure 6. Screen capture. Review and generation of MEPDG input files for site-specific 

NALS ...................................................................................................................................... 58

Figure 7. Screen capture. Review of site-specific NALS ............................................................. 59

Figure 8. Screen capture. Manual selection and generation of MEPDG input files using 

default NALS .......................................................................................................................... 60

Figure 9. Screen capture. Review of manually selected default NALS ........................................ 61

Figure 10. Screen capture. Assisted, interactive assignment of default NALS ............................ 62

Figure 11. Screen capture. Review of user-defined NALS .......................................................... 64

Figure 12. Screen capture. View, group, and combine NALS from multiple WIM sites............. 66

Figure 13. Screen capture. Compute and record user-defined NALS. ......................................... 68
vi 

LIST OF TABLES 

Table 1. Summary of NALS cluster groups representing different loading conditions by 

vehicle class and axle type ........................................................................................................ 9

Table 2. Summary of axle loading categories by weight for different axle types ........................ 10

Table 3. Description of alternative Class 4 axle loading conditions ............................................. 11

Table 4. Description of alternative Class 5 axle loading conditions ............................................. 12

Table 5. Description of alternative Class 6 axle loading conditions ............................................. 13

Table 6. Description of alternative Class 7 axle loading conditions ............................................. 15

Table 7. Description of alternative Class 8 axle loading conditions ............................................. 17

Table 8. Description of alternative Class 9 axle loading conditions ............................................. 18

Table 9. Description of alternative Class 10 axle loading conditions ........................................... 20

Table 10. Description of alternative Class 11 axle loading conditions ......................................... 21

Table 11. Description of alternative Class 12 axle loading conditions ......................................... 22

Table 12. Description of alternative Class 13 axle loading conditions ......................................... 23

Table 13. Global default APC based on 26 SPS TPF sites ........................................................... 25

Table 14. Distribution of axle spacing on tractor units for FHWA classes 8 through 13 ............. 26

Table 15. Distribution of axle spacing by vehicle class using sample of SPS TPF WIM data .... 27

Table 16. Average axle spacing for multi-axle groups ................................................................. 27

Table 17. Example of computing dominant truck classes ............................................................ 29

Table 18. Pavement performance impact factors, Wij ................................................................... 43

Table 19. Example of traffic design conditions for each vehicle class ......................................... 44

Table 20. Difference in RPPIF per axle likely to cause change in pavement performance ......... 46

Table 21. Field names and descriptions for ALF_DEFAULT_ALS ............................................ 73

Table 22. Field names and descriptions for ALF_Gen_Axle_Group ........................................... 73

Table 23. Field names and descriptions for DEFAULT_AxlesPerTruck ..................................... 73

Table 24. Field names and descriptions for DEFAULT_NALS ................................................... 73

Table 25. Field names and descriptions for LTPP_CODES ......................................................... 75

Table 26. Field names and descriptions for PLUG_LEF_FOR_ESAL ........................................ 76

Table 27. Field names and descriptions for PLUG_W_FACTORS_FOR_RPPIF....................... 77

Table 28. Field names and descriptions for SITE_SPECIFIC_AxlesPerTruck ........................... 80

Table 29. Field names and descriptions for SITE_SPECIFIC_NALS ......................................... 80

Table 30. Field names and descriptions for SITE_SPECIFIC_NVCD ........................................ 82

Table 31. Field names and descriptions for USER_DEFINED_NALS ....................................... 82

Table 32. Field names and descriptions for XMLGen_AxleLoadDistribution ............................ 85

Table 33. Field names and descriptions for XMLGen_AxleLoadMain_Template ...................... 85

Table 34. Field names and descriptions for 

XMLGen_DEFAULT_NALS_By_Loading_Cluster ............................................................. 85
vii 

LIST OF ABBREVIATIONS AND ACRONYMS 

AADTT Average Annual Daily Truck Traffic 

AASHTO American Association of State Highway and Transportation Officials 

APC Axle-per-Truck Coefficient 

ASTM ASTM International (formerly American Society for Testing and Materials) 

AVC Automated Vehicle Classification 

DOW Day-of-the-Week 

ESAL Equivalent Single-Axle Load 

FHWA Federal Highway Administration 

GPS General Pavement Studies 

I Interstate 

JPCP Jointed Plain Concrete Pavement 

LTPP Long-Term Pavement Performance 

MEPDG Mechanistic-Empirical Pavement Design Guide 

MPO Metropolitan Planning Organization 

NALS Normalized Axle Load Spectra 

NCHRP National Cooperative Highway Research Program 

PLUG Pavement Loading User Guide 

QA Quality Assurance 

QC Quality Control 

RANALS Representative Annual Normalized Axle Load Spectra 

RPPIF Relative Pavement Performance Impact Factor 

RV Recreational Vehicle 

SHRP Strategic Highway Research Program 

SPS Specific Pavement Studies 

TPF Transportation Pooled-Fund (study) 

TWRG Truck Weight Road Group 

WIM Weigh-in-Motion 

1 

INTRODUCTION 

BACKGROUND 

Many State highway agencies are evaluating and implementing the American Association of 

State Highway and Transportation Officials (AASHTO) Mechanistic-Empirical Pavement 

Design Guide (MEPDG) and the DARWin-ME software.(1) The main MEPDG traffic inputs are 

normalized axle load spectra (NALS), a percentile truck classification volume distribution, truck 

volumes, and truck growth rates. In most earlier pavement design and analysis methodologies, 

the effect of traffic loads was accounted for in the design by using the AASHTO equivalency 

factors to compute the number of equivalent single-axle loads (ESAL).(2) Instead of using the 

computed ESAL values, the MEPDG and DARWin-ME software use the load spectra that can be 

used directly to estimate truck statistics. 

NALS are percentile distributions of axle type counts by load range. Individual NALS are 

computed for each axle type and truck class. The axle types included in the MEPDG design 

procedure are single, tandem, tridem, and quad, and the truck classes are vehicle classes 4 

through 13 from the Federal Highway Administration (FHWA) classification scheme.(3) The 

MEPDG uses NALS representative of a “typical day of the month.” For roads that do not show 

significant seasonal variations in percentages of heavy and light loads, the same NALS are used 

for all calendar months. 

Of all MEPDG traffic loading inputs, NALS are the most challenging owing to the high cost and 

considerable time to collect an adequate quantity of accurate axle load data. Therefore, the 

majority of pavement designs and analyses using the MEPDG and DARWin-ME software do not 

use site-specific NALS. Instead, most analyses rely on regional, agency-wide, or national NALS 

traffic loading defaults, combined with site-specific truck volume counts. It is important that 

these default NALS tables be as representative as possible of the actual truck traffic loading 

characteristics at the project site. 

The original default traffic datasets for the MEPDG were developed during National Cooperative 

Highway Research Program (NCHRP) Project 1-37A using Long-Term Pavement Performance 

(LTPP) traffic data available in 1998.(4) At that time, these data represented the best available 

and most comprehensive national set of weigh-in-motion (WIM) and automated vehicle 

classification (AVC) data. However, some concerns existed regarding the lack of documented 

quality of the data that were used to determine the truck traffic default values—specifically, the 

NALS values for each axle type within each class of trucks. Just as important, many agency 

personnel also questioned the quality and adequate quantity of their own State’s truck traffic 

data. Consequently, a new set of default NALS has been produced for use with the MEPDG and 

DARWin-ME software. In addition, detailed instructions have been developed to help States 

create NALS tables that reflect the unique truck types and trucking patterns in their State. 

To develop the improved default tables, LTPP undertook a Specific Pavement Studies (SPS) 

Transportation Pooled-Fund (TPF) study that focused on installation of highly reliable, wellcalibrated, permanent WIM systems, and collection of axle loading data using a uniform vehicle 

classification scheme and rigorous quality control procedures. One outcome of that ongoing 

effort is the production of research-quality traffic data (classification and weight), primarily to 
2 

support LTPP analysis projects. The SPS TPF study has generated high-quality traffic loading 

information for 26 LTPP SPS sites located in 23 different States that represent moderate- and 

high-volume rural principal arterial interstate and non-interstate highways. These data also allow 

the update of the original MEPDG axle loading defaults. The SPS TPF data and their use as 

default NALS tables are described in Part I of this guide. 

PURPOSE AND SCOPE OF THIS GUIDE 

This guide addresses two issues critical for MEPDG use: 

 How to select LTPP axle loading defaults (Part I). 

 How to develop axle loading defaults (Part II). 

This guide primarily focuses on NALS, but it also addresses other defaults computed from WIM 

data, including axle spacing, wheelbase, and axles-per-truck defaults. 

This guide is designed for analysts working with LTPP pavement performance data. It is 

designed specifically to aid in the selection of the default axle loading inputs computed using the 

SPS TPF data and application of those defaults to LTPP sites that do not have reliable sitespecific axle loading data, when such data are required for use in pavement design analysis. 

This guide also can be used outside of LTPP research and analysis. For example, the new SPS 

TPF based axle loading defaults can be used for any MEPDG-based pavement analysis when the 

pavement sites do not have reliable site-specific axle loading data. Agencies can also use this 

guide to help develop their own NALS defaults for use with the MEPDG and the DARWin-ME 

software. 

ORGANIZATION OF THE GUIDE 

As noted above, Part I of this guide provides guidance on selecting LTPP axle loading defaults 

for MEPDG use. Part II provides guidance on developing additional axle loading default tables 

for MEPDG use. Appendix A contains an operator’s manual for an accompanying software 

application and database application CD, and appendix B contains the data dictionary for the 

LTPP Pavement Loading User Guide (PLUG) database application. The LTPP PLUG database 

application can also be requested through the LTPP Customer Support Service Center at: 

E-mail: LTPPinfo@dot.gov 

Telephone: (202) 493-3035 

Fax: (202) 493-3161 
3 

PART I—GUIDELINES FOR USING LTPP SPS TPF AXLE LOADING DEFAULTS 

WHEN AXLE LOADING DEFAULTS SHOULD AND SHOULD NOT BE USED 

Many factors can affect the truck loading patterns on a roadway (e.g., the vehicle types observed, 

the axle configurations on those vehicles, and the axle weights carried). These different patterns 

result in the application of very different load spectra on those pavements. Among the most 

important factors affecting the traffic load applied to any given pavement are: 

 State’s truck size, weight, and permitting laws. 

 Degree to which those laws are enforced, both in general and on specific roads. 

 Commodities carried on specific roads. 

 Distances between origins and destinations served by truck traffic using that roadway 

(local service versus long haul operations). 

To account for the wide variation in traffic loading patterns, the best traffic data to use for 

pavement analysis are data collected with well-calibrated equipment on road segments directly 

leading to or from the site in question. Unfortunately, accurate truck and axle weight data are 

difficult and expensive to collect. In addition, rough pavement increases the dynamic motion 

(bouncing) of trucks, making it nearly impossible for WIM scales to collect accurate data on 

these roads. Thus, site-specific truck weight data frequently are not available for pavement 

analysis. When this situation occurs, the pavement analyst must use truck characteristic data 

(load spectra) collected elsewhere. 

As a general guide, a pavement analyst should use data from one specific WIM scale when: 

 The load spectra data from that scale have been collected at a site that serves the same 

traffic stream that is operating over the pavement for which load spectra are desired. For 

example, this may be the case if the scale is located upstream or downstream of the 

pavement analysis site on the same road and no major change in truck traffic occurs on 

that road between the scale and the pavement analysis site. 

 The scale is located on a road known to carry trucks with unique characteristics that are 

also present on the road for which load spectra data are needed. For example, this 

situation may occur if the scale is present on a coal hauling route in the same State as the 

pavement design site, which is also located on a road used for hauling coal. 

Selecting one specific WIM site from another location generally is not encouraged unless the 

pavement analyst is confident that the trucking patterns at the data collection site match those of 

the analysis site, even when the scale is on the same road as the pavement analysis site. Loading 

patterns frequently change from one segment of road to another. For example, Interstate (I)-405 

in the Seattle metropolitan region has a very different loading pattern south of the interchange 

with I-90 than it has north of that interchange. South of the I-90 interchange, I-405 carries a mix 

of urban delivery trucks and trucks serving the long haul movements that use I-90 to reach the 
4 

Port of Seattle and the large warehouse district located in the southern part of the metropolitan 

area. North of I-90, the vast majority of trucks are urban delivery trucks. 

If a single scale is not an obvious choice to provide load spectra data, the next option is to select 

a default load spectrum that represents the average of the loading patterns observed on a group of 

similar roads within the same State as the pavement analysis site. Part II of this guide describes 

how to develop these State-specific defaults. The advantage of selecting data that represent a 

group of sites is that the effects of any unusual condition that may exist at any one site is 

minimized by the lack of that unusual condition at the other sites in the group. Group averages 

are thus likely to be more representative of the loading patterns at other locations around the 

State. Selecting load spectra data collected only from the same State as the pavement to be 

analyzed also improves the accuracy of the default load spectra because it ensures that the trucks 

for which data are being collected follow the same truck size and weight laws. 

Unfortunately, some States do not have strong truck weighing programs or have yet to produce 

default load spectra in formats that are available to users of the MEPDG and DARWin-ME 

software. For example, some States have had considerable difficulty maintaining WIM scale 

calibration and do not trust much of the truck load data they have collected. 

When a State does not have reliable load spectra data, or the pavement analyst does not have 

access to a specific State’s load spectra data (which may be the case with many LTPP analyses), 

the best option is to use default load spectra developed at the national level. 

Using the high-quality data available from the SPS TPF study, the LTPP program has developed 

national-level load spectra defaults. These defaults were developed to represent a variety of 

alternative loading conditions observed in the national data sample. This variety helps pavement 

analysts select appropriate load spectra for their work, and it allows them to test the sensitivity of 

their analyses by re-running MEPDG analyses using different (e.g., lighter or heavier) default 

load spectra to determine the degree to which changes in load spectra affect their specific 

pavement analysis outcome. 

When using national-level defaults, analysts are encouraged to perform at least a few MEPDG 

sensitivity tests simply because load spectra developed at the national level cannot adequately 

account for the differences in trucking patterns that result from State-specific size and weight 

laws. Neither can national defaults account for trucking patterns unique to specific roads or 

regions within a State. At a minimum, MEPDG sensitivity tests provide pavement analysts with 

insight into the reliability of their analysis results, given the uncertainties inherent in the traffic 

inputs used to generate those results. 

MEPDG TRAFFIC LOADING DEFAULTS BASED ON LTPP SPS TPF WIM SITES 

The LTPP program worked with 22 States to install and operate 26 WIM scales under a set of 

rigorous quality control (QC) procedures, with frequent equipment calibration, testing, and 

validation. The result is a wealth of reliable traffic loading data that has been used to develop 

defaults for use with the MEPDG and DARWin-ME software instead of the initial set of defaults 

created as part of the NCHRP 1-37A study. 
5 

Overview of Traffic Loading Defaults Based on SPS TPF WIM Data 

NALS are the primary traffic loading defaults produced with the SPS TPF data. Other defaults 

produced are axle-per-truck coefficients (APC) and other axle spacing and wheelbase parameters 

used by the MEPDG software. 

Two tiers of NALS defaults were developed based on SPS TPF WIM data, as described in the 

following sections: 

 Tier 1—global defaults based on all applicable SPS TPF data. These defaults were 

computed by averaging the NALS produced for each of the 26 SPS TPF sites. Default 

global NALS are computed for each vehicle class and axle type. 

 Tier 2—supplemental defaults that represent different loading conditions (e.g., conditions 

heavier or lighter than the global default) observed in the SPS TPF. 

In addition to NALS, this guide contains one set of default APCs based on SPS TPF sites. 

Representative axle spacing and wheelbase values were also computed based on data from all 

SPS TPF sites and included in this guide. 

All defaults are included in the LTPP PLUG database application and can be viewed in graphical 

or tabular form. These defaults can be used to develop MEPDG or DARWin-ME files using the 

LTPP PLUG database application. 

Global Axle Loading Defaults Based on LTPP SPS TPF Sites (Tier 1) 

Global NALS defaults were computed based on a simple averaging of the representative annual 

NALS (RANALS) for the 26 SPS TPF sites. This computation was done separately for each 

vehicle class and axle type. 

Compared with the original MEPDG NALS defaults developed under the NCHRP 1-37A 

project, the SPS TPF NALS defaults have fewer very light and fewer very heavy loads. This is 

most likely because the new defaults were collected with more consistently calibrated WIM 

equipment. The better calibration of the WIM scales used to collect the SPS TPF data means that 

fewer very light loads (caused by under-calibrated scales “observing” very light loads) and fewer 

very heavy loads (caused by over-calibrated scales “observing” very heavy loads) are contained 

in the LTPP SPS TPF database. Because the SPS TPF-based NALS have smaller percentages of 

overloads, pavement life predicted using these global defaults is likely to be longer than 

predicted using the old global defaults.1

 However, these differences are not likely to be 

significant for many designs because the new global defaults also have a higher percentage of 

legally loaded heavy axles. 

 

 1 “Overload,” as used here, means axles that exceed the legal Federal limit. The axles may or may not exceed the 

legal limit for the State in question or for the load being moved. 
6 

Axle Load Spectra Defaults Representing Alternative Loading Conditions (Tier 2) 

Tier 2 defaults are supplemental defaults that represent different loading conditions (e.g., 

conditions heavier or lighter than the global default) observed in the SPS TPF study. Each of the 

Tier 2 NALS represents a different loading condition. Part II of this guide describes the 

methodology to develop these alternative NALS groups so that States can follow similar 

procedures to develop additional, State-specific, axle loading defaults for the trucks operating on 

their roads. For analysts who do not have access to State-specific NALS, national defaults are 

available. 

Analysis of the loading conditions observed in the LTPP SPS TPF study revealed that truck 

loading characteristics (axle weights) can vary considerably from location to location. Therefore, 

it was determined that default NALS should be developed that allowed users of the MEPDG and 

DARWin-ME software to select from alternative default loading conditions for their analyses to 

account for those observed differences in traffic loading per vehicle. For example, alternative 

loading conditions (Tier 2 NALS) can be required when one set of sites experiences a high 

percentage of trucks in a specific vehicle class that are fully legally loaded while another set of 

sites exhibits a high percentage of that same vehicle class that is unloaded. A third NALS might 

be needed to represent sites that experience a much higher than normal percentage of trucks 

carrying loads that exceed Federal legal limits. 

Alternative NALS also may be needed to account for differences in State truck size and weight 

laws. Differences in State laws can result in trucks of similar FHWA classifications having very 

different axle configurations and loading conditions for axles of a similar type. For example, 

many western States use flexible permitting rules to allow multi-trailer trucks to carry additional 

gross vehicle weight. These trucks are often found in FHWA Class 13. States that allow these 

additional weights have trucks with both different axle configurations and different axle weight 

patterns for FHWA Class 13 than States that do not routinely permit these kinds of loads. 

Table 1 summarizes the Tier 2 default NALS that have been developed from the SPS TPF 

datasets. The first two columns in the table allow the user to select the specific FHWA vehicle 

class and type of axle of interest. For example, FHWA vehicle Class 4, axle type 1, is the row for 

single axles on buses. On the far right of table 1 is the number of Tier 2 NALS, or different 

groups of loading patterns, that have been developed for each class of vehicle and type of axle. If 

only one NALS is present, it means that, from a pavement design perspective, little difference 

was found in the axle load spectra observed at the 26 sites in the LTPP SFS TPF data, and all 

pavement analyses can use a single NALS for that type of axle for that class of vehicles. 

The third column of table 1 indicates how frequently axles of each specific type appear on U.S. 

primary roads. This information is based on the data present in the LTPP database. This column 

is provided to give users an idea of whether specific kinds of trucks are commonly found on 

roads for which the MEPDG is likely to be used. (Note that individual roads may have truck 

volumes that are different than those commonly found in the LTPP database.) 

The fourth column in table 1 provides two pieces of information. First, it describes the NALS 

group that contains the largest number of SPS TPF sites. It is recommended that this group be 

used as the default Tier 2 NALS if no other information is available about loads carried by that 
7 

class of vehicle. If the analyst has information about loads, he or she may use that information to 

choose a different NALS for that type of axle and vehicle classification. Second, the term used in 

the fourth column of the table (e.g., Moderate or Light) describes the relative weight (or 

pavement damaging potential) of the average axle in that group relative to other axles. Table 2 

provides a quantitative definition of this descriptive loading condition, as well as full and 

abbreviated names of alternative NALS. 

As an example of how to read this fourth column of table 1, the default NALS for Class 5 single 

axles is Very Light. Thus, the average Class 5 single axle is lighter and causes much less damage 

than the average default axle for either Class 4 or Class 6 single axles. The default single axles 

for both Class 4 and Class 6 trucks are considered moderate in weight/damage potential. 

The next five columns in table 1, labeled “NALS Clusters Observed in Multiple States 

(Recommended for National Use),” describe the characteristics of the various NALS groups 

identified in the review of SPS TPF data. They use the same relative description of axle weight/ 

pavement damaging potential as is used in column 4 and in table 2. For example, the symbol 

“M” in the “Moderate” column indicates that a group of SPS TPF sites was found to have NALS 

similar to each other for that class of vehicle and type of axle, and the default NALS developed 

based on site-specific NALS included in this group is of moderate weight/damage potential. 

The next five columns, labeled “NALS Clusters in a Single State (Recommended for Use in That 

State on Roads with Similar Truck Traffic),” describe the relative weight/damage potential of the 

“special case” or outlier conditions identified in the SPS TPF dataset. Also included in these five 

columns is an abbreviated name of the State where the WIM site was located that produced the 

outlier described. For example, Class 6 single axle has two light outlier sites, one in Washington 

and one in Ohio. Possible reasons for the existence of these special-case NALS include: 

 Specific commodity hauls and State/local trucking regulations are present that cause 

unusual truck types and loads unique to that location (or State) to dominate the loading 

characteristics of a given vehicle class at the site. 

 Differences in the vehicle classification algorithm implemented on some State-installed 

SPS TPF WIM sites can cause some vehicles to be classified differently in the Statesupplied data than would be the case in the LTPP classification algorithm. These 

differences in vehicle classification outcome can cause differences in the load spectra for 

those affected classes at those sites. 

 The road containing the SPS TPF WIM site may serve commodity movements that result 

in a larger than usual percentage of trucks operating under special permits and thus have 

axles weighing more than at other sites. 

 Trucking regulations often differ from one State to another. Axle weight limits adopted 

by one State can be different from Federal limits, resulting in unusual axle weights for 

roads in that State that do not carry much interstate traffic. 

 Truck fleet characteristics can also differ from one State to another as a result of 

differences in trucking regulations. States may actively encourage specific truck 
8 

categories and actively discourage others. Consequently, States with unusual truck types 

can exhibit unusual loading conditions for the FHWA categories that contain those 

specific truck types. For example, a few western States allow triple trailer trucks. These 

trucks are classified as Class 13, and their presence generally increases the number of 

single axles found on Class 13 trucks and changes the load distribution of Class 13 single 

axles. 

The following example illustrates how to read table 1. For Class 6 tandem axles, the review of 

SPS TPF data resulted in the formation of three NALS. Two of these NALS are formed based on 

groups of sites. One of these two groups has moderate weight tandem axles. This group 

contained the greatest number of SPS TPF sites and is thus the default NALS initially 

recommended for Class 6 tandem axles. A second identified group of SPS TPF sites produced 

NALS for heavy axles. This NALS is also considered reasonably common on roads throughout 

the nation. In addition to these two fairly common groups, one SPS TPF site was an outlier. That 

site, observed in Florida, exhibited very heavy Class 6 tandem axles. This result would indicate 

that it is possible to have very heavy Class 6 tandem axles but that such a condition is considered 

unusual. This NALS should be used only if the analyst has specific knowledge that such a 

loading condition is likely to occur at the analysis site. 

NALS for each cluster group shown in table 1 are available in the LTPP PLUG database. 
9 

Table 1. Summary of NALS cluster groups representing different loading conditions by vehicle clas

FHWA 

Vehicle 

Class 

Axle 

Type 

Frequency of 

Vehicle Class 

(by Volume) on 

U.S. Primary 

Road System 

Default NALS 

Category by 

Loading Condition

NALS Clusters Observed in Multiple 

States (Recommended for National Use) 

NALS Clusters Observed in a Single State (R

Use in That State on Roads with Similar 

Very 

Light

(VL) 

Light

(L) 

Moderate

(M) 

Heavy

(H) 

Very 

Heavy 

(VH) 

Very 

Light 

(VL) Light (L) 

Moderate 

(M) Heavy (H)

4 1 Moderate Moderate M 

2 Very Heavy H VH1, VH2 

5 1 Frequent Very Light VL L (FL) 

2 Very Light VL 

6 1 Low or Moderate Moderate M 

L (WA) 

L (OH) 

2 Moderate M H 

7 

1 

Low 

Heavy M H VL (WA) M (OH) 

2 Heavy M VH VL (WA) M (OH) H (OH) 3 Very Heavy VH1, VH2 4 Very Heavy VH 

8 1 Moderate Light L H (FL) 

2 Light L L (AZ)2 

9 1 Most Frequent Light L 

2 Moderate or Heavy M H1, H2 M (FL) 

10 

1 

Low 

Light L 

2 Very Heavy M VH 3 Heavy H VH L (ME) M (MN) 4 Heavy H 

11 1 Low Moderate L M H (AZ) 12 1 Low Light L 

VL (NM) 

VL(LA) M (ME) 

2 Light L 

13 

1 

Low 

Moderate M H M (OH)2 

2 Very Heavy H VH1,VH2 3 Very Heavy H VH1,VH2 H (OH) 4 Very Heavy H VH H (OH)** 

1NALS has very heavy overloads 2NALS identified as outlier based on classification issue (high percentage of very light weight axles) 

FL = Florida, WA =Washington (State), OH = Ohio, DE = Delaware, TN = Tennessee. AZ = Arizona, ME = Maine, MN = Minnesota, 

LA = Louisiana 
10 

Table 2. Summary of axle loading categories by weight for different axle types 

Axle Category 

by Weight 

Average RPPIF 

per Cluster 

Percentage of 

Single Axles 

>= 15 kip 

Percentage of 

Tandem Axles 

>=26 kip 

Percentage of 

Tridem Axles 

>=39 kip 

Percentage of 

Quad Axles 

>=54 kip 

Very Light (VL) <0.05 <3 0 N/A N/A 

Light (L) 0.05–0.15 <10 <10 N/A N/A 

Moderate (M) 0.15–0.30 10–30 10–30 N/A N/A 

Heavy (H) 0.30–0.50 >30 30-50 <50 <30 

Very Heavy (VH) >0.50 n/a >50 >50 >30 

RPPIF = Relative Pavement Performance Impact Factor (described in Part II of this guide) 

N/A = not applicable 

NALS Clusters for Class 9 Tandems 

Although for many vehicle classes and axle types there is one clearly defined default loading 

condition for many vehicle classes and axle types (i.e., the majority of SPS TPF sites have a 

common axle loading distribution), no one loading condition dominated the Class 9 tandem data. 

The loading condition of Class 9 tandems varied among the SPS TPF sites, ranging from 

moderately loaded conditions (less than 30 percent of tandem axles were more than 26 kips) to 

very heavily loaded (up to 70 percent of tandem axles were more than 26 kips). All of these 

conditions can be found routinely on U.S. roads. 

A sensitivity analysis using the MEPDG procedures indicated that pavement design outcomes 

are very sensitive to the selection of the Class 9 tandem NALS, primarily because this is the most 

frequently observed truck carrying heavy loads on U.S. primary roads. Also, the majority of the 

load on these trucks is carried on their two sets of tandem axles. Hence, the number and weight 

of Class 9 trucks using a road typically has a major impact on pavement design. 

No one loading condition dominated the Class 9 tandem-axle NALS in the SPS TPF dataset; 

therefore, instead of one default loading condition, all three NALS cluster groups developed for 

Class 9 tandems (one moderate and two heavy) are recommended as potential defaults. 

If no site-specific loading information is available, the moderate (M) loading condition is 

recommended for roads serving predominately urban delivery trucking movements, where a 

large percentage of trucks are empty (returning to their distribution centers) or partially full after 

having made one or more stops. Alternatively, the heavy #1 (H1) loading condition is 

recommended for roads where long haul trucking or heavy directional hauls overlap with urban 

delivery movements. The heavy #2 (H2) loading condition is recommended for rural roads where 

almost all Class 9 truck traffic is fully loaded long haul traffic and few heavy trucks are expected 

to be operating in a partially full or empty condition. 

Characteristics and Recommended Use of Tier 2 NALS Clusters 

To help characterize the NALS representing default and alternative axle loading conditions so 

that pavement analysts can more easily choose between alternative loading conditions, several 

statistical parameters were computed for each Tier 2 default NALS cluster, including Relative 

Pavement Performance Impact Factor (RPPIF) values and percentage of heavy axles (i.e., the 
11 

percentage of axles that are at or above 75 percent of the Federal legal weight limit). In addition, 

text descriptions were developed of alternative NALS axle loading conditions for each vehicle 

class and axle type and recommendations for their use. This information is presented in the 

following subsections. 

Vehicle Class 4: Buses (Table 3) 

There are multiple styles of buses, ranging from over-the-road coaches (e.g., Greyhound buses), 

to two- and three-axle urban transit buses, to recreational vehicles (RV) that have been 

constructed using bus frames and bodies (e.g., tour buses used by many traveling bands). Buses 

commonly have one steering axle and either a single rear drive axle or a tandem rear axle. 

Because none of the SPS TPF WIM scales observed large numbers of urban transit buses, which 

can have very heavy single axles, a large portion of the observed single axles were steering axles. 

As a result, all of the observed sites had similar single-axle loading patterns and were grouped 

into one national NALS, with a moderate loading condition. On the other hand, three different 

tandem-axle loading conditions were identified. Tandem axles on buses are generally at least 

moderately loaded because they tend to carry the weight of the bus engine. As the number of 

passengers carried increases, the axle weight increases further, often approaching or exceeding 

the Federal axle limits. Lighter tandem axles generally are observed when the buses are lightly 

loaded with passengers, as is often the case when the “buses” are RVs rather than over-the-road 

motor coaches. Table 3 describes the alternative Class 4 axle loading conditions. 

Table 3. Description of alternative Class 4 axle loading conditions 

Vehicle 

Class 

Axle 

Type 

NALS 

Cluster RPPIF 

% 

Heavy 

Axles Description 

Recommende

d Use 

4 1 M(T) 0.20 14 

Only one national NALS exists for single axles on 

buses. It shows a relatively normal distribution of 

moderately heavily loaded axles with the majority of 

the load distribution occurring between 10,000 and 

16,000 lb. 

For use on all 

roads 

4 2 

H 0.42 46 

This NALS has a large percentage (greater than 

65 percent) of tandem axles that weigh less than 

28,000 lb and a third of the axles weighing less than 

22,000 lb. These lighter axles may be caused by the 

site observing a mix of RVs built on bus chassis 

mixed with heavier, more conventional over-theroad motor coaches. 

For use on 

roads where a 

moderate 

percentage of 

buses are “bus 

style” RVs 

VH1(T) 0.56 68 

This NALS is recommended as the default. Most of 

tandem axles are heavy (approximately 70 percent 

are greater than 26,000 lb), but relatively few (less 

than 2 percent) exceed the Federal legal limit. 

Therefore, these sites likely have a lower percentage 

of RV traffic mixed with the over-the-road coaches. 

For use on 

rural roads 

where RV 

traffic is 

modest 

VH2 0.69 85 

This NALS contains almost exclusively heavy 

tandem axles. Less than 16 percent of tandem axles 

weigh less than 26,000 lb. 

For use on 

roads carrying 

heavily loaded 

transit buses 

and over-theroad coaches 
12 

Vehicle Class 5: Two-Axle, Six-Tire Single Unit Vehicles (Table 4) 

Class 5 consists of smaller two-axle trucks. This class includes large pick-up trucks (those with 

dual wheels on their rear axle), as well as urban delivery vehicles, such as panel trucks and 

smaller tow trucks. By definition, when these vehicles pull trailers, they become Class 8 trucks. 

(This is unlike conventional Class 3 pick-ups, which remain in Class 3, even when they are 

pulling small trailers.) However, some classification algorithms do classify Class 5 trucks pulling 

trailers as Class 5. This results in some TPF sites observing tandem axles in Class 5. 

In the SPS TPF dataset, all but one condition for both single and tandem axles are grouped into 

just one NALS group for each type of axle. There is one special case. In that case, a Florida site 

was observed at which much heavier single axles were observed than at all other sites. This was 

because two-axle farm vehicles transport very heavy loads on this road (when compared with 

normal Class 5 axle loads). Table 4 describes the alternative Class 5 axle loading conditions. 

Table 4. Description of alternative Class 5 axle loading conditions 

Vehicle 

Class 

Axle 

Type 

NALS 

Cluster RPPIF 

% 

Heavy 

Axles Description Recommended Use 

5 1 

VL(T) 0.04 3 

This NALS is recommended as a Tier 2 default. 

It is appropriate for all roads that are not subject 

to unusual loading conditions. 

For use on all roads 

SP 

L(FL) 0.13 8 

This special case is caused by a permitted farmto-market haul that causes an unusually heavy 

loading condition for Class 5 trucks. It was 

found only at one Florida site. 

A special case where a 

large percentage of 

large pick-ups and 

other two-axle trucks 

carry unusually heavy 

loads for two axle 

vehicles 

5 2 VL(T) 0.00 0 

This NALS is recommended as a Tier 2 default. 

These axles are generally found on small 

trailers pulled by small trucks and are invariably 

light. 

For use on all roads 

Vehicle Class 6: Three-Axle Single Unit Vehicles (Table 5) 

Class 6 trucks are frequently smaller natural resource haulers (e.g., sand trucks, small dump 

trucks) and heavier urban delivery vehicles, such as trucks delivering cases of soft drinks. For 

these trucks, the weight on the front axle is primarily from the engine, not the load carried, and 

thus these axles are rarely either unloaded or very heavily loaded. The Class 6 classification also 

includes tractors operating without trailers. The presence of large numbers of these vehicles in 

the traffic stream can result in large numbers of lightly loaded tandem axles. Finally, many heavy 

(Class 7) single unit vehicles are equipped with “lift axles” (i.e., axles which, when not needed, 

can be lifted off the ground). Thus, trucks that are Class 7 vehicles when full (and all of their 

axles are on the ground to support the load) are often classified as Class 6 trucks when they are 

empty because only two of their load axles are touching the pavement. This often increases the 

number of lightly loaded Class 6 trucks recorded, increasing the percentage of lightly loaded 

tandem axles at many sites. Table 5 describes the alternative Class 6 axle loading conditions. 
13 

Table 5. Description of alternative Class 6 axle loading conditions 

Vehicle 

Class 

Axle 

Type 

NALS 

Cluster RPPIF 

% 

Heavy 

Axles 

Description Recommended Use 

6 1 M(T) 0.17 10 

This NALS is recommended as a Tier 2 

default. The vast majority of roads fall 

into this loading group. Most single axles 

are steering axles. The weight on the 

steering axle is primarily from the engine 

not the load carried. Few axles weighing 

more than 14,000 lb are observed. 

For use on all roads 

6 1 SP 

L(OH) 0.10 3 

The vehicle classification scheme used 

by Ohio can classify some vehicles 

pulling trailers as Class 6. These light 

trailers produce much lighter single-axle 

load spectra than are commonly found 

elsewhere, with many axles weighing 

less than 6,000 lb. 

For use on some 

Ohio roads 

6 1 SP 

L(WA) 0.08 3 

Washington’s WIM data produced load 

spectra with an unusual percentage 

(greater than 20 percent) of light axles. 

For use on 

Washington State 

roads 

6 2 M(T) 0.24 20 

This NALS is recommended as a Tier 2 

default. This NALS represents roadways 

where up to 50 percent of Class 6 trucks 

are operating empty or lightly loaded 

(approximately 40 percent of tandem 

axles weigh less than 12,000 lb, and 

approximately 50 percent of tandem 

axles weigh less than 16,000 lb). The vast 

majority of roads fall into this default 

loading group. 

For use on most 

roads, especially 

where more than 

40 percent of Class 6 

trucks are operating 

empty 

6 2 H 0.43 30 

This NALS represents roadways where 

less than 30 percent of Class 6 trucks are 

operating empty. A commensurately 

larger percentage of trucks are carrying 

full loads. This is a good NALS to select 

for roads with a strong directional haul 

that uses Class 6 trucks (e.g., a farm to 

market road where this direction is the 

loaded direction of the haul). 

For use on roads with 

strong directional 

hauls where Class 6 

trucks carry heavy 

roads 

6 2 SP 

VH(FL) 0.63 36 

Data at one Florida site showed a large 

percentage of very heavily loaded Class 6 

tandem axles. This site had 5 percent of 

its tandem-axle loads greater than 

40,000 lb, which is highly unusual for 

Class 6. 

For use on roads 

experiencing high 

overloading 

conditions with Class 

6 trucks 

Vehicle Class 7: Four-or-More Axle Single Unit Vehicles(Table 6) 

Class 7 consists of very large single unit trucks. These trucks are most commonly used for 

hauling heavy natural resources. They are often very large dump trucks. In the Midwest, they are 

often used to carry coal. The most common configuration is a single steering axle and a tridem 

axle that carries the majority of the load. Less common configurations use a quad axle instead of 

a tridem axle, or a tridem with an extended lift axle (observed as a single), or even a quintuple 
14 

axle. A larger percentage of these vehicles use lift axles. These axles are usually lowered (used to 

carry load) when the vehicle is carrying a load, and raised (so that they do not touch the 

pavement) when the vehicle is empty. As a result, relatively few empty Class 7 trucks are 

observed at scales. When empty, these trucks are most commonly configured as Class 6 vehicles. 

The use and configuration of Class 7 trucks varies considerably across the nation based on Statespecific size and weight regulations. Both the axle configurations and axle weights are quite 

variable. Class 7 trucks, along with Class 13 trucks, are possibly the most diverse categories 

within FHWA’s vehicle classification scheme. In addition, the Class 7 truck is uncommon in 

some States but quite common in others. Tandems are reasonably rare axles on Class 7 trucks. 

Only 17 of 26 sites observed enough tandems on Class 7 vehicles to construct a site-specific 

NALS. Table 6 describes the alternative Class 7 axle loading conditions. 
15 

Table 6. Description of alternative Class 7 axle loading conditions 

Vehicle 

Class 

Axle 

Type 

NALS 

Cluster RPPIF 

% 

Heavy 

Axles Description Recommended Use 

7 1 M 0.26 26 

This group of NALS contains few axles (less than 

10 percent) that weigh less than 10,000 lb. The 

majority of single axles at sites belonging to this 

group weigh between 11,000 and 18,000 lb, with 

a mean axle weight of about 13,000 lb. 

For use on roads 

where dirt and other 

heavy natural 

resources are typically 

carried by Class 10 

trucks not Class 7 

trucks 

7 1 H(T) 0.41 52 

This NALS is recommended as a Tier 2 default. 

This NALS contains few lightly loaded axles. The 

majority of single axles that fall in this group 

weigh between 13,000 and 22,000 lb, with a mean 

axle weight of about 18,000 lb. This default group 

contains axles that are slightly heavier than the 

alternative moderate (M) group. 

For use on roads 

where five-axle and 

larger Class 7 trucks 

are routinely found or 

where state laws 

routinely permit very 

heavy single unit 

trucks 

7 1 SP 

VL(WA) 0.04 4 

The Washington SPS TPF site observed a larger 

number of light single axles on Class 7 vehicles 

(approximately 70 percent weighing less than 

6,000 lb). This may be the result of a limitation in 

the Washington vehicle classification algorithm. 

For use on roads in 

Washington State 

7 1 SP 

M(OH) 0.18 18 

One of the two Ohio SPS TPF sites observed a 

larger number of light single axles on Class 7 

vehicles. (More than 40 percent weigh less than 

7,000 lb.) This may be the result of a limitation in 

the Ohio vehicle classification algorithm. The 

large percentage of light axles was somewhat 

offset by 35 percent of the axles being heavier 

than 14,000 lb. 

For use on roads in 

Ohio, where large 

percentages of nonClass 7 vehicles may 

be classified as Class 

7 trucks 

7 2 M 0.24 22 

Tandems are reasonably rare axles on Class 7 

trucks. For this NALS, more than 50 percent of 

quad axles weigh less than 12,000 lb. 

For use on roads 

serving the “light” 

direction (backhaul) 

of a directional 

natural resource haul 

7 2 VH(T) 0.85 64 

This NALS is recommended as a Tier 2 default. 

Tandems are reasonably rare axles on Class 7 

trucks. The default has a low percentage of 

tandem axles supporting little weight but also 

does not have a concentration of any specific axle 

weight. Less than 10 percent of these axles carry 

less than 12,000 lb, and while more than 40 

percent of tandem axles weigh more than 

30,000 lb, less than 15 percent weigh more than 

40,000 lb. 

For use on roads 

where Class 7 trucks 

use tandem axles and 

for directional, 

resource hauls 

7 2 SP 

H(OH) 0.41 28 

Ohio has two special-case Class 7 NALS. This 

specific special case is the heavier of the two 

special Ohio cases. It has more than 15 percent of 

axles with little or no load (weighing less than 

6,000 lb) and 35 percent of its axles weighing 

between 20,000 and 36,000 lb. 

For use in Ohio, 

where heavy loads are 

observed 
16 

Vehicle 

Class 

Axle 

Type 

NALS 

Cluster RPPIF 

% 

Heavy 

Axles Description Recommended Use 

7 2 SP 

M(OH) 0.29 16 

Ohio has two special case Class 7 NALS. This 

specific special case has 45 percent of its axles 

weighing between 16,000 and 26,000 lb. Less 

than 10 percent of axles weigh more than 

32,000 lb. More than 15 percent of axles carry 

little or no load (weighing less than 6,000 lb). 

For use in Ohio, 

where few very heavy 

loads are observed 

7 2 SP 

VH(DE) 2.42 81 

The Delaware TPF is very heavy. Very few 

unloaded axles were observed. More than half the 

tandem axles observed weigh more than 

40,000 lb. 

For use in Delaware 

7 2 SP 

VH(FL1) 3.48 100 

This Florida NALS is very heavy. Less than 

10 percent of axles weigh less than 40,000 lb. 

For use in Florida, 

and only where heavy 

overloads of Class 7 

trucks are expected 

7 2 SP 

VH(FL2) 6.11 98 

This Florida NALS is very heavy. More than 

50 percent of the observed Class 7 tandem axles 

weigh more than 48,000 lb. 

For use in Florida 

only where extreme 

overloads of Class 7 

trucks are expected 

7 2 SP 

VH(TN) 9.94 91 

This Tennessee NALS is very heavy. More than 

85 percent of the observed Class 7 tandem axles 

weigh more than 50,000 lb. 

For use on roads in 

Tennessee where 

tandem axles are 

heavily overloaded 

7 2 SP 

VL(WA) 0.03 3 

This Washington NALS is very light. More than 

60 percent of its tandem axles weigh less than 

12,000 lb. 

For use only where a 

high percentages of 

Class 7 trucks are not 

loaded 

7 3 VH1(T) 0.65 55 

This NALS is recommended as a Tier 2 default. 

The default NALS has most axles weighing 

between 30,000 and 54,000 lb. 

For use on roads 

where tridem axles 

are routinely fully 

loaded 

7 3 VH2 1.55 96 

This tridem NALS should be used where Class 7 

tridem axles are primarily loaded well over the 

Federal legal limit. The median axle weight for 

this NALS is roughly 54,000 lb. 

For use on roads 

where tridem axles 

are heavily 

overloaded 

7 3 SP 

VH(TN) 2.25 98 

This special case NALS has extremely heavy 

tridem axles. The median axle weight is just under 

60,000 lb. 

For use on roads in 

Tennessee where 

tridem axles are 

heavily overloaded 

7 4 VH(T) 0.78 31 

This NALS is recommended as a Tier 2 default. 

The SPS TPF data showed only a few sites that 

contain quad axles in Class 7. Thus, only one 

NALS is provided for quad axles. 

For use on all roads 

Vehicle Class 8: Four-or-Less Axle, Single Trailer Vehicles (Table 7) 

Class 8 consists of smaller two-unit trucks. Common configurations include two-axle tractors 

pulling a semitrailer with a tandem axle, or a three-axle tractor pulling a semitrailer with a single 

trailer axle, or a dual axle truck pulling a two-axle trailer. The trailer can consist of two single 

axles, or it can be a semitrailer with one tandem axle. These trucks tend to be lightly loaded 

because heavier tractors are needed to pull heavy loads, and the trailers pulled by most dual axle 
17 

trucks tend to be light-duty configurations. Table 7 describes the alternative Class 8 axle loading 

conditions. 

Table 7. Description of alternative Class 8 axle loading conditions 

Vehicle 

Class 

Axle 

Type 

NALS 

Cluster RPPIF 

% 

Heavy 

Axles Description Recommended Use 

8 1 L (T) 0.11 9 

This NALS is recommended as a Tier 2 default. The 

SPS TPF data found only one group NALS and one 

outlier for Class 8 single axles. This NALS is 

dominated by loads associated with the steering axle 

weight of two- and three-axle tractors, with the vast 

majority of single-axle weights in the range of 

8,000 to 14,000 lb. Generally, less than 20 percent of 

axles are heavier than 13,000 lb. 

For use on all roads 

8 1 SP 

H (FL) 0.34 31 

One Florida site had a very different NALS for Class 

8 single axles. It showed more than 25 percent of 

single axles weighing more than 17,000 lb. 

For use on Florida 

roads serving farms 

where overloaded 

axles are common 

8 2 L (T) 0.10 5 

This NALS is recommended as a Tier 2 default. The 

default NALS has the vast majority of Class 8 

tandem axles weighing less than 24,000 lb, and 

almost no illegal tandem axles. 

For use on all roads 

8 2 SP 

L (AZ) 0.09 6 

One special case was observed in Arizona. This site 

had more than 40 percent of tandem axles weighing 

less than 6,000 lb. The rest of the distribution 

resembled the typical NALS. 

For use on roads in 

Arizona where a 

high percentage of 

unloaded axles is 

common 

8 2 

SP 

VH 

(FL) 

1.09 56 

The Florida special case captured a farm-to-market 

movement where trucks pulling tandem-axle trailers 

were very heavily loaded. More than 50 percent of 

tandem axles weighed more than 34,000 lb. 

For use on Florida 

roads serving farms 

where overloaded 

axles are common 

Vehicle Class 9: Five-Axle, Single Trailer Vehicles (Table 8) 

Class 9 is by far the most common truck in use in the United States and, as such, dominates the 

vast majority of pavement loading computations. Although a number of configurations can be 

found, the most common Class 9 truck is the “classic” three-axle tractor pulling a tandem-axle 

equipped semitrailer. Infrequently, the semitrailer can use “split tandems,” which, depending on 

the distance between those axles, can be classified as either two single axles or one tandem. In 

addition, the common European configuration of a two-axle tractor pulling a tridem-equipped 

semitrailer can be observed occasionally in the United States. Finally, some full trucks pulling 

full trailers are correctly classified as Class 9 trucks. 

Because so many Class 9 trucks have single-tandem, tandem-axle configurations, the axle 

weights for single axles are dominated by the steering axle weight of the truck tractor. Because 

the steering axle on even a fully loaded truck does not approach the legal load limit for single 

axles, the axle damaging characteristics of the single axles at all of the SPS TPF sites are similar. 

Thus, only a single-axle NALS group exists. 
18 

Unlike the single axles, considerable variety exists in the tandem-axle loads carried by Class 9 

trucks. This variety is driven in part by the wide variety of loads carried by these trucks, as well 

as by their use in both urban delivery modes (where some trailers are full, some are partially full 

after completing one of several deliveries, and others are empty as the trucks return to their 

terminals after completing a delivery) and long haul transport (where the vast majority of trucks 

are fully loaded). But even in long haul travel, a “fully loaded” truck may not approach the legal 

limit because many commodities (e.g., computer parts) are bulky but not heavy. 

Consequently, three different loading conditions are considered “typical” or commonly found. 

Any one of them can be found in any U.S. State. These three loading conditions differ primarily 

in the percentage of heavy (fully loaded) axles that were observed. When selecting from among 

these three conditions, the primary consideration is the percentage of tandem axles that are 

lightly loaded (weigh less than 20,000 lb) and the percentage that are heavily loaded (weigh 

more than 30,000 lb). Table 8 describes the alternative Class 9 axle loading conditions. 

Table 8. Description of alternative Class 9 axle loading conditions 

Vehicle 

Class 

Axle 

Type 

NALS 

Cluster RPPIF 

% 

Heavy 

Axles Description Recommended Use

9 1 L(T) 0.14 9 

This NALS is recommended as the Tier 2 default. 

Only one Class 9 single-axle NALS was observed 

because the majority of Class 9 trucks have only one 

single axle (the steering axle) and its load is only 

modestly affected by the load carried by the truck. 

All roads 

9 2 M 0.30 31 

This NALS represents the loading condition 

frequently observed at SPS TPF sites. This loading 

condition has more lightly loaded tandem axles 

(axles between 12,000 and 16,000 lb) than heavily 

loaded axles (30,000 and 34,000 lb). In this NALS, 

40 percent of axles carry loads greater than 

20,000 lb. 

For use in urban 

areas and on other 

roads where 70 

percent or more of 

trucks are not fully 

loaded 

9 2 H1(T) 0.38 39 

This loading condition NALS has more loaded axles 

(between 30,000 and 34,000 lb) than unloaded axles 

(between 12,000 and 16,000 lb). This is a balanced 

distribution with similar total percentages of light 

and heavy loads. In this NALS, 55 percent of axles 

carry loads greater than 20,000 lb. 

For use on 

highways that serve 

a mix of urban 

delivery and long 

haul truck 

movements 

9 2 H2 0.48 49 

This heavy loading NALS is representative of roads 

where a sizeable majority of tandem axles are 

heavily loaded. It is commonly found on rural 

highways that serve significant long haul truck 

movements. 

For use on rural 

highways that serve 

significant long 

haul truck 

movements 

9 2 SP 

M(FL) 0.27 22 

This NALS contains very few loaded axles with no 

defined loaded peak of distribution. It also does not 

have a high concentration of axle weights near the 

conventional unloaded axle weights of 10,000 to 

16,000 lb. 

For use on roads in 

Florida with little 

long haul or 

“through 

movement” traffic 

9 2 SP 

VH(AZ) 0.68 70 

This NALS is a special very heavy case that contains 

70 percent of axles with weights greater than 

26,000 lb. 

For use on roads 

with almost all 

tandem axles fully 

loaded 
19 

Vehicle Class 10: Six-or-More Axle, Single Trailer Vehicles (Table 9) 

Class 10 consists of a variety of heavy truck configurations. These trucks have two basic styles: a 

three-axle tractor pulling a semitrailer with three or more axles, and large trucks pulling full 

trailers. The first configuration is commonly used by trucks carrying, for example, heavy 

shipping containers. The second configuration is common in States that allow longer trucking 

configurations. For example, in many western States, the most common truck for delivering 

gasoline to gas stations is a four-axle tank truck pulling a three- or four-axle tank trailer. In some 

States, Class 10 trucks are also the primary vehicles used for hauling heavy natural resources. In 

these instances, a common Class 10 vehicle is a four-axle dump truck pulling a large three- or 

four-axle “pup trailer” on a long steel beam. In some States, the primary resource haulers are 

Class 7 trucks, whereas in other States, this job is mostly performed by Class 10 vehicles. 

Generally, a State uses one or the other of these truck styles for this task. Thus, a State that 

commonly uses Class 10 trucks for natural resource hauling will tend to have few very large 

Class 7 trucks, and vice versa. Table 9 describes the alternative Class 10 axle loading conditions. 

 
20 

Table 9. Description of alternative Class 10 axle loading conditions 

Vehicle 

Class 

Axle 

Type 

NALS 

Cluster RPPIF 

% 

Heavy 

Axles Description Recommended Use 

10 1 L(T) 0.12 4 

Only one NALS was observed because single 

axles are mostly used on Class 10 vehicles as the 

steering axle of the tractor. Thus, single-axle 

loads are driven by common steering axle 

loading patterns. 

For use on all roads 

10 2 M 0.18 15 

This NALS pattern for tandems is dominated by 

unloaded axles. In this NALS, more than 

80 percent of tandem axles weigh less than 

20,000 lb. 

For use on roads where 

the Class 10 trucks are 

primarily unloaded 

10 2 VH(T) 0.52 45 

This NALS is recommended as a Tier 2 default. 

It has slightly more loaded axles (weighing 

26,000 to 34,000 lb) than unloaded or lightly 

axles (12,000 to 20,000 lb). It also includes 

about 5 percent of axles exceeding the Federal 

legal limit. 

For use on roads with an 

even mix of heavy and 

light Class 10 trucks 

10 2 SP 

VH(AZ) 1.04 38 

This special case NALS did not fit either pattern. 

Although it has more unloaded axles than the 

default NALS, it also has more than 12 percent 

of its axles weighing more than the Federal legal 

limit, which results in the very heavy loading 

condition. 

For use on roads with 

high levels of 

overloaded Class 10 

tandem axles 

10 3 H(T) 0.35 23 

This NALS is recommended as a Tier 2 default. 

It contains a significant number of both loaded 

and unloaded tridem axles. More than 40 percent 

of axles weigh less than 21,000 lb. However, 

more than 30 percent of the axles weigh between 

33,000 and 48,000 lb. 

For use on roads with a 

mix of fully and lightly 

loaded Class 10 tridem 

axles 

10 3 VH 0.56 43 

This alternative to the default NALS has a lower 

percentage of lightly loaded axles, and a much 

greater percentage of heavy axles. Less than 

22 percent of axles weigh less than 21,000 lb, 

and more than 50 percent of axles are heavier 

than 36,000 lb, with more than 10 percent 

heavier than 48,000 lb. 

For use on roads with a 

mix of loaded and 

unloaded tridem axles, 

where a significant 

portion of the axles 

exceed the Federal 

weight limit 

10 3 SP 

L(ME) 0.09 5 

This special case is for a Maine site that has a 

very high percentage of light axles, and a low 

weight for loaded axles. Almost 75 percent of 

axles weigh less than 15,000 lb, and less than 

5 percent of axles weigh more than 39,000 lb. 

For use on Maine roads 

where almost all tridem 

axles are unloaded or 

lightly loaded 

10 3 SP 

M(MN) 0.18 9 

This special case in Minnesota also reflects a 

very high percentage of lightly loaded axles, but 

with a larger percentage of heavy axles. Fifty-six 

percent of axles weigh less than 15,000 lb, with 

another 25 percent of axles weighing between 

27,000 and 48,000 lb. 

For use on Minnesota 

roads with a high 

percentage of unloaded 

tridem axles 

10 4 H(T) 0.46 7 

This NALS is recommended as a Tier 2 default. 

It contains both a significant number of loaded 

and unloaded quad axles but less than 5 percent 

of axles weigh more than 57,000 lb. 

For use on roads with a 

mix of heavy and lightly 

loaded Class 10 quad 

axles 
21 

Vehicle Class 11: Five-or-Less Axle, Multi-Trailer Vehicles (Table 10) 

Class 11 trucks are multi-trailer trucks mostly intended for carrying light, bulky cargo. For 

example, they are good choices for carrying large quantities of mixed packages and other light 

but high-volume cargo. The vast majority of trucks in this classification consist of a two-axle 

tractor pulling a smaller (28-ft) single-axle semitrailer and a small two-axle trailer. Because the 

drive axle of the tractor and the load-bearing axles on the trailers are all single axles, this 

configuration is one of the heavy truck configurations for which changes in truck loading 

characteristics (i.e., the commodities being hauled and whether the truck is loaded or not) have a 

significant effect on the single-axle loading pattern observed for single axles. Consequently, 

three different single-axle NALS patterns were developed for this class of trucks. Table 10 

describes the alternative Class 11 axle loading conditions. 

Table 10. Description of alternative Class 11 axle loading conditions 

Vehicle 

Class 

Axle 

Type 

NALS 

Cluster RPPIF 

% 

Heavy

Axles Description Recommended Use 

11 1 M(T) 0.19 18 

This NALS is recommended as a Tier 2 default. 

The default NALS has relatively few very light 

axles. Less than 15 percent of axles weigh less 

than 8,000 lb. It differs from the primary 

alternative NALS group in that 35 percent of the 

axles in this group weigh more than 14,000 lb. 

For use on all roads 

11 1 L 0.08 5 

This alternative NALS is lighter than the default. 

Only 10 percent of axles in this group are heavier 

than 14,000 lb, while 35 percent are lighter than 

8,000 lb. 

For use when a high 

percentage of Class 11 

trucks are running 

empty 

11 1 SP 

H(AZ) 0.38 53 

This special case represents a very heavy loading 

condition observed in Arizona. Two peaks are 

observed in the load spectra, one represents the 

steering axles of these trucks with weights near 

10,000 lb, and the other represents the loaded 

single axles with weights ranging between 

16,000 and 22,000 lb. More than 45 percent of all 

axles weigh more than 16,000 lb. 

For use when nearly all 

Class 10 trucks are 

fully loaded, such as 

roads used exclusively 

by long haul trucks, 

observed in Arizona 

Vehicle Class 12: Six-Axle, Multi-Trailer Vehicles (Table 11) 

Class 12 trucks are long multi-trailer trucks. They typically have one set of tandem axles and 

four single axles, one of which is the steering axle. The most common Class 12 truck 

configuration is a three-axle tractor pulling a single-axle semitrailer and a full trailer with two 

single axles. Less common configurations include a two-axle tractor pulling either a two-axle 

semitrailer and two-axle full trailer, or a two-axle tractor pulling a single-axle semitrailer and a 

three-axle full trailer. These vehicles carry a wide variety of commodities and can exhibit a 

variety of loading conditions. One NALS group was identified for single axles, but three specialcase outliers were also noted in the SPS TPF dataset. Only one tandem-axle NALS group was 

identified. Table 11 describes the alternative Class 12 axle loading conditions. 
22 

Table 11. Description of alternative Class 12 axle loading conditions 

Vehicle 

Class 

Axle 

Type 

NALS 

Cluster RPPIF 

% 

Heavy 

Axles Description Recommended Use 

12 1 M(T) 0.12 7 

This NALS is recommended as a Tier 2 default. 

The default NALS for Class 12 single axles has an 

almost normal distribution. There are very few very 

light axles (weights less than 6,000 lb), and very 

few heavy axles (weights greater than 18,000 lb). 

The majority of axles weigh between 10,000 and 

16,000 lb. 

For use on all roads 

12 1 SP 

M(ME) 0.25 25 

This special case differs from the default NALS 

because more than 20 percent of its axles are 

heavier than 16,000 lb, compared with 5 percent in 

the default NALS. It represents a site where Class 

12 trucks are carrying heavier loads than typically 

found elsewhere in the country. 

For use on all roads 

where at least 20 

percent of Class 12 

trucks are carrying 

heavy commodity 

loads 

12 1 SP VL 

(LA) 0.04 3 

This special case represents a very light loading 

condition. Two peaks are present in the loading 

spectra; the larger peak represents unloaded single 

axles, weighing about 7,000 to 8,000 lb. The 

smaller peak represents the steering axle of the 

tractor, weighing about 10,000 to 12,000 lb. 

For use on roads 

where almost all 

Class 12 trucks are 

operating empty 

12 1 SP VL 

(NM) 0.03 1 

This special case from New Mexico represents a 

very light axle loading condition. Less than 4 

percent of axles weigh more than 12,000 lb. The 

light single axles in this NALS form a single-peak 

distribution between 7,000 and 11,000 lb rather 

than having two peaks. 

For use on roads in 

New Mexico, where 

almost all Class 12 

trucks are observed 

to be operating 

empty 

12 2 L(T) 0.14 2 

This NALS is recommended as a Tier 2 default. 

Only one NALS was observed for Class 12 tandem 

axles. 

For use on all roads 

Vehicle Class 13: Seven-or-More Axle, Multi-Trailer Vehicles (Table 12) 

Class 13 is the classification that contains multi-trailer trucks specifically designed for carrying 

heavy loads. This classification of vehicles contains a wide variety of both truck configurations 

and axle configurations. They are common in some States but fairly rare in others. In Canada, 

one specific configuration (the “Canadian B Train”) was designed to meet Canada’s long haul 

trucking needs. In return for specific safety improvements (the use of a “B-style” connection 

between the first and second trailer) and the use of a tridem axle supporting the back of the first 

trailer and front of the second trailer, the Canadian B Train is permitted to carry additional load 

and therefore is extremely common in Canada and is also found in many northern States. 

In addition, the adjustment of many State-specific truck size and weight laws to meet the needs 

of local heavy industry has resulted in classification of State-specific truck configurations as 

Class 13. For example, some western States have allowed the use of triple-trailer trucks. The 

result is considerable diversity in the number and weight of different types of axles on Class 13 

trucks. Table 12 describes the alternative Class 13 axle loading conditions. 
23 

Table 12. Description of alternative Class 13 axle loading conditions 

Vehicle 

Class 

Axle 

Type 

NALS 

Cluster RPPIF 

% 

Heavy

Axles Description Recommended Use 

13 1 M(T) 0.18 11 

This NALS is recommended as a Tier 2 default. The 

default NALS for Class 13 single axles has the 

rough shape of a triangle with the peak between 

12,000 and 13,000 lb. This default NALS has very 

few unloaded and very few heavily loaded single 

axles. 

For use on all roads, 

especially where 

fewer Class 13 

trucks use single 

axles to carry heavy 

trailer loads 

13 1 H 0.32 29 

This alternative NALS is similar to the default 

distribution, but has fewer lightly loaded axles 

(fewer axles between 9,000 and 12,000 lb) and more 

axles greater than 15,000 lb. This NALS has 

30 percent of axles exceeding 16,000 lb with more 

than 10 percent exceeding 18,000 lb. 

For use on all roads 

where single axles 

on Class 13 trailers 

are routinely 

carrying heavy loads 

13 1 SP 

M(OH) 0.21 21 

This special case comes from Ohio. It differs from 

the default in three areas. First, it has a very high 

percentage of very light single axles (more than 

35 percent weigh less than 5,000 lb). Second, it has 

almost 20 percent of loads weighing more than 

17,000 lb compared with less than 9 percent for the 

default, and third, it has more than 7 percent of axles 

weighing more than the Federal legal limit. 

For use in Ohio, 

where both 

classification issues 

place many very 

light axles in Class 

13, and where a high 

percentage of 

overloads are 

observed on Class 13 

trucks 

13 1 SP 

VH(OH) 0.55 48 

This special case comes from Ohio. This NALS has 

a high percentage of heavy and overloaded axles. 

More than 20 percent of axles in this NALS exceed 

18,000 lb. 

For use in Ohio, 

where many single 

axles exceed the 

Federal legal limit 

13 2 VH1(T) 0.87 54 

This NALS is recommended as a Tier 2 default. The 

default NALS has very few light axles. There are 

two peaks in the axle load distribution. One centers 

on 22,000 to 24,000 lb and the other centers on 

34,000 to 36,000 lb. Roughly 25 percent of tandem 

axles exceed the Federal legal limit of 34,000 lb. 

For use on all roads, 

with a balance of 

moderate and 

heavily loaded axles 

13 2 H 0.49 37 

This alternative NALS has axles that are not as 

heavy as found in the default NALS. In this loading 

pattern, about 17 percent of axles weigh less than 

12,000 lb. Only 12 percent of the observed axles 

exceed the Federal legal limit. 

For use on roads 

where the majority 

of Class 13 trucks 

are not fully loaded 

13 2 VH2 1.46 58 

This alternative NALS differs from the default 

primarily in that it has a much higher percentage of 

very heavy axles. More than 40 percent of all axles 

observed exceed the 34,000 lb Federal limit. 

For use on roads 

where loads Class 13 

loads routinely 

exceed the Federal 

limits 

13 3 VH1(T) 1.12 76 

This NALS is recommended as a Tier 2 default. The 

default NALS contains very few light tridem axles. 

Fifty percent of the axles in this NALS exceed 

48,000 lb. 

For use on roads 

where a large 

percentage of Class 

13 tridem axles are 

very heavily loaded 
24 

Vehicle 

Class 

Axle 

Type 

NALS 

Cluster RPPIF 

% 

Heavy

Axles Description Recommended Use 

13 3 H 0.47 28 

This alternative NALS is lighter than the default 

NALS but it still represents a reasonably heavy 

loading condition. Twenty percent of the axles are 

lightly loaded (weigh less than 21,000 lb). The peak 

of the loaded distribution is between 36,000 and 

39,000 lb. Only 5 percent of axles exceed 48,000 lb. 

For use on all roads 

where most tridem 

axles are fully loaded 

but where overloads 

are not routine 

13 3 VH2 1.76 86 

This alternative NALS is even heavier than the 

default NALS. It contains very few lightly loaded 

tridem axles. More than 60 percent of the observed 

axles exceed 48,000 lb. 

For use on roads 

where overloaded 

tridem axles are very 

common 

13 3 SP 

H(OH1) 0.44 24 

This special case from Ohio has a very large 

percentage of very light axles (24 percent weighing 

less than 15,000 lb). Another 36 percent weigh less 

than 36,000 lb. However, the NALS also has 

11 percent of axles weighing more than 50,000 lb, 

and 1 percent of axles that weigh more than 

70,000 lb. 

For use only on 

roads in Ohio, where 

some tridem axles 

exceed 70,000 lb 

13 3 SP 

H(OH2) 0.50 31 

This special case is also from Ohio. It has a large 

percentage of light axles. Only 6 percent are lighter 

than 15,000 lb, but 20 percent are less than 

18,000 lb. Seventy percent of these axles are heavier 

than 30,000 lb, but only 18 percent exceed 

42,000 lb. 

For use only in Ohio, 

on roads where few 

tridem axles exceed 

57,000 lb 

13 4 VH(T) 0.83 39 

This NALS is recommended as a Tier 2 default. The 

default NALS for Class 13 quad axles is reasonably 

flat with no loads in the range between 12,000 and 

72,000 lb having less than 2.5 percent of the axles or 

more than 9 percent of the axles. A small peak exists 

between 18,000 and 21,000 lb, and a second small 

peak occurs between 60,000 and 63,000 lb. Thirtyfive percent of axles weigh more than 57,000 lb. 

For use on all roads 

where Class 13 quad 

axles are routinely 

very heavy 

13 4 H 0.43 14 

This alternative NALS is lighter than the default 

NALS, but it is still fairly heavy. It contains a higher 

percentage of lighter quad axles (a peak value near 

12 percent) and many fewer very heavy axles (less 

than 12 percent of axles weigh more than 57,000 lb). 

For use on all roads 

where only a modest 

percentage of quad 

axles are very 

heavily loaded 

13 4 SP 

H(OH) 0.46 21 

The special case site in Ohio has a very large 

fraction (43 percent) of very light axles. These very 

light axles are offset by the fact that 16 percent of 

axles weigh more than 69,000 lb. 

For use only in Ohio, 

where vehicles with 

very light quad axles 

are being observed 
25 

Description of APC Defaults 

APC defaults were computed for each vehicle class and axle type based on data from the 26 SPS 

TPF sites. Averaging the APC values computed for all SPS TPF sites resulted in one set of 

global default values, shown in table 13. 

Table 13. Global default APC based on 26 SPS TPF sites 

Vehicle 

Class Single Tandem Tridem Quad 

4 1.43 0.57 0.00 0.00 

5 2.16 0.02 0.00 0.00 

6 1.02 0.99 0.00 0.00 

7 1.26 0.20 0.63 0.15 

8 2.62 0.49 0.00 0.00 

9 1.27 1.86 0.00 0.00 

10 1.09 1.15 0.79 0.05 

11 4.99 0.00 0.00 0.00 

12 3.99 1.00 0.00 0.00 

13 1.59 1.26 0.69 0.31 

The APC global defaults computed from the LTPP SPS TPF data were compared with the 

defaults developed in the NCHRP1-37A study.(4) Although some differences were found 

(especially in classes 11 and 13), these differences were relatively small. The small changes do 

not result in any significant difference in the required layer thickness or predicted distress for 

either flexible or rigid pavements. If States have State-specific APC statistics, these should be 

used in place of the global defaults; otherwise, the global defaults are the best available statistics 

for use in the MEPDG and DARWin-ME software. 

Description of Wheelbase and Axle Spacing Defaults 

SPS TPF data were used to investigate the distribution of axle spacing (wheelbase) of the tractor 

unit of tractor-semitrailer combination trucks for FHWA vehicle classes 8 and above. These 

statistics can be used to define the categories of “short,” “medium,” and “long” axle spacing that 

are used in the analysis of jointed plain concrete pavement (JPCP) slab cracking. 

Because 15 ft is the most frequently used joint spacing for JPCP design, the following 

percentages of axles in the short, medium, and long categories should be used as defaults in the 

MEPDG and DARWin-ME software for 15-ft joint spacing: 

 Short (<= 12 ft): 4.3 percent. 

 Medium (>12 and <=15 ft): 16.2 percent. 

 Long (>=15 feet): 79.5 percent. 

If a different joint spacing is used, the values presented in table 14 can be used to compute the 

correct percentage of short, medium, and long axles for that desired joint spacing. 
26 

Table 14. Distribution of axle spacing on tractor units for FHWA classes 8 through 13 

Axle Spacing (ft) 

Percentage of Axle Spacings 

on the Tractor Unit 

<=7 0.0 

>7 and <=8 0.0 

>8 and <=9 0.0 

>9 and <=10 0.1 

>10 and <=11 0.7 

>11 and <=12 3.5 

>12 and <=13 7.8 

>13 and <=14 5.4 

>14 and <=15 3.0 

>15 and <=16 8.1 

>16 and <=17 12.9 

>17 and <=18 32.9 

>18 and <=19 9.8 

>19 and <=20 7.3 

>20 and <=21 6.9 

>21 and <=22 0.9 

>22 and <=23 0.3 

>23 and <=24 0.2 

>24 0.2 

In addition, the MEPDG states that if other vehicles in the traffic stream have the axle spacings 

in the range of the short, medium, and long spacings defined above, the frequency of those 

vehicles could be added to the axle spacing distribution of truck tractors. For example, if 

10 percent of truck traffic is multiple trailers (Class 11 and above) that have the trailer-to-trailer 

axle spacings in the “short” range, 10 percent should be added to the percentage of truck tractors 

that have “short” axles. Thus, the sum of the percentages of trucks in the short, medium, and 

long categories will be greater than 100. Table 15 shows the results of the analysis of the axle 

spacing distribution for units other than tractors for vehicle classes 4 through 13 based on the 

SPS TPF data. These results provide additional insights regarding the vehicle classes that are 

likely to have axle spacings that could contribute to the development of top-down cracking in 

JPCP. 
27 

Table 15. Distribution of axle spacing by vehicle class using sample of SPS TPF WIM data 

Axle Spacing 

(ft) 

Percentage of Axle Spacing by Class 

Class 4 Class 5 Class 6 Class 7 Class 8 Class 9 Class 10 Class 11 Class 12 Class 13

<=8 37 13 49 66 25 47 62 0 20 50 

>8 and <=9 0 1 0 0 3 0 0 2 6 4 

>9 and <=10 0 1 0 1 1 0 1 17 11 5 

>10 and <=11 0 2 0 3 1 3 1 3 3 3 

>11 and <=12 0 12 1 11 2 1 1 2 5 3 

>12 and <=13 0 7 2 9 8 1 2 12 2 3 

>13 and <=14 0 21 3 3 8 1 2 7 0 2 

>14 and <=15 0 12 3 2 4 1 1 2 0 2 

>15 and <=16 0 4 6 1 2 2 2 2 2 3 

>16 and <=17 0 3 6 0 2 4 2 2 3 3 

>17 and <=18 0 4 9 0 4 9 3 4 6 3 

>18 and <=19 0 3 6 1 4 3 4 2 2 5 

>19 and <=20 0 3 5 0 4 2 2 1 5 4 

>20 and <=21 0 4 6 0 6 2 1 6 13 2 

>21 and <=22 0 5 2 0 5 0 1 24 8 2 

>22 and <=23 1 3 1 0 3 0 0 15 12 1 

>23 and <=24 20 1 0 0 1 0 0 1 1 1 

>24 42 2 0 0 16 25 15 0 0 5 

Description of Default Axle Spacings for Multi-Axle Groups 

SPS TPF axle spacing data were used to compute the average axle spacing for tandem, tridem, 

and quad axle groups. These averages were then compared with current MEPDG defaults. The 

results are presented in table 16. 

Table 16. Average axle spacing for multi-axle groups 

Source 

Axle Spacing (inches) 

Tandem Tridem Quad 

NCHRP 1-37A 51.6 49.2 49.2 

LTPP SPS TPF 49.0 50.8 51.8 

As table 16 shows, the values are very close. SPS TPF-based averages are slightly lower for 

tandem axles and higher for tridem and quad axles compared with the current MEPDG default 

values. 

The values based on SPS TPF WIM sites reported in table 16 are recommended for use as the 

new MEPDG defaults because these values are obtained from accurately calibrated WIM sites. 

GUIDELINES FOR SELECTING AXLE LOAD SPECTRA FOR THE MEPDG 

Knowledge of Local Traffic Loading Conditions 

Before an analyst chooses among the alternative NALS defaults, it is recommended that every 

effort be made to understand the expected traffic-loading pattern at the site for which default 
28 

NALS selections are being made. For example, analysts who work at a State department of 

transportation can talk to the staff in the department’s freight office, individuals involved in 

collecting truck data, and individuals in the department’s maintenance office who actively work 

on that roadway. Another source of commodity information is Metropolitan Planning 

Organizations (MPO). Personnel from these agencies often can provide a reasonable description 

of the truck traffic using a specific road that can be used to identify the most appropriate NALS 

tables to apply. Topics to discuss include the following: 

 Dominant commodities carried by trucks and the types of trucks used. 

 Presence of specific directional hauls that may cause one direction of a roadway to be 

loaded heavily and the other to be lightly loaded. 

 Routine axle weight of tridem and quad axles of classs 7, 10, and 13 trucks in the State. 

 Percentage of through trucks versus local delivery trucks. 

 Truck sizes and weight laws of different States (which can result in different truck body/ 

configurations for the same FHWA truck class). 

 Presence and effectiveness of weight enforcement activities. 

 Number of roadway lanes. 

This information should be used to establish a descriptive understanding of the traffic loading 

conditions for at least the dominant heavy vehicle classes observed at the site (“dominant” is 

defined at the end of this subsection). The intent is to learn whether the trucks producing the 

majority of traffic load at this site are loaded, unloaded, or an even mix of these two conditions. 

This will help determine whether they are of “typical” or usual” weight, or whether they are 

heavier or lighter than typical, which in turn helps the analyst choose between the Tier 2 default 

NALS options. Table 3 through table 12 can help the analyst select specific Tier 2 default NALS 

based on this information. The guidance from these tables is also built into the LTPP PLUG 

Interactive Traffic Library Database. In addition to defaults created using SPS TPF data, State 

agencies may choose to put their own default NALS into the PLUG Library Database, including 

their own information for tables 3 through 12. 

Determination of the Dominant Truck Classes 

In the selection of NALS defaults, the most care should be applied in selecting the appropriate 

default for the dominant truck class. The dominant trucks for a given site are those that apply the 

largest percentage of the total traffic load at that site. (That is, the truck classes that are expected 

to cause a large amount of the expected pavement damage.) “Dominant” is a function of both the 

volume of a class of trucks and the expected pavement damage each truck causes. Dominant 

trucks generally are heavy trucks, and they generally contribute a high percentage of the total 

truck volume. 
29 

The LTPP PLUG software provides several methods to determine dominant truck classes. One 

such method is described below. Table 17 demonstrates how to estimate the percentage of total 

load (or load-related damage) carried by each truck class for determining the most dominant 

truck classes at a site. This table uses RPPIF per truck values as a simplified measure of the 

expected amount of damage caused by each truck. It is not meant to be used for direct damage or 

distress prediction but rather to rate the relative importance of loads from the perspective of their 

potential to cause damage to the pavement. These values are shown in the third column of the 

table. Analysts may replace the values in this column with their own statistics for “damage per 

truck.” For example, they can insert conventional ESAL/truck values. 

Table 17 is an example of how to compute dominant trick classes. To use a table like table 17, 

determine the percentage of truck traffic for FHWA vehicles in classes 4 through 13 that uses the 

pavement sections being analyzed. Place these values in the second column of the table. Multiply 

the value in the second column by the value in the third column and place this value in the fourth 

column. This is a measure of the relative damage each class of trucks will apply at this site. In 

the fifth column, convert the value in the fourth column to a percentage of that total traffic load 

by dividing each value in the fourth column by the total of the fourth column. The “dominant 

truck class” is the class of trucks that has the highest percentage of the estimated load. In the 

example shown in table 17, Class 9 is the dominant truck class because no other class of trucks 

produces more than 12 percent of the total estimated load. All classes that provide more than 

25 percent of the traffic load should be considered dominant classes. 

To use a table like table 17 effectively, and to perform a good pavement analysis, the analyst 

should have access to site-specific truck volume data. These data can be collected at almost any 

pavement analysis section in the United States at a cost that is small relative to their importance 

in the pavement analysis process. (The vast majority of LTPP test sections have valid, accurate 

vehicle classification count data.) 

Table 17. Example of computing dominant truck classes 

Vehicle Class 

Percentage of 

Truck Traffic RPPIF/Truck 

Load Applied by 

Truck Class 

(Percentage of 

Truck Traffic times 

RPPIF/Truck) 

Percentage of Total 

Load Applied by 

Class 

4 5 0.60 0.0302 5.9 

5 40 0.08 0.0317 6.2 

6 6 0.50 0.0303 5.9 

7 2 0.53 0.0107 2.1 

8 4 0.34 0.0138 2.7 

9 36 0.93 0.3339 65.2 

10 1 0.53 0.0053 1.0 

11 3 0.67 0.0200 3.9 

12 1 0.46 0.0046 0.9 

13 2 1.58 0.0316 6.2 

Applying What the Analyst Has Learned About Truck Loads 

The questions that the analyst asks those in the traffic data collection, freight mobility, and 

maintenance groups are intended to give him or her an understanding of where unloaded, loaded, 
30 

and over-loaded trucks are operating. Because different kinds of trucks carry different kinds of 

commodities, loaded, unloaded, and overloaded conditions may vary considerably among types 

of trucks on a single road. For example, on one road, long haul Class 9 tractor-semitrailers may 

be operating fully loaded, but rarely overloaded, because they routinely pass port of entry 

enforcement stations at the State borders. At the same time, natural resource haulers on that same 

road may frequently be operating in an overloaded condition because their trips are a shorter 

distance and that distance does not include passing a weight enforcement site. 

Insight into the commodities carried on the road helps determine whether loaded trucks are 

expected to be near the Federal legal limit. Some commodities, such as general household goods 

or computer parts, tend to be light. These goods “fill up” a truck or container (bulk out), but the 

“full” truck’s axles do not reach the Federal legal limit. (For example, most consumer packages 

have large amounts of packaging to protect the contents. This makes the packages large but 

relatively light, filling up the trailer box but not heavily loading the truck’s axles.) Other 

commodities can be quite heavy. For example, frozen food shipped from eastern Washington to 

the Port of Seattle in containers are very heavy loads. Little packaging is needed and the foods 

are tightly packed, resulting in very dense containers, and thus heavy axle loads. 

If it is known that the pavement analysis section is on a road that carries heavy natural resource 

loads—and this direction of traffic is the direction that carries the loaded natural resource 

trucks—then the analyst should select a heavy NALS for the class of trucks used to carry heavy 

natural resources in that State. If, on the other hand, the side of the road that contains the analysis 

segment carries the unloaded trucks returning to pick up more natural resources, the analyst 

should select one of the lighter Class 6 or Class 10 NALS and a moderate Class 7 and/or 

Class 10 NALS. 

Another key question for the analyst to learn about natural resource hauls is what kind of trucks 

most commonly carry natural resources on that road and what kinds of axle loads are present. In 

some parts of the country, Class 7 is the primary natural resource hauler. In other parts of the 

country, Class 10 trucks fulfill this role. In either case, it is also important to understand the 

common axle weights that these trucks exhibit when loaded. In some parts of the country, these 

trucks are renowned for having overloaded axles. In other parts of the country, these loads are 

maintained near the legal limits owing to tight enforcement and specific truck size and weight 

regulations. The Tier 2 NALS provide a number of different loading conditions for these trucks 

and discussing likely loading conditions for them with knowledgeable State traffic data 

personnel increases the accuracy of the NALS selected for these trucks and axle types. 

Most trucks hauling natural resources do not travel very long distances. (Natural resources are 

generally shipped by rail for long distance hauls.) However, many truck classes do operate in 

long haul, urban delivery, and single-day return modes of operation. These kinds of operating 

patterns affect how often a truck is observed as being loaded, partially loaded, or empty. 

Trucks that operate over very long distances (more than 1 day’s travel) tend to operate loaded 

during the vast majority of time. The longer the distances traveled, the more likely the truck is 

full (although its axles may still be well below legal Federal axle load limits if it is carrying 

bulky cargo) because the economics of trucking are such that the cost of finding a return load is 

lower than the cost of traveling a long distance empty. However, if a roundtrip can be made in 
31 

1 day, the likelihood that such the truck is full in one direction and empty in the other increases 

considerably. This is simply because the labor cost of waiting for a return load can be high 

relative to the cost of driving back to base. Similarly, in urban areas, delivery trips that start and 

end at a terminal are commonly full at the start of the trip, partially loaded during the middle of a 

trip, and empty by the end of the trip. 

When considering these operating conditions together, and looking at the loading patterns for 

truck classes 8, 9, 11, 12, and 13 (but usually not Class 10), it becomes clear why it is important 

to understand the percentage of through trips versus local delivery trips made. Each of these 

truck classes is commonly used for both local delivery and long haul trips. The greater the 

percentage of local delivery (and single-day return) movements occurring on a road, the higher 

the percentage of light axles should be in the selected NALS. On the other hand, the greater the 

percentage of through traffic, the smaller the percentage of lightly loaded axles. These conditions 

reach their extreme on roads like I-10 near the New Mexico/Arizona border. Because there are 

few local destinations in this area, almost all truck traffic on I-10 is loaded. 

Finally, the size and weight laws in place in the State, and the degree to which those laws are 

enforced on that road, are useful information for the analyst. In some cases, States routinely 

allow additional axle loads on specific styles of trucks to meet the needs of important Statespecific industries. Similarly, there are some commodity movements that are renowned for being 

overloaded (e.g., some coal movements have this reputation). When these conditions are known 

to exist, the analyst can select Tier 2 NALS that feature larger percentages of axles that exceed 

the Federal axle weight limits. 

Selection of NALS 

Once an analyst understands the basic truck volumes at a site and has obtained the available 

knowledge on the truck loading conditions, especially for the dominant truck classes, table 3 

through table 12 could be used to identify NALS best representing identified loading conditions. 

To facilitate the selection of Tier 2 NALS, information from these tables has been included in the 

LTPP PLUG database and software application. Details are provided in the appendices of this 

guide. 

For vehicle classes where no loading conditions are identified because of lack of knowledge or 

because these classes carry a low percentage of the total volume, it is recommended that analysts 

use the SPS TPF NALS defaults (either Tier 1 or Tier 2). 

MEPDG Sensitivity Test 

When NALS defaults are used, and if time and resources permit, the analyst is strongly 

encouraged to run at least some sensitivity tests of the MEPDG analysis outputs, especially if 

very limited knowledge of loading conditions exists. The minimum recommended sensitivity 

tests include two runs. Both are performed by keeping all inputs the same except the NALS. The 

first test substitutes a heavier Tier 2 NALS than the initial default NALS for the dominant trucks 

in the design. The second test substitutes a lighter Tier 2 NALS for the dominant trucks classes 

using the site. 
32 

The sensitivity test is intended to simply increase and decrease the total load applied to 

determine whether the MEPDG outputs for a particular design change significantly based on 

changing traffic load. If they do, then the analyst can decide how conservative a design to build, 

given the uncertainty in the traffic loading. 

Limitations of Loading Cluster NALS Defaults 

The Tier 1 and Tier 2 defaults are useful estimates when site-specific information is not 

available. However, because they were developed from only 26 WIM sites in 23 States, and all 

of those sites are LTPP test sites (which means they tend to be on larger roads), they are not truly 

representative of all the locations at which traffic loading estimates are needed. The small 

number of SPS TPF WIM sites also limits the geographic scope of the weight data. These 

estimates may not be representative of specific roads in specific States where loading conditions 

are dominated by State regulations or specific commodity movements that differ from national 

norms. When State- or site-specific trucking movements dominate the use of a road, those 

roadways may experience loading conditions that are different than those observed in the SPS 

TPF data. Consequently, when analysts believe that these State-specific conditions are present, 

they are encouraged to (1) work with their State to develop State-specific NALS defaults, (2) talk 

to their State’s traffic data collection personnel to gain more insight into which loading patterns 

to apply, and (3) perform sensitivity tests of the MEPDG outputs using a variety of different 

NALS. 

MEPDG TRAFFIC INPUTS BEYOND AXLE LOAD SPECTRA 

The estimation of traffic load requires a number of factors in addition to the NALS, including: 

 Truck volumes distributions for classes 4 through 13. 

 Expected rate of truck traffic growth for future pavement performance prediction (or 

back-casted traffic for analysis of historical pavement performance data). 

 Distribution of truck traffic by time of day. 

 Distribution of truck traffic by month of the year. 

 Distribution of truck traffic by lane and by direction. 

States are encouraged to develop their own defaults or site-specific values for these statistics. 

Although truck volumes will change with the national economy, State economic growth will 

likely have an even greater impact on truck traffic on most roads. Truck volume time of day 

distributions are easily collected as part of site-specific truck volume counts. Truck travel 

distributions are important in States where truck travel varies by season and are especially 

important where seasonal environmental changes significantly affect material properties. (That 

is, it is especially important to understand how truck volume patterns change during the year in 

States with significant freeze-thaw conditions.) All of these data are available to some degree in 

the LTPP traffic database, but additional information on these factors should also be available 

through State sources. 
33 

PART II—GUIDELINES FOR DEVELOPING AXLE LOADING DEFAULTS 

INTRODUCTION 

Although the SPS TPF data provide an improved set of traffic loading defaults compared with 

the original MEPDG defaults because they were collected with better calibrated WIM 

equipment, the SPS TPF data, by necessity, represent national conditions. Unfortunately, many 

truck characteristics differ markedly from State to State. Consequently, if a State operates wellcalibrated WIM scales, summarizing the data obtained from those scales can provide default 

truck characteristic data that are more accurate for designs in that State than if national defaults 

are used. Therefore, States are encouraged to develop and apply their own NALS and other truck 

characteristics when their WIM data have been carefully checked for quality assurance (QA) and 

found to be accurate. 

Analysis of WIM data from the LTPP program indicates that axle loading distributions vary 

among different axle types, different truck types (vehicle classes), and different roadways. 

Differences in axle load spectra between different axle types can, in part, be attributed to a 

variety of factors related to different truck configurations, including differences in: 

 Axle configuration. 

 The legal axle load limits that apply to single, tandem, tridem, and quad axles. 

 Truck body structure needed to carry different commodities (e.g., flatbeds versus tanks 

versus basic cargo boxes). 

 Vehicle length and the number of units (single unit versus multiple units) pulled by the 

truck’s power unit. 

 The purpose of an axle (steering or load-carrying axle). 

Even for the same vehicle class and axle type, axle weights vary based on local conditions for 

reasons such as: 

 Differences in truck size and weight laws between States. 

 Presence and effectiveness of weight enforcement activities. 

 Dominant commodities carried by specific classes of trucks on each road (e.g., a standard 

five-axle tractor semitrailer weighs much more when carrying a full load of wood chips 

than it does carrying a full load of computer parts shipped with large amounts of 

padding). 

 Number of roadway lanes (outer lanes typically are loaded more heavily than inner lanes 

on multilane roads). 

In addition, the percentage of trucks carrying full or partial loads versus those returning empty to 

a terminal is a function of the type of trucking movement, the type of commodity hauled, and the 
34 

location of the road segment being analyzed. Factors that can significantly affect the percentage 

of loaded trucks observed include: 

 Percentage of long haul trucking movements occurring versus the percentage of local 

delivery movements. 

 Proximity of the roadway to urban areas (roads in or near urban areas are more likely to 

see partial or empty loads). 

 Nature of the commodities hauled on the road (e.g., most trucks carrying natural 

resources operate loaded in one direction and empty in the other). 

 Lane of traffic monitored (heavier trucks are more frequently in the outside lanes). 

Local site conditions are more likely to have a significant effect on load spectra for locations that 

have a high percentage of local traffic and a low percentage of through traffic (i.e., traffic that is 

generated from far away, especially when that through traffic must cross State boundaries). 

HOW TO CAPTURE DIFFERENCES IN AXLE LOADING IN DEFAULTS 

The key to successful development of NALS defaults is an understanding of differences in 

loading conditions within the road network for which defaults are being developed. This guide 

emphasizes the need to identify different trucking patterns and collect data on those patterns to 

develop an understanding of the NALS associated with those patterns. State agency personnel 

need to work with their freight community to accomplish this task. Once loading conditions are 

identified, the number of WIM sites that should be used to develop a default NALS could be 

determined based on observed variability in loading data. 

This guide does not prescribe the number of WIM sites that should be used to develop a default 

NALS. This information can be found in the FHWA’s Traffic Monitoring Guide and NCHRP 

Reports 538, Traffic Data Collection, Analysis, and Forecasting for Mechanistic Pavement 

Design, and 509, Equipment for Traffic Load Data.

(3,5,6) In general, it is advisable to use all 

available WIM sites in development of the defaults, provided that these sites have data that 

satisfy the data selection criteria described in the following section. 

At the same time, to keep this data analysis task manageable, those developing and applying the 

default NALS should focus on the truck and loading patterns that will significantly affect the 

outcome of the pavement analysis—in other words, the dominant vehicle classes. For example, if 

one type of truck carries a highly variable load (axles on these trucks can be very heavy or not 

too heavy), but only 1 of 1,000,000 trucks is of that truck type, then it is not necessary to spend 

much time or effort understanding when and where this specific truck type occurs, or what it 

weighs when it is observed. On the other hand, if 9 of 10 heavy trucks are of a specific type in a 

given State, understanding the differences in load carried by these trucks, and being able to 

correctly select the loading condition occurring on specific road segments, is very important. 

Alternatively, if a specific truck type never carries heavy weights, it is not important to 

understand the variation in that type of truck’s weights, even if the percentage of variation is 

large. (That is, the analyst does care whether truck axles vary from 2,000 to 4,000 lb, even 
35 

though that is a 100-percent variation, because neither of these axles will cause significant 

pavement damage.) In both the case of the “rare truck type” and the case of the “very light truck 

type,” significant amounts of variability are acceptable simply because the effects of that 

variability will have little effect on the pavement analysis. 

For the majority of the LTPP sites (and the majority of U.S. primary roads), Class 9 is the 

dominant heavy vehicle type and is responsible for a very high percentage of the traffic load 

applied to pavements. Therefore, when developing and applying NALS, a special effort should 

be made to identify different loading conditions for Class 9 vehicles. While Class 5 vehicles are 

frequently dominant in terms of truck volume, they normally are not heavy enough to make a 

significant contribution to total traffic loading and thus may be excluded from determination of 

the dominant heavy vehicle classes (unless local knowledge exists of heavier-than-usual Class 5 

vehicles at the site). 

Finally, it is advised that when NALS are developed, they should be accompanied by descriptive 

information about the loading conditions to help users correctly identify the NALS that should be 

applied for any given analysis. In this guide, these descriptions begin with the identification of 

the “typical” loading condition. This represents the most commonly observed loading condition. 

This designation serves as a useful starting point in selecting a NALS. Alternative NALS are 

then defined as lighter or heavier than the default, meaning that trucks exhibiting these 

alternative patterns will cause less or more pavement damage than trucks exhibiting the pattern 

most commonly observed. These designations are meant to help analysts select the appropriate 

NALS and understand whether the NALS they are using will provide a particularly conservative 

design. 

It is also recommended to use all available loading information (both quantitative and 

qualitative) when assigning the available default loading conditions to specific pavement 

analysis sections. 

APPROACH FOR DEVELOPMENT OF AXLE LOADING DEFAULTS 

Two types of NALS defaults are frequently used with MEPDG applications. Each of these types 

of defaults should be computed at the State level whenever possible: 

 Tier 1, or global, defaults representing statewide or nationwide default loading 

conditions. 

 Tier 2, or alternate, defaults representing specific loading conditions. These defaults are 

developed from, and assigned to, groups of roads that have common loading conditions 

for specific truck class–truck weight road groups. 

As described in Part I, Tier 1 NALS defaults are used for sites that have no information 

regarding expected traffic loading patterns on a specific pavement analysis segment. These 

defaults represent an average traffic loading condition observed at all sites used in the 

development of the default. The benefit of Tier 2 defaults is that they provide multiple choices 

for selecting traffic loading conditions for different truck classes and axle types. Appropriate 
36 

selection of these defaults requires some knowledge about the expected traffic loading condition 

at the pavement design site. 

In some cases, Tier 2 roads can be grouped and/or identified based on regional trucking patterns 

that affect the nature of truck loads carried on those roads. For example, a “regional pattern” 

might be based primarily on the commodity routinely carried on the road (coal, cut trees, specific 

agricultural products), or “regional” may simply refer to roads that are or are not in proximity to 

large metropolitan areas (rural versus urban). Some truck weight road groups and regional 

designations may only apply to specific classes of trucks. For example, the “coal region” in a 

midwestern State may only apply to Class 7 and Class 10 trucks, because other truck classes 

(e.g., Class 9) may not be involved in the specific commodity movements identified by the group 

or regional designation. This also means that more than one “truck weight group” may need to be 

applied for any given pavement analysis to reflect the different loading patterns applied by 

different classes of trucks. 

In addition, the availability of Tier 2 defaults allows easy testing of the sensitivity of the 

pavement analysis outcomes to differences in NALS inputs. That is, the user can perform two 

different runs, one using the selected NALS and one using a heavier NALS. The differences in 

the analysis outcomes provide the analyst with considerable insight into the consequences of 

using different NALS for pavement design. 

The development of MEPDG traffic-loading defaults starts with the selection of WIM sites that 

satisfy specific data selection criteria, followed by the development of representative NALS for 

each of the sites with data that meet those criteria. Then, NALS from selected individual sites (or 

all the sites, in the case of global defaults) are averaged to compute Tier 1 default NALS or 

grouped in clusters with similar loading characteristics and averaged for each cluster group. 

Based on this approach, the methodology for development of the MEPDG traffic loading 

defaults includes the following sequence of tasks: 

1. QA testing of available WIM data and selection of sites. 

2. Development of site-specific representative NALS for all selected WIM sites. 

3. Development of one set of global defaults using data for all selected WIM sites (Tier 1). 

4. Development of supplemental sets of NALS using subsets of data for sites with similar 

loading conditions (Tier 2). 

Guidelines to accomplish these tasks are described in the following sections. 

DATA SELECTION AND DEVELOPMENT OF RANALS FOR INDIVIDUAL SITES 

MEPDG NALS are produced by vehicle class and axle type for a typical day of a month. Each 

NALS represents the expected frequency with which an axle within each specified load range 

will be encountered for that vehicle type and class of axle. 

Because seasonal changes in axle load frequency distributions are not uniform across different 

States and are likely to be observed only on the roads that carry a large percentage of seasonally 
37 

affected loads, national default NALS values are developed to represent axle load frequency 

distributions for a typical day of the year. These distributions are called “representative annual 

normalized axle load spectra,” or RANALS. If truck loads change seasonally owing to truck 

volume changes, monthly adjustment coefficients are used to adjust truck volumes between 

different months. If a State has a group of roads subject to seasonal changes in load distribution 

frequencies, default NALS should be developed to represent each month or season in the year. 

Data Selection Criteria for Development of Site-Specific Representative NALS 

These guidelines address WIM data requirements to develop representative site-specific NALS 

for computation of the default NALS. To take full advantage of the available WIM data, the data 

selection criteria focus on maximizing the use of available data without compromising the 

quality of MEPDG defaults. WIM data selection criteria address the following data selection 

categories: 

 Data availability: maximized use of available data that satisfy data quality criterion. 

 Data quality: identification and utilization of reliable, high-quality axle loading data. 

 Data reasonableness: identification of data that are not only accurate but also represent 

typical/expected conditions for a given site or a group of sites that have similar trafficloading patterns. 

The following conservative minimum data availability criteria were identified to remove any 

potential day-of-the-week (DOW) and monthly bias from the computation of RANALS for 

individual WIM sites: 

 Availability of at least 1 of each 7 DOW per month to avoid potential DOW bias. Days 

do not need to be consecutive. 

 Availability of at least 1 of each 12 calendar months to avoid potential seasonal bias. 

Months do not need to be consecutive or from the same calendar year. 

These minimums were developed through a number of statistical analyses designed to evaluate 

the reliability of computed NALS using different data quality and availability scenarios. 

When more than 7 DOWs per month or more than 12 calendar months of acceptable quality data 

are available, all available data for that site should be used in the computation of site-specific 

RANALS. If less than these minimums are present, the lack of data may create bias in the 

RANALS such that they underestimate the effects of loading patterns missing from the data. For 

example, if no data are present from the spring months owing to equipment failure, and loads are 

lighter in the spring months than during the rest of the year owing to spring thaw load 

restrictions, the RANALS will overestimate the average loading condition. Similarly, in urban 

areas, weekend loads may be heavier than weekday loads as the percentage of through traffic to 

local traffic increases. 
38 

The following acceptable data quality criteria were identified for RANALS to be used in the 

LTPP project: 

 Data should be from a WIM site conforming to ASTM (ASTM International, formerly 

American Society for Testing and Materials) 1318 specification for Type I WIM system 

accuracy and performance requirements specified in the LTPP SPS Field Operation 

Guide.(7,8)

 Selected data must pass quality review using LTPP QC procedures for the SPS TPF study 

and be identified as Level E data in the LTPP database.(9)

States developing NALS default tables for their own use are encouraged to follow these same 

data quality standards but are not expected to follow LTPP reporting requirements. It is also 

advisable to limit the maximum acceptable bias in axle weight measurements to less than 

5 percent to avoid significant differences in MEPDG outcomes owing to bias in axle weight data. 

In addition to the basic quality of the data and the number of days for which data are available at 

each site, data from specific sites should be evaluated for reasonableness for inclusion in default 

NALS used to represent the traffic load expected to occur on other roads in a State. In some 

circumstances, data may be valid but (1) are atypical because of atypical conditions that occurred 

at a site (for example, a 6-month-long, temporary load restriction imposed during bridge 

construction downstream of the data collection site); (2) truck volumes for a particular vehicle 

class are so low, given a specific truck class distribution at the site, that data are not sufficient to 

produce a representative axle load spectrum for some vehicle classes; or (3) the loading pattern 

observed at a site is significantly different from other sites owing to unique truck traffic 

generators in the vicinity of the site. 

In the first two conditions, data for vehicle classes affected by the loading restriction are not 

suitable for use in default RANALS. In the first case, the data are not representative of “normally 

observed” loading conditions. In the second case, the very low frequency of vehicles makes the 

values in the RANALS unstable statistically. When averaged with other RANALS, these few 

axles have too much impact on the NALS for any group in which they are placed. For example, 

if only four axles are measured at a site and two fall into one load range in the NALS, that load 

range contains 50 percent of all axles in the RANALS for that site. When averaged with any 

other set of RANALS, the 50-percent value badly biases the computation of the average 

percentage of axles that fall into that load range. 

In the third case, the RANALS should not be included in a load group with data from other sites. 

Instead, it should be treated as a “special case.” This means that a “special case” description of 

why it is unique should be developed for that condition so that it can be used in pavement 

analysis when other pavements also experience that condition. 

All of these data would be useful for site-specific MEPDG analysis but should not be used for 

creation of generalized defaults, which are designed to represent typical traffic loading 

conditions for sites without site-specific axle load spectra. 
39 

Procedure for Development of RANALS Estimates 

The following procedure describes the steps for developing RANALS using daily axle load 

spectra stored in a format consistent with LTPP LTAS DD_AX tables: 

1. Identify all sites for which the available data meet the selection criteria of having data for at 

least 7 DOWs, for each calendar month, and at least 12 calendar months. These data must 

have passed the LTPP SPS TPF QC checks for data and performance of the WIM equipment. 

They must also pass the data reasonableness checks described in the LTPP report MEPDG 

Traffic Loading Defaults Derived from LTPP Transportation Pooled Fund Study.

(10)

2. Extract daily axle load spectra from the LTPP LTAS DD_AX tables for all years and months 

from all sites that were identified in the previous step, where the resulting data are expressed 

as daily axle load counts by weight bin. 

3. For each site, compute axle load spectra representing the typical day of the month for each 

month, by year, axle type, and vehicle class (classes 4 through 13). The daily axle load 

spectra should be averaged first by DOW and then across DOWs to produce an unbiased 

monthly axle load spectra (as representative loading for a day of the month for a given year) 

for each vehicle class, axle type, month, and year. 

4. For each site, year, month, axle type, and vehicle class, normalize the axle load spectra 

representing the typical day of the month to obtain monthly NALS. 

5. For each site, axle type, vehicle class, and calendar month (January through December), 

compute average monthly NALS (as representative loading for a day of the month) by 

averaging data across all available years. This will result in 12 representative monthly NALS 

for each calendar month, axle type, and vehicle class for each site. 

6. For each site, axle type, and vehicle class, average the 12 monthly NALS. This will result in 

one RANALS representing the typical day of the year for each axle type and vehicle class for 

each site. 

Each set of RANALS includes a normalized axle load spectrum for each vehicle class (for 

classes 4 through 13) and each axle type (single, tandem, tridem, and quad as applicable) 

representing the expected axle loading distribution for a typical day of the year for that site. 

DEVELOPMENT OF GLOBAL NALS DEFAULTS (TIER 1) 

Overview 

The purpose of the global NALS defaults is to serve as input to the MEPDG when very little or 

no information about existing or expected future traffic loading patterns is available for a design 

site. Global NALS defaults follow the exact format of the original MEPDG defaults and can be 

implemented easily. These defaults are based on averaging RANALS from all the WIM sites that 

have sufficient data. 
40 

Procedure for Development of Global NALS Defaults (Tier 1) 

This procedure is based on averaging RANALS from the WIM sites that have sufficient data. To 

avoid biasing NALS as a result of unstable load spectra distributions caused by very low axle 

counts (which are considered insufficient to define a load spectra frequency distribution for a 

given class and axle), if a site has fewer than 100 axles and/or an APC of less than 0.01, that site 

should not be included in the computation of global NALS defaults for that vehicle class and 

axle type. 

The computational steps and data availability criteria are presented below: 

1. Obtain RANALS for all sites that satisfy the data selection criteria presented in this guide. 

2. For each vehicle class and axle type, exclude from further computations RANALS that are 

based on very low axle counts, using the following criteria: 

 RANALS that are based on very low axle counts (fewer than 100 axles and/or axles per 

class less than 0.01). 

 RANALS representing highly unusual or unique loading conditions that are not likely to 

be encountered on road classes where global defaults will be used. 

3. For each vehicle class and axle type, average the available RANALS. 

4. Save the results in a table format provided in the LTPP PLUG database (see appendix B). 

DEVELOPMENT OF ALTERNATE NALS DEFAULTS REPRESENTING 

ALTERNATIVE AXLE LOADING CONDITIONS (TIER 2) 

This section provides guidelines for States to use their own WIM data to develop NALS 

representing different loading conditions within the State for use with the MEPDG and 

DARWin-ME software. NALS representing different loading conditions within the State’s road 

network provide flexibility to MEPDG users in the selection of axle loading defaults so that they 

can more accurately describe their local loading conditions. 

Tier 2 NALS are designed to be used independently to specify different truck loading conditions 

by class and axle type. For example, a pavement designer may select a “heavy” axle load 

spectrum for Class 9 vehicles but a “light” load spectrum for Class 6 vehicles because those 

loading conditions are appropriate for the truck traffic using the roadway they are designing. 

Methodology for Grouping WIM Sites With Similar Loading Conditions 

To create Tier 2 NALS, the site-specific RANALS should be grouped in clusters based on 

similarities in the axle loading conditions. For each cluster, alternative default NALS should be 

computed for each vehicle class and axle type in such a way that there is a high probability that 

the use of these alternative NALS will result in a significant differences in the expected 

pavement life or design thickness predictions. 
41 

The grouping of site-specific NALS into Tier 2 defaults should be done separately for each class 

and axle type. That is, just because tandem axles for Class 9 trucks from sites 1 and 2 are shown 

to belong to the same Tier 2 NALS does not mean that tandem axles for Class 10 trucks from 

those same two sites should also be placed together in a default NALS. 

The recommended way to create Tier 2 NALS is to use the hierarchical clustering technique, 

available in most statistical software packages, to group RANALS from State WIM sites that 

have similar pavement damaging potential. Step-by-step instructions are given below. The 

methodology and detailed analysis behind this procedure are presented in chapters 8 through 10 

of the LTPP report, MEPDG Traffic Loading Defaults Derived from LTPP Transportation 

Pooled Fund Study. (10) 

Procedure for Development of NALS Defaults Representing Different Loading Conditions 

The procedures described below are based on the methodology described in the LTPP report,

MEPDG Traffic Loading Defaults Derived from LTPP Transportation Pooled Fund Study.

(10)

Other mechanisms to group load spectra into “similar” groups are also possible. The steps 

required to create Tier 2 NALS are as follows: 

1. Ensure that the WIM data used to compute State-specific defaults come from data collection 

equipment that is calibrated and functioning properly. 

2. Develop RANALS for each site. 

3. Using the RANALS, compute an RPPIF summary statistic associated with each load 

spectrum that takes into account both the pavement damage potential of different axle load 

weights and the frequency of the application of those loads (i.e., the fraction of loads of a 

given magnitude in the axle load spectra). 

4. Determine the importance of each vehicle class and axle type based on the frequency with 

which specific classes of vehicles are observed and the loading characteristics of those 

vehicles (i.e., identify types of trucks that cause heavy damage to the pavement because of 

their weight and volume). 

5. Determine the sensitivity of the MEPDG to the variation inherent in the truck fleets observed 

by the agency, given the pavement design philosophy of the agency, and establish maximum 

RPPIF differences for cluster analysis. 

6. Perform a cluster analysis of the RPPIFs (by vehicle class and type of axle) using the output 

of the sensitivity of the MEPDG as a guide for determining when to stop the clustering 

process. 

The first two steps above were discussed as part of constructing the Tier 1 default NALS. Each 

of the remaining steps is described below. 
42 

Step 3: Compute RPPIF Statistics Using RANALS 

The RPPIF summary statistics were used in the creation of the new national default NALS based 

on SPS TPF data. The intent of the RPPIF is to allow simple summary comparisons of the size of 

different loading conditions by providing a single statistic associated with each load spectrum. 

RPPIF is computed by taking into account both the pavement damage potential of different axle 

load weights and the frequency of the application of those loads (i.e., the fraction of loads of a 

given magnitude in the axle load spectra). It is computed using the W-factors shown in table 18. 

These factors provide a generic measure of the relative pavement damaging potential caused by 

axles of specific weights and configurations, as determined through MEPDG analysis in the 

report, MEPDG Traffic Loading Defaults Derived from LTPP Transportation Pooled Fund 

Study.

(10) 

The RPPIF statistic is used to identify axle loading conditions within each vehicle class and axle 

type that are likely to produce significantly different MEPDG outcomes. States wishing to group 

“similar” RANALS using other criteria are welcome to do so. 

To compute the RPPIF statistics, use the equation shown in figure 1. Start with the RANALS 

computed for each vehicle class and axle type. For each of those RANALS, multiply the load 

frequency corresponding to each load bin in those load spectra by the corresponding W-factor 

from table 18. Sum these values across all load bins (i = 1 to n) for that load spectra. 

Figure 1. Equation. Computation of RPPIF statistics 

Where: 

RPPIFjk = relative pavement performance impact factor for axle type j and vehicle class k 

i = load bin 

j = the type of axle 

k = the class of vehicle 

Wij = the impact factor for load range i, for axle type j from table 18 

Fijk = the fraction of axles in load range i, for axle type j, and vehicle class k

RPPIFjk = 

i1

n

(Fijk * Wij)
43 

Table 18. Pavement performance impact factors, Wij

Load 

Bin 

Single Axle Tandem Axle Tridem Axle Quad Axle 

Load Range 

(lb) 

Weight 

Factor 

Load Range 

(lb) 

Weight

Factor 

Load Range 

(lb) 

Weight 

Factor 

Load Range 

(lb) 

Weight

Factor 

BIN_01 0–2,999 0.00 0–5,999 0.00 0–11,999 0.00 0–11,999 0.00 

BIN_02 3,000–3,999 0.00 6,000–7999 0.00 9,000–11,999 0.00 9,000–11,999 0.00 

BIN_03 4,000–4,999 0.00 8,000–9999 0.00 12,000–14,999 0.00 12,000–14,999 0.00 

BIN_04 5,000–5,999 0.00 10,000–11,999 0.00 15,000–17,999 0.04 15,000–17999 0.00 

BIN_05 6,000–6,999 0.00 12,000–13,999 0.01 18,000–20,999 0.09 18,000–20,999 0.02 

BIN_06 7,000–7,999 0.00 14,000–15,999 0.04 21,000–23,999 0.15 21,000–23,999 0.05 

BIN_07 8,000–8,999 0.02 16,000–17,999 0.08 24,000–26,999 0.21 24,000–26,999 0.09 

BIN_08 9,000–9,999 0.04 18,000–19,999 0.14 27,000–29,999 0.28 27,000–29,999 0.14 

BIN_09 10,000–10,999 0.08 20,000–21,999 0.22 30,000–32,999 0.35 30,000–32,999 0.20 

BIN_10 11,000–11,999 0.12 22,000–23,999 0.30 33,000–35,999 0.43 33,000–35,999 0.27 

BIN_11 12,000–12,999 0.18 24,000–25,999 0.40 36,000–38,999 0.53 36,000–38,999 0.34 

BIN_12 13,000–13,999 0.24 26,000–27,999 0.51 39,000–41,999 0.64 39,000–41,999 0.42 

BIN_13 14,000–14,999 0.31 28,000–2,9999 0.62 42,000–44,999 0.76 42,000–44,999 0.52 

BIN_14 15,000–15,999 0.40 3,0000–31,999 0.75 45,000–47,999 0.92 45,000–47,999 0.62 

BIN_15 16,000–16,999 0.49 32,000–33,999 0.89 48,000–50,999 1.10 48,000–50,999 0.73 

BIN_16 17,000–17,999 0.59 34,000–35,999 1.04 51,000–53,999 1.32 51,000–53,999 0.85 

BIN_17 18,000–18,999 0.71 36,000–37,999 1.21 54,000–56,999 1.58 54,000–56,999 0.99 

BIN_18 19,000–19,999 0.85 38,000–39,999 1.40 57,000–59,999 1.90 57,000–59,999 1.14 

BIN_19 20,000–20,999 1.01 4,0000–41,999 1.63 60,000–62,999 2.27 60,000–62,999 1.30 

BIN_20 21,000–21,999 1.19 42,000–43,999 1.90 63,000–65,999 2.71 63,000–65,999 1.47 

BIN_21 22,000–22,999 1.41 44,000–45,999 2.23 66,000–68,999 3.22 66,000–68,999 1.66 

BIN_22 23,000–23,999 1.67 46,000–47,999 2.63 69,000–71,999 3.82 69,000–71,999 1.87 

BIN_23 24,000–24,999 1.99 48,000–49,999 3.13 72,000–74,999 4.51 72,000–74,999 2.10 

BIN_24 25,000–25,999 2.38 50,000–51,999 3.74 75,000–77,999 5.30 75,000–77,999 2.35 

BIN_25 26,000–26,999 2.85 52,000–53,999 4.49 78,000–80,999 6.20 78,000–80,999 2.63 

BIN_26 27,000–27,999 3.43 54,000–55,999 5.42 81,000–83,999 7.22 81,000–83,999 2.93 

BIN_27 28,000–28,999 4.12 56,000–57,999 6.56 84,000–86,999 8.37 84,000–86,999 3.26 

BIN_28 29,000–29,999 4.96 58,000–5,9999 7.95 87,000–89,999 9.66 87,000–89,999 3.62 

BIN_29 30,000–30,999 5.97 60,000–61,999 9.64 90,000–92,999 11.09 90,000–92,999 4.02 

BIN_30 31,000–31,999 7.18 62,000–63,999 11.67 93,000–95,999 12.68 93,000–95,999 4.46 

BIN_31 32,000–32,999 8.62 64,000–65,999 14.11 96,000–98,999 14.44 96,000–98,999 4.94 

BIN_32 33,000–33,999 10.33 66,000–67,999 17.00 99,000–101,999 16.37 99,000–101,999 5.47 

BIN_33 34,000–34,999 12.35 68,000–69,999 20.43 102,000–104,999 18.48 102,000–104,999 6.06 

BIN_34 35,000–35,999 14.72 7,0000–71,999 24.47 105,000–107,999 20.78 105,000–107,999 6.71 

BIN_35 36,000–36,999 17.48 72,000–73,999 29.19 108,000–110,999 23.28 108,000–110,999 7.42 

BIN_36 37,000–37,999 20.70 74,000–75,999 34.68 111,000–113,999 25.98 111,000–113,999 8.20 

BIN_37 38,000–38,999 24.41 76,000–77,999 41.04 114,000–116,999 28.90 114,000–116,999 9.06 

BIN_38 ≥ 39,000 28.70 ≥ 78,000 48.37 ≥ 117,000 32.03 ≥ 117,000 10.01 

Step 4: Determine the Importance of Specific Vehicle Classes and Axle Types 

If the criteria used for the creation of the national Tier 2 NALS are acceptable (see step 6), 

simply skip to step 6 and use the criteria presented in table 20, along with State-specific 

RANALS, to develop State-specific Tier 2 NALS. If State-specific traffic attributes and design 

criteria/performance models are to be used, then steps 4 and 5 must be followed to develop a 

State-specific criteria table that replaces table 20 in step 6. 

Because of their complexity, this guide only summarizes steps 4 and 5. They are discussed in 

greater detail in chapter 9 of the LTPP report, MEPDG Traffic Loading Defaults Derived from 

LTPP Transportation Pooled Fund Study.

(10) 
44 

In step 4, a State determines the truck volumes to test the sensitivity of the MEPDG pavement 

designs to State-specific loading conditions. The Tier 2 national defaults described in Part I of 

this guide are based on the truck volume patterns observed in the LTPP traffic database. As a 

result, they may or may not be representative of the kinds of trucks traveling on a given State’s 

roads. For example, roads in the western States often have a much higher percentage of multitrailer truck travel than roads in most eastern States. Consequently, the use of national averages 

tends to overestimate multi-trailer truck travel and importance to pavement performance in 

eastern States and underestimate their importance in western States. Similarly, in portions of 

some midwestern States (e.g., Ohio, Pennsylvania, and Kentucky), very heavy, multi-axle singleunit trucks (i.e., four, five, and six+ axle, single-unit trucks) are commonly found on roads that 

serve natural resource extraction industries (e.g., coal). The largest of these trucks is rarely found 

in many other States. 

The primary purpose of step 4 is to determine the upper bounds of the volume of trucks 

occurring and the maximum percentage of all truck traffic that occurs in that class. These two 

factors are used to set up tests of the sensitivity of the MEPDG’s outputs to different observed 

loading conditions for that class of trucks. 

To obtain the maximum observed truck volumes per lane and the maximum observed truck 

percentages by class of truck, the agency should examine the data in its own historical traffic 

database. The intent is to find those traffic conditions that maximize the impact of each vehicle 

class on pavement design. That is, under what truck volume and vehicle class distribution 

conditions does a given vehicle class represent the largest percentage of the total truck load on 

roads found in the State? Identified maximum truck volume conditions (relative to other truck 

volumes) can then be used to determine how sensitive the MEPDG outcomes are to the possible 

changes in load observed in that class. Table 19 shows an example of the outcome of this data 

analysis task. The highlighted percentage values and average annual daily truck traffic (AADTT) 

values can then be taken into the MEPDG sensitivity tests. 

Table 19. Example of traffic design conditions for each vehicle class 

Class Site Number AADTT 

Vehicle Class Distribution for Vehicle Class (percent) 

4 5 6 7 8 9 10 11 12 13 

4 1 5,560 50.5 3.8 0.0 14.9 21.4 0.1 0.3 2.2 6.6 0.0 

5 2 1,560 6.4 75.3 14.9 0.0 0.7 2.6 0.1 0.0 0.0 0.0 

6 3 450 1.5 19.2 53.6 9.3 7.1 5.5 1.3 0.5 0.0 2.0 

7 4 1,210 2.9 27.1 17.0 10.6 8.0 32.6 1.0 0.8 0.1 0.0 

8 5 610 15.0 22.1 7.9 5.9 38.4 5.9 2.3 0.3 0.2 2.1 

9 6 3,040 0.3 4.8 1.6 0.1 2.3 85.7 0.5 3.1 1.3 0.2 

10 7 1,890 4.5 8.8 5.2 3.3 1.1 14.3 28.9 0.0 0.6 33.2

11 8 1,860 1.1 45.0 9.6 0.7 6.6 24.3 0.0 12.3 0.1 0.2 

12 9 1,220 2.7 25.9 6.1 0.8 3.7 33.0 4.9 0.6 7.8 14.6

13 7 1,890 4.5 8.8 5.2 3.3 1.1 14.3 28.9 0.0 0.6 33.2

Note: The boldface percentage values and average annual daily truck traffic (AADTT) values can be 

used in the MEPDG sensitivity tests. 

Step 5: Determine MEPDG Sensitivity 

This task uses the RANALS obtained in step 2 and the traffic volume data developed in step 4 to 

test the sensitivity of the selected MEPDG designs to the loading conditions present in the State. 
45 

States implementing this step should identify a set of typical pavement designs and pavement 

distress modes frequently observed in the State, determine pavement performance criteria for 

MEPDG design, and use locally calibrated pavement design models. 

To test MEPDG sensitivity to a single class of trucks at a time, all traffic loading conditions 

other than the axle load spectra for the class being studied should be held constant for a selected 

pavement design. For each class of trucks being tested, the truck traffic volume and vehicle class 

distribution parameters should represent the case when the test truck class contributes the largest 

percentage of total load, compared with other vehicle classes, observed in that State (using the 

AADTT and the percentage shown in the State-specific version of table 19). 

Different MEPDG runs are then performed for the class of vehicles being examined, with all 

inputs held constant, except that different RANALS are used as inputs. The RANALS developed 

in step 2 for that vehicle class are selected from the State’s WIM data to represent the range of 

axle weight conditions those trucks are observed to carry in that State. 

The output from the MEPDG is then used to determine the degree to which differences in 

observed axle loads for each vehicle class can change pavement analysis outcomes. When two 

RANALS for a given vehicle class produce “significantly different” pavement analysis results, 

the RPPIF values that represent those two RANALS can be compared. The difference in the 

RPPIF values between those two RANALS can be used to establish criteria for determining 

when two RANALS should be kept as part of two different Tier 2 NALS clusters. That is, if two 

RANALS produce significantly different pavement analysis outcomes, they are not “similar,” 

and they should not be combined into the same group for computation of default NALS. The 

difference in their RPPIF values then becomes a measure that can be used to determine the size 

of required boundaries between Tier 2 NALS clusters. 

Each State may select its own definition of “significantly different” MEPDG outcome. For 

example, a change in asphalt concrete or portland cement concrete thickness of 1⁄2 inch could be 

used as one measure of “significantly different.” So when differences in load spectra do not 

produce a change in thickness equal to or greater than 1⁄2 inch, those load spectra are determined 

to be “similar.” Another measure of significance could be a difference in predicted pavement 

service life greater than 20 percent. 

By summarizing the RPPIF differences that resulted in significant differences in MEPDG 

outcomes for each class of truck, it is possible to produce a table such as table 20, shown in 

step 6 below. This table is then used as the criterion for when to stop the clustering process that 

produces Tier 2 NALS. 

Step 6: Perform Cluster Analysis 

The final step in the development of agency-specific default load spectra is the actual clustering 

of “similar” load spectra into a limited number of groups. This is best done with a statistical 

program such as SPSS, SAS, or similar programs. 

The clustering of agency-supplied RPPIFs (computed in step 3 above for each site, vehicle class, 

and axle type) is controlled by the sensitivity of the pavement design process to traffic loadings. 
46 

If State-specific sensitivity tests have been performed, use those results to control the clustering 

process. If no State-specific tests have been performed, use the values in table 20. 

Table 20. Difference in RPPIF per axle likely to cause change in pavement performance 

Class 

Frequency of Truck 

Occurrence 

(percent of total truck 

volume) 

Truck Type 

by Weight 

Axle Type 

Single Tandem Tridem Quad 

7, 10, 13 Infrequent (<35) Heavy >0.55 0.41 0.49 0.8 

6, 8, 11, 12 Moderate to Infrequent (<50) Moderate 0.25 0.23 N/A N/A 

9, 4 Frequent to Moderate (>50) Heavy >0.13 0.09 N/A N/A 

5 Frequent (>75) Light >0.09 N/A N/A N/A 

N/A = not applicable 

In the clustering process, the difference between the mean RPPIF for two nearest-neighbor 

clusters should not exceed the values in table 20. Thus, the cluster process should be stopped one 

step prior to the step when that distance is exceeded. 

Once all clusters are identified, RANALS for the sites that belong to the same cluster should be 

averaged to compute default NALS representing that cluster group. This should be done for each 

vehicle class and axle type. For each computed average NALS, RPPIF and percentage heavy 

statistics should be computed and compared with the values in table 2 or a similar table defined 

by the agency. Based on these statistics, a name and/or code should be assigned to the NALS 

cluster, similar to the names/codes included in the first column of table 2. If more than one 

cluster is identified for the same loading category, then sequential codes should be assigned to 

these NALS. For example, if two NALS clusters for Class 9 tandems fall within the “heavy” (H) 

loading category, cluster codes H1 and H2 should be used. H1 should be used for the lighter of 

the two NALS and H2 for the heavier. A cluster that has a majority of sites for a given vehicle 

class and axle type should be selected as the default or “typical” cluster, and the letter code (T) 

should be added to the cluster code, for example, H1(T). All computed NALS should be saved to 

the database. Appendix B provides a data dictionary to facilitate appending State-defined Tier 2 

NALS to the LTPP PLUG database. 

DEVELOPMENT OF REPRESENTATIVE SITE-SPECIFIC AND DEFAULT AXLEPER-CLASS COEFFICIENTS 

Overview 

The MEPDG requires users to specify the number of axles per truck type as a part of traffic 

inputs for pavement design and analysis. These values are used in the computation of total axle 

loading. These numbers are also called APC coefficients. The MEPDG procedure uses APC as a 

multiplier in the process of converting NALS to projected axle load spectra for use in pavement 

design. 

APC values are required for each vehicle class and axle type. If a specific axle type is not used 

for a given vehicle class, then a zero value is entered as the APC for that axle type. One set of 

APCs is used per pavement design, representing the typical number of axles observed for each 

axle type for each vehicle class. 
47 

APCs are computed for each vehicle class and axle type by dividing axle load counts by vehicle 

volumes collected for the same periods of time and the same vehicle class. Because the MEPDG 

requires only one set of APCs per design, these values are computed based on the annual axle 

count and vehicle volume estimates. 

Procedure to Develop Site-Specific and Default APC Coefficients 

The following approach is recommended to compute a default set of APCs using the daily axle 

weight and vehicle volume data stored in database tables that are consistent with the LTAS 

DD_AX and DD_WT_CT tables: 

1. Extract daily vehicle and axle count summaries from the LTPP LTAS DD_AX and 

DD_WT_CT tables for each site for the years and months that satisfy the data selection 

criteria of having data during at least 7 DOWs for each calendar month and at least 

12 calendar months per site that pass the LTPP SPS TPF QC checks for data and WIM 

equipment. 

2. Compute site-specific APC for each site (MEPDG Level 1 inputs) using the following 

procedure: 

a. Develop a list of all matching dates in the DD_AX and DD_WT_CT tables. 

b. For all matching dates, compute the total daily axle counts by class and axle type by 

summing axle counts reported in individual load bins. If no axle counts are found for a 

given axle type, vehicle class, year, month, and day while a non-zero volume is computed 

for the matching vehicle class, year, month, and day, enter 0 for the total axle counts for 

this axle type, vehicle class, month, and year. 

c. For all matching dates in DD_AX and DD_WT_CT tables, compute the total daily 

vehicle volumes by vehicle class for each month and year. 

d. For each day, month, and year that had non-zero total vehicle class volume, divide the 

total axle counts by the total vehicle volumes for each axle type and vehicle class. This 

step results in an APC for each axle type and vehicle class by day, month, and year. 

e. For each axle type and vehicle class, average the computed daily APC over all available 

days. This step results in site-specific APC for each axle type and vehicle class for a 

given site (MEPDG Level 1 inputs for individual site). 

3. To compute a default APC based on all sites, average the site-specific APCs among all sites 

for each axle type and vehicle class. This step results in a global default APC for each axle 

type and vehicle class (MEPDG Level 3 input). 

DEVELOPMENT OF DEFAULT AXLE SPACING AND WHEELBASE VALUES 

Average Axle Spacing and Wheelbase for JPCP Model 

Average axle spacing or wheelbase information is used for MEPDG applications involving the 

top-down slab cracking failure mode in JPCP. For this failure mode, the critical loading is caused 

by a combination of axles that place axle loads close to both ends of the same slab (in the 

direction of travel) at the same time. For JPCP designs with 15-ft-long slabs, axle spacings of 

between 12 and 15 ft would result in the axle loading positions most critical to development of 
48 

top-down slab cracking. For JPCP with 20-ft joint spacings, the most critical axle spacings would 

be between 17 and 20 ft. 

The current MEPDG top-down slab cracking model assumes that the majority of axle spacings 

that could induce top-down slab cracking are attributed to the wheelbase of the tractor (power) 

units in tractor-semitrailer combination trucks (FHWA classes 8 through 13). To account for 

these axles and axle spacings, the MEPDG directly considers the wheelbase of the tractor unit in 

the form of three inputs: the percentages of tractor units with short, medium, and long 

wheelbases. The MEPDG states that the percentage of trucks in each of these three categories 

should be based on the axle spacing distribution (or wheelbase) of truck tractors in Class 8 and 

above. The MEPDG recommends the following three-axle spacings or “tractor” wheelbase 

categories for analysis: 

 Short—12 ft. 

 Medium—15 ft. 

 Long—18 ft. 

By default, the MEPDG software assumes an even distribution of short, medium, and long axle 

spacing occurrences: 33, 33, and 34 percent, respectively. 

Axle spacing can be estimated based on a sample of per-vehicle records obtained for each of the 

LTPP WIM sites. One month of data for each WIM site is considered sufficient, unless it is a low 

truck volume site. This sample size is considered to be representative based on an evaluation of 

the consistency of the axle spacing measurements through the year. 

Procedure to Compute Average Axle Spacing and Wheelbase 

1. Extract axle spacing values from per-vehicle records by vehicle class for all the sites. 

2. Filter records corresponding to the first axle spacing for classes 8 and above. 

3. Determine ranges for short, medium, and long axle spacing relative to JPCP joint spacing 

values used by the agency, or use the MEPDG values of 12, 15, and 18 ft. 

4. Compute percentages of the first axle spacing for classes 8 and above for each of the three 

categories referenced in step 3. 

In addition, the MEPDG states that if other vehicles in the traffic stream have axle spacings in 

the range of the short, medium, and long spacing defined above, the frequency of those vehicles 

could be added to the axle spacing distribution of truck tractors. For example, if 10 percent of 

truck traffic is multiple trailers (Class 11 and above) that have trailer-to-trailer axle spacings in 

the “short” range, 10 percent should be added to the percentage of truck tractors with “short” 

axles. Thus, the sum of the percentages of trucks in the short, medium, and long categories can 

be greater than 100. “Short” spacing should not include multi-axle groups such as tandem, 

tridem, and quad in the computation. 
49 

Procedure to Compute Axle Spacing for Multi-Axle Groups 

Axle spacing for multi-axle groups is the distance between the two consecutive axles of a 

tandem, tridem, or quad. Default axle spacing values can be computed based on averaging the 

values extracted from per-vehicle records for all the sites, using the following procedure: 

1. Extract axle spacing values from per-vehicle records for all sites. 

2. Filter records that have axle spacings of less than 8 ft for vehicle classes 4 through 13. 

3. Review filtered records and identify multi-axle groups as follows: 

a. Mark two consecutive spacings of less than 8 ft each per record as tridem axles. 

b. Mark three consecutive spacing less than 8 ft each per record as quad axles. 

c. If there is only one spacing less than 8 ft in sequence per record, mark it as tandem axle. 

4. Compute average axle spacing values among axles marked as tandem, tridem, and quad 

axles. 

For tridem and quad axles, compute average axle-to-axle spacing. 

USE OF AXLE LOADING DEFAULTS WITH DARWIN-ME 

Currently, the DARWin-ME software contains the NALS defaults developed under NCHRP 

Project 1-37A. If the user wants to use NALS defaults generated based on SPS TPF data, there 

are four ways to enter these data into the Axle Distribution table in the DARWin-ME project file: 

 Enter data manually. 

 Import default NALS file in MEPDG (*.alf) format. 

 Import default NALS file in an XML format. 

The LTPP PLUG software provides the options of generating an axle load file in both the 

MEPDG (*.alf) format and the DARWin-ME XML formats for any of the default or site-specific 

NALS included in the LTPP PLUG database. Generated *.alf or XML files could be stored in a 

user-specified directory and uploaded in DARWin-ME using the data import option. *.alf files 

work with both NCHRP 1-37A and DARWin-ME software products. 

51 

APPENDIX A. LTPP PLUG SOFTWARE OPERATOR’S MANUAL 

PURPOSE AND APPLICABILITY 

This manual and accompanying software program were developed to aid users in estimating 

traffic loading inputs for MEPDG applications for sites with insufficient site-specific traffic 

loading data. 

This application is beneficial for developing MEPDG Level 2 or 3 traffic loading inputs for 

LTPP sites that have site-specific vehicle classification and/or truck volume data but no axle load 

information (or if the accuracy of the loading information is questionable owing to limited data 

availability or traffic monitoring equipment type). Traffic loading inputs are developed by 

selecting or computing NALS for each vehicle class and axle type based on available LTPP 

NALS defaults or site-specific NALS for SPS TPF WIM sites. Once default or surrogate NALS 

are established for a given LTPP site, the software develops a NALS input file for use with the 

DARWin-ME software (*.alf or *.xml file). 

The LTPP PLUG database and software also can be used to develop MEPDG levels 2 and 3 

traffic loading inputs and NALS defaults using agency-specific NALS (site-specific and/or 

defaults) or a combination of agency-specific data and LTPP-based loading defaults. The 

software includes a data import function for this purpose. The LTPP PLUG data dictionary is 

provided in appendix B to facilitate the integration of agency-specific axle load distributions and 

vehicle classification data. 

STARTING THE APPLICATION 

This application is embedded in a Microsoft® Access database file and can run on any computer 

on which Access is installed. No LTPP PLUG software installation is required. 

Start the application by opening the LTPP PLUG database file, LTPP_PLUG.mdb. Based on the 

user’s computer and Microsoft® Access security settings, the user may need to ensure that 

macros/content is enabled in the application. This is accomplished by clicking the “Options...” 

frame located on the security warning ribbon and clicking the “Enable this content” radio button. 

Microsoft® Access Reference Libraries 

This application was developed using Microsoft® Access 2007. If the user is using this 

application with a different version of Access, references to some of the Microsoft® libraries 

used in this application could be lost, and these libraries will be marked as “Missing.” In these 

circumstances, the user should add and activate the necessary reference libraries. To accomplish 

this task, open the VBA code window by pressing Alt+F11 and choosing “References” from the 

Tools menu. This will display the form showing all available reference libraries. The user should 

make sure that the three reference libraries shown with the checkmarks in figure 2 are available 

and selected. 
52 

Figure 2. Screen capture. Selection of necessary library references 

FUNCTIONALITY DESCRIPTION 

Select Actions from the Main Menu 

When the user starts LTPP PLUG database application, the main menu, shown in figure 3, 

displays. 
53 

Figure 3. Screen capture. Main menu for selecting different actions 

This menu offers three action options: 

 ACTION #1: Import traffic summaries to LTPP PLUG database. 

 ACTION #2: Select site-specific or default NALS for MEPDG use. 

 ACTION #3: View, group, and combine NALS from multiple WIM sites. 

ACTION #1 provides means for uploading LTPP or user-supplied data to the following tables in 

the LTPP PLUG database: 

 DEFAULT_NALS—This table contains default NALS. 

 SITE_SPECIFIC_NALS—This table contains representative site-specific NALS. 

 DEFAULT_AxlesPerTruck—This table contains default axles per truck factors. 

 SITE_SPECIFIC_AxlesPerTruck—This table contains representative site-specific axles 

per truck factors. 

 SITE_SPECIFIC_NVCD—This table contains normalized site-specific vehicle class 

distributions (classes 4 through 13). 
54 

 PLUG_W_FACTORS_FOR_RPPIF—This table contains the W-factors for computation 

of the RPPIF statistic (MEPDG-based damaging potential). 

See appendix B for table formats. 

ACTION #2 provides means for selecting site-specific or default NALS and development of 

MEPDG load distribution input files: 

 Site-specific NALS—Representative site-specific NALS uploaded to the 

SITE_SPECIFIC_NALS table. 

 Tier 1 default NALS—Global default NALS computed by averaging NALS for 26 LTPP 

SPS TPF sites. 

 Tier 2 default NALS—Alternate default NALS that represent different loading 

conditions. Tier 2 NALS can be selected using manual or computer-assisted processes. 

 User-defined NALS—NALS based on computations using user-selected, site-specific 

NALS. 

ACTION #3 provides means for reviewing load spectra from multiple WIM sites and grouping 

of the sites based on similarities in loading characteristics or based on manual user selections. 

Grouped load spectra can be used to compute new NALS, such as NALS for user-defined truck 

weight road groups (TWRG). These NALS can be added to the USER_DEFINED_NALS table 

in the PLUG database and/or saved as DARWin-ME and/or NCHRP 1-37A MEPDG load 

distribution input files. 

To select ACTION #1, ACTION #2, or ACTION #3, click the radio button next to the desired 

action on the main menu and then click the “Select” button. 

Import Traffic Summaries to LTPP PLUG Database 

To import traffic summaries to the LTPP PLUG database, select ACTION #1 on the main menu 

and click the “Select” button (see figure 3). This action displays a data import form, shown in 

figure 4. 
55 

Figure 4. Screen capture. Data import form for importing traffic data summaries 

The current version of the PLUG database requires user-supplied data in the Microsoft® Access 

database tables. The database table format is described in appendix B. A blank database with 

preset table formats is available for download along with the LTPP PLUG software application 

from the LTPP Customer Support Service Center (e-mail: LTPPinfo@dot.gov, telephone: 

(202) 493-3035, or fax: (202) 493-3161.). 

To import data: 

1. Use the radio buttons at the top of the form to specify the source of traffic data: LTPP or 

user-supplied data. 

2. Use the check boxes in the middle of the form to select the tables (data summaries) that will 

be uploaded to the LTPP PLUG database: 

 DEFAULT_NALS—This table contains default NALS based on user-supplied or LTPP 

data. 

 DEFAULT_AxlesPerTruck—This table contains default axles per truck factors based on 

user-supplied or LTPP data. 

 SITE_SPECIFIC_NALS—This table contains representative site-specific NALS based 

on user-supplied or LTPP data. 
56 

 SITE_SPECIFIC_AxlesPerTruck—This table contains representative site-specific axles 

per truck factors based on user-supplied or LTPP data. 

 SITE_SPECIFIC_NVCD—This table contains normalized site-specific vehicle class 

distributions (classes 4 through 13) for sites with and without WIM data. 

 PLUG_W_FACTORS_FOR_RPPIF—This table contains damage factors for 

computation of the RPPIF statistic (MEPDG-based damaging potential). Users may 

supply their own damage factors. 

3. Click the “Import” button at the bottom of the screen to import data. 

To close the form, click the “Close” button at the bottom of the screen. 

Select NALS Source for MEPDG Use 

To select the source of NALS for MEPDG use, select ACTION #2 on the main menu and click 

the “Select” button (see figure 3). This action displays the form shown in figure 5. 

Figure 5. Screen capture. Select NALS source form for selecting loading inputs for 

MEPDG use 
57 

The LTPP PLUG provides three types of NALS for development of MEPDG axle loading 

distribution inputs: 

 OPTION #1: Site-Specific NALS. 

 OPTION #2: Default NALS. 

 OPTION #3: User-Defined NALS. 

Option #1 provides a graphical review and facilitates development of MEPDG axle loading input 

files using NALS computed for LTPP SPS TPF sites or any other NALS uploaded to the 

SITE_SPECIFIC_NALS table of the LTPP PLUG database. This option is recommended if the 

pavement analyst has determined that identified site-specific NALS are the best for the specific 

pavement design or analysis needs (see the LTPP PLUG report for guidance). 

Option #2 provides a graphical review and facilitates development of MEPDG axle loading input 

files using the Tier 1 global or Tier 2 default NALS based on LTPP data or any other default 

NALS uploaded by the user to the DEFAULT_NALS table. Tier 1 NALS are recommended 

where no site-specific information is available regarding truck loading conditions at the site in 

question. It assigns a loading condition computed as the average of the 26 SPS TPF NALS. 

Tier 2 NALS allow the user to apply knowledge about traffic loading at the site in question. 

Tier 2 NALS also are recommended for setting up sensitivity analyses through the selection of 

NALS representing different loading conditions (e.g., light versus heavy). If the Tier 2 option is 

selected, the user has two additional options: choosing all NALS manually or using the assisted 

interactive NALS assignment option that uses a decision tree algorithm to make NALS 

selections based on user responses. 

Option #3 provides a graphical review and facilitates development of MEPDG axle loading input 

files based on NALS included in the USER_DEFINED_NALS table, such as NALS representing 

different TWRGs. These NALS are the results of computations based on user-selected sitespecific NALS. 

To select the desired the NALS option, click the appropriate radio button and then click the 

“Select” button. 

Use the “Back” and “Close” buttons at the bottom of the screen to go back to the previous form 

or to close the form, respectively. 

Select Site-Specific NALS for MEPDG Use 

After selecting the site-specific NALS source from the options shown in figure 5, the user should 

click the “Select” button. This action displays the form shown in figure 6. This screen allows the 

user to view the NALS for each type of axle for each class of truck for a selected site (from the 

SITE_SPECIFIC_NALS table) to compare site-specific data with the defaults and to generate 

site-specific MEPDG axle load distribution files. 
58 

Figure 6. Screen capture. Review and generation of MEPDG input files for site-specific 

NALS 

A list of the sites for which NALS are available is displayed on the left side of the screen. To 

select a site, click its site ID in the list. Use scroll bars to see all available sites. To filter sites for 

a specific State, select from the “Select State” drop-down box displayed above the list. 

To the right of the site ID list is another list showing all available vehicle classes and axle types. 

Click a radio button in the “Plot” column to display a NALS plot for the corresponding vehicle 

class and axle type. One NALS may be selected/displayed at a time. 

To generate a MEPDG NALS input file, select the desired file format (*.alf and/or *.xml) at the 

bottom of the screen and click the “Generate” button. The MEPDG NALS input file(s) is saved 

to a user-specified directory. 

For the example shown in figure 7, Class 9 tandem axles have been selected for a non-LTPP site 

uploaded by the user to the SITE_SPECIFIC_NALS table. This NALS is displayed as a pink 

line. In addition, for comparison purposes, the user could display either Tier 1 default NALS 

(national average) or Tier 2 default NALS (“typical” default) for that type of axle and class of 

truck by selecting the appropriate radio buttons at the bottom of the form. The comparison NALS 

is displayed in blue. A text description of the NALS is provided in the box below the NALS plot. 
59 

Figure 7. Screen capture. Review of site-specific NALS 

Select Default NALS for MEPDG Use—Manual Selection 

If the Manual Selection option was selected (see figure 5), a screen displays like that shown in 

figure 8. This screen allows the user to select the default NALS for each type of axle for each 

class of truck. The same default type can be selected for all vehicle classes and axle types, or 

different defaults can be assigned to different vehicle classes and axle types. 
60 

Figure 8. Screen capture. Manual selection and generation of MEPDG input files using 

default NALS 

To apply the same default selection to all vehicle classes and axle types, choose the desired 

default type from the “Select default type” drop-down box. 

To apply a different default to a selected vehicle class and axle type, use the “Select default by 

class and axle” table shown on the left side of the screen. Identify the row with the desired 

vehicle class and axle type and use the drop-down box in the “Default Name” column to make a 

different default selection. 

To view NALS for the selected vehicle class and axle type, click the radio button for the 

appropriate “Plot.” (For example, in figure 8, Class 9 tandem axles have been selected.) 

To compare the selected default with either Tier 1 or Tier 2 default NALS for that type of axle 

and class of truck, click the appropriate radio buttons at the bottom of the form. These two 

default options provide means for comparing the manually selected alternative NALS with the 

default NALS. 

A text description of the NALS is provided in the box displayed below the NALS plot. 
61 

To generate a MEPDG NALS input file, select the desired file format (*.alf and/or *.xml) at the 

bottom left and click the “Generate” button. The MEPDG NALS input file(s) is saved to a userspecified directory. 

To compare all of the available alternative Tier 2 default NALS against the Tier 1 national 

average defaults, click the drop-down list for the desired class of trucks and type of axle in the 

“Default Name” column. These manual selections must be made for each class of vehicles and 

type of axles. The intent of this selection process is to allow the user to apply known information 

about the site loading conditions to select the NALS alternative that best describes these 

conditions. The user should step through each class of trucks and type of axles, comparing the 

alternative Tier 2 NALS against the Tier 1 default. 

For example, the user can compare the selected and default NALS to determine which is heavier. 

Figure 9 shows that the selected Tier 2 heavy (H2) NALS has a much higher percentage of heavy 

axles than the Tier 1 NALS. Thus, the Tier 2 heavy (H2) NALS for Class 7 tridem axles will 

cause the MEPDG software to predict more pavement damage than the Tier 1 global default. 

Figure 9. Screen capture. Review of manually selected default NALS 

Select Default NALS for MEPDG Use—Assisted, Interactive NALS Assignment 

If the user chooses the Assisted, Interactive NALS Assignment option (see figure 5), the 

software displays a screen that looks like that shown in figure 10. At the top of this screen, the 

user should identify the LTPP test site for which the NALS selection will apply. This could be 

any LTPP site that has truck volume by class information or any other site with truck volume by 
62 

class information added to the LTPP PLUG database table SITE_SPECIFIC_NVCD. The site ID 

is formed by using the numerical State Code ID and Strategic Highway Research Program 

(SHRP) ID, which together uniquely identify an LTPP site. The optional “State Filter” dropdown box at the top of the form allows the user to narrow the selection to a specific State. If no 

State name is selected, all sites available in the LTPP traffic database are displayed. 

Figure 10. Screen capture. Assisted, interactive assignment of default NALS 

For each of the identified dominant truck classes, the user is asked whether 50 percent or more of 

these trucks are empty or almost empty. If the user answers “Yes,” then the load spectrum best 

describing this loading condition is selected from the list of available defaults. If the user 

answers “No,” then a list of options with check boxes displays to help better define the expected 

loading condition. The following options are provided: 

 High percentage of loads in the dominant class close to the Federal legal weight limit. 

 High percentage of loads in the dominant class above the Federal legal weight limit due 

to permitted loads or illegal activity. 

 None of the above. 
63 

The first two options provide means to determine a likely shape of a heavy loading distribution 

that helps identify heavy NALS defaults. One or both of these options could be selected. If the 

user selects the “None of the above” option, a Tier 2 default “typical” distribution is used for the 

dominant vehicle class. 

If the user has no knowledge of the loading condition and specifies the “Don’t know” option on 

the form, a drop-down list displays to provide different road use options for the user to select. 

The number and type of entries in this list depends on the vehicle class. Each default has 

assigned road use recommendations in the LTPP PLUG database DEFAULT_NALS table. This 

list could be updated when new default NALS are added to the database or new road uses are 

identified for the LTPP Tier 2 NALS. 

This input screen is designed to accommodate up to two dominant classes. If the user wishes to 

identify additional heavily loaded vehicle classes, this can be done by selecting those additional 

classes at the bottom of the screen. 

When all questions have been answered and appropriate selections made on the form, click the 

“Next” button at the bottom of the screen. This displays a screen similar to the one shown in 

figure 8, except, unlike the manual selection of Tier 2 NALS, not all vehicle class and axle types 

are set to the “typical” (default) Tier 2 NALS conditions. Instead, the data entered for the 

dominant truck classes have been used to select specific Tier 2 NALS defaults. Also, vehicle 

classes and axle types that are likely to have a significant effect on pavement damage for the 

selected site will be colored black in the table displaying all available vehicle classes and axle 

types. 

The user may now review and change any or all of the cluster assignments for each class of 

vehicle and type of axle. Thus, even if this NALS selection option is used, the user may still 

manually apply information previously learned about trucking patterns at the test site. This 

screen also may be used to select other NALS to test the sensitivity of MEPDG outputs to 

different loading conditions. 

Select User-Defined NALS for MEPDG Use 

This option facilitates the review of NALS computed using ACTION #3 (View, group, and 

combine NALS from multiple WIM sites) provided in the LTPP PLUG software. Once userdefined NALS have been added to the LTPP PLUG database by executing ACTION #3, these 

NALS can be viewed by selecting “user-defined” as the NALS source from the options shown in 

figure 5 and clicking the “Select” button on that form. Clicking the “Select” button displays the 

form shown in figure 11. 
64 

Figure 11. Screen capture. Review of user-defined NALS 

This screen allows the user to view the NALS for each type of axle for each class of truck for a 

user-defined NALS, such as NALS computed for TWRGs (from the LTPP PLUG 

USER_DEFINED_NALS table), to compare user-defined NALS with the defaults, and to 

generate site-specific MEPDG axle load distribution files. The same user-defined NALS type 

can be selected for all vehicle classes and axle types, or different user-defined NALS types can 

be assigned to different vehicle classes and axle types. 

To apply the same user-defined NALS type to all vehicle classes and axle types, select the 

desired user-defined NALS type from the “Select user-defined NALS” drop-down box in the top 

left corner of the screen. 

To apply a different user-defined NALS type to a selected vehicle class and axle type, use the 

table shown on the left side of the screen. Identify the row with the desired vehicle class and axle 

type and click the appropriate drop-down box in the “User-Defined” column. 

To view user-defined NALS for the selected vehicle class and axle type, click the appropriate 

“Plot” button on the left of the screen. 

To compare the selected user-defined NALS with either Tier 1 or Tier 2 default NALS for that 

type of axle and class of truck, select the appropriate radio button at the bottom of the form. 

These two default options provide means for comparing user-defined NALS to the default 

NALS. 
65 

A text description of the NALS is provided in the box displayed below the NALS plot. 

To generate a MEPDG NALS input file, select the desired file format (*.alf and/or *.xml) and 

click the “Generate” button. The MEPDG NALS input file(s) is saved to a user-specified 

directory. 

Generate MEPDG NALS Input Files 

Functionality to generate the MEPDG NALS input file is provided for each “Select NALS for 

MEPDG Use” option. The button to generate MEPDG NALS input files is located at the bottom 

left corner of the “Review NALS and Generate Input Files” form presented in figure 9. MEPDG 

axle load spectra files are developed automatically by a software routine using two of the file 

formats supported by DARWin-ME: *.alf and *.xml. Files are saved to a user-specified 

directory. To execute this function, select the file format and click the “Generate” button. The 

NALS selection displayed in the table located above the “Generate” button will be used in the 

development of the MEPDG NALS input file. 

View, Group, and Combine NALS from Multiple WIM Sites 

To view, group, and combine NALS from multiple WIM sites, select ACTION #3 on the main 

menu and click the “Select” button (see figure 3). This action displays the data import form 

shown in figure 12. 
66 

Figure 12. Screen capture. View, group, and combine NALS from multiple WIM sites 

A list of the sites for which NALS are available is displayed on the left side of the screen. To 

filter sites for a specific State, select from the “Select State” drop-down box displayed above the 

site list. To select the sites for comparison and viewing of NALS, select the site IDs displayed in 

the list. Hold the Ctrl or Shift key to select multiple sites. Use scroll bars to see all available sites. 

Click the “Select” button under the site ID list to apply the selection. 

To the right of the site ID list is a list of all available vehicle classes and axle types. Click a radio 

button in the “Plot” column to display a NALS plot for the corresponding vehicle class and axle 

type. One class and axle combination may be selected at a time. 

If site selection has been changed, click the “Plot” button at the bottom of the table to refresh the 

plot for the selected class and axle. 

The site IDs for the selected sites display in a table located under the axle load spectra plot. Site 

IDs display in different columns depending on the percentages of heavy axles or the damaging 

potential of the axle load spectrum. Use this information to group sites with similar loading 

conditions. To change the method for grouping load spectra, click the radio buttons displayed 

above the table to specify the statistical parameter used for grouping: “% of Heavy Loads” or 

“Damage Potential (RPPIF).” 
67 

Vehicle classes and axle types that are likely to have a significant effect on pavement damage for 

the selected site(s) are colored black; purple indicates that the selected class-axle combination is 

likely to have a significant effect for some but not all of the selected sites. This determination is 

made based on vehicle class distributions and axle load spectra for the selected sites. 

In addition to site-specific load spectra, default load spectra can be displayed using the radio 

buttons at the bottom of the screen. 

To narrow down site selection or plot only a few sites at a time, hold the Shift or Ctrl key to 

highlight site IDs in the table below the load spectra plot and click the “Re-plot for highlighted 

sites” button. 

To record average NALS for sites displayed in the table below the load spectra plot, and to 

generate MEPDG load distribution files, click the “Record/Compute NALS” button at the 

bottom of the screen. 

Compute and Record User-Defined NALS for Groups of Sites 

This function facilitates development of user-defined NALS by vehicle class and axle type. This 

is accomplished by grouping sites with similar loading conditions, or based on manual selection 

of site IDs, and computing average NALS for each group of sites. Groupings are performed for 

the sites selected by the user on the “View, group, and combine NALS from multiple WIM sites” 

screen (see figure 12). Click the “Record/Compute NALS” button on that form to display a form 

containing the selected sites, as shown in figure 13. 
68 

Figure 13. Screen capture. Compute and record user-defined NALS. 

This form shows instructions for four steps and a table at the bottom of the form populated with 

the site IDs selected on the previous screen. The site IDs are placed in different columns of the 

table based on axle loading conditions observed for the selected vehicle class and axle type. 

The LTPP PLUG provides multiple options for computation of average NALS for the selected 

group of sites. Step 1 on the form asks the user to select whether site selection for computation of 

average NALS should apply to: 

 Selected vehicle class and axle type only. 

 Selected vehicle class, all axle types. 

 All vehicle classes and axle types. 

It is recommended that the loading conditions observed for the dominant vehicle class are used 

as the basis for grouping of sites, at least to develop alternative NALS for that vehicle class. For 

the light vehicle classes and axle types that do not contribute much to the total loading, all sites 

may be combined to compute an average NALS. In some circumstances, where several heavy 

vehicle types are well represented on the road or loading conditions observed for different 
69 

vehicle classes are different (for example, for a road with moderate Class 9 trucks and very 

heavy Class 7 trucks), it is recommended that NALS alternatives are computed based on 

grouping of sites for individual vehicle classes and axle types. 

Step 2 offers the following options for grouping the sites for computation of the average NALS 

for each group: 

 By combining NALS for the sites highlighted in the table. 

 By combining NALS for all the sites displayed in the table. 

 For each loading condition specified in the table header. 

To change the selection of sites for grouping, highlight the desired site IDs in the table by 

clicking them. Use Shift or Ctrl key to select multiple sites. 

Step 3 asks the user to select the output format from the following options: 

 Database table (USER_DEFINED_NALS). 

 MEPDG *.alf file. 

 DARWin-ME *.xml file. 

In step 4, the user is asked to provide several characteristics for the average NALS being 

computed based on user selection, including: 

 Label to use in the LTPP PLUG database USER_DEFINED_NALS table or in *.alf and 

*.xml file names to identify computed NALS. 

 Description of the computed NALS (what loading condition or group of roads this NALS 

represents). 

 Recommended road use (for which roads this new NALS is recommended). 

After steps 1 through 4 have been completed, click the “Generate NALS” button to compute and 

save the new user-defined NALS. If NALS have been written to the USER_DEFINED_NALS 

table of the LTPP PLUG database, use Option #3 of the “Select NALS Source for MEPDG Use” 

form (see figure 5) to view the computed NALS. 

Click the “Close” button to close the form. 

71 

APPENDIX B: LTPP PLUG DATABASE DATA DICTIONARY 

This appendix provides a data dictionary containing field names and descriptions for the tables 

included in the LTPP PLUG database. This information can aid in understanding the data in the 

database tables and to facilitate uploading of the additional information (LTPP updates or Statespecific information) to the database tables. 

Listed below are brief descriptions of the tables present in the database: 

 ALF_DEFAULT_ALS and ALF_Gen_Axle_Group—These tables are used internally by 

the LTPP PLUG software to generate *.alf files. Table 21 and table 22 contain the field 

names and descriptions. 

 DEFAULT_AxlesPerTruck—This table contains default APCs based on all applicable 

SPS TPF data. Table 23 contains the field names and descriptions. 

 DEFAULT_NALS—This table contains Tier 1 or Tier 2 NALS defaults, based on all 

applicable SPS TPF data or user-defined defaults. Table 24 contains the field names and 

descriptions. 

 LTPP_CODES—This table, imported from the LTPP LTAS database, contains numeric 

codes and names for all the States and Provinces in the United States and Canada. Table 

25 contains the field names and descriptions. 

 PLUG_LEF_FOR_ESAL—This table contains load equivalency factors by axle type and 

is used for Percentage of Total Load (ESAL) computations. Table 26 contains the field 

names and descriptions. 

 PLUG_W_FACTORS_FOR_RPPIF—This table contains W-factors by axle type and is 

used for Percentage of Total Load (RPPIF) computations. Table 27 contains the field 

names and descriptions. 

 SITE_SPECIFIC_AxlesPerTruck—This table contains APCs for each site. Table 28 

contains the field names and descriptions. 

 SITE_SPECIFIC_NALS—This table contains representative annual NALS for each SPS 

TPF or user-supplied site. Table 29 contains the field names and descriptions. 

 SITE_SPECIFIC_NVCD—This table contains the normalized vehicle class distribution 

for the most recent year for all SPS and GPS sites or user-supplied sites. Table 30 

contains the field names and descriptions. 

 USER_DEFINED_NALS—This table contains user-defined NALS based on the 

computation performed under Action 3 of the LTPP PLUG software (multiple sites 

selection and computation of NALS). Table 31 contains the field names and descriptions. 
72 

 XMLGen_AxleLoadDistribution, XMLGen_AxleLoadMain_Template, and 

XMLGen_DEFAULT_NALS_By_Loading_Cluster—These tables are used internally by 

the LTPP PLUG software to generate DARWin-ME *.xml files. Table 32 through table 

34 contain the field names and descriptions. 

 
73 

Table 21. Field names and descriptions for ALF_DEFAULT_ALS 

Field Name Data Type Description 

Month NUMBER(2,0) Code specifying the month in text format (January–December) 

Veh_Class NUMBER(2,0) 

Code indicating the 13-bin classification into which trucks have been 

grouped 

Sum_Axles NUMBER(3,0) A constant value of 100 populated in each record for ALF file generation 

Axle_Group NUMBER(1,0) Type of axle for which these percentages of axles apply 

Table 22. Field names and descriptions for ALF_Gen_Axle_Group 

Field Name Data Type Description 

Veh_Class NUMBER(2,0) 

Code indicating the 13-bin classification into which trucks have been 

grouped 

Axle_Group NUMBER(1,0) Type of axle for which these percentages of axles apply 

Table 23. Field names and descriptions for DEFAULT_AxlesPerTruck 

Field Name Data Type Description 

classNumber NUMBER(2,0) 

Code indicating the 13-bin classification into which trucks have been 

grouped 

numberAxle NUMBER(1,0) 

Type of axle for which the values in the field “truckAxleConfig” 

apply 

truckAxleConfig NUMBER(2,2) Number of this type of axle for a vehicle in this class 

Table 24. Field names and descriptions for DEFAULT_NALS 

Field Name Data Type Description 

VEH_CLASS NUMBER(2,0) 

Code indicating the 13-bin classification into which trucks have been 

grouped 

AXLE_GROUP NUMBER(1,0) Type of axle for which these percentages of axles apply 

NALS_CLUSTERS VARCHAR2(255) Text field indicating the type of NALS cluster 

MEPDG_LG01 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 0–2,999 lb for single 

axles; 0–5,999 lb for tandem axles; 0–11,999 lb for tridem and quad 

axles. 

MEPDG_LG02 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 3,000–3,999 lb for 

single axles; 6,000–7,999 lb for tandem axles; 12,000–14,999 lb for 

tridem and quad axles. 

MEPDG_LG03 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 4,000–4,999 lb for 

single axles; 8,000–9,999 lb for tandem axles; 15,000–17,999 lb for 

tridem and quad axles 

MEPDG_LG04 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 5,000–5,999 lb for 

single axles; 10,000–11,999 lb for tandem axles; 18,000–20,999 lb for 

tridem and quad axles 

MEPDG_LG05 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 6,000–6,999 lb for 

single axles; 12,000–13,999 lb for tandem axles; 21,000–23,999 lb for 

tridem and quad axles 

MEPDG_LG06 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 7,000–7,999 lb for 

single axles; 14,000–15,999 lb for tandem axles; 24,000–26,999 lb for 

tridem and quad axles 

MEPDG_LG07 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 8,000–8,999 lb for 

single axles; 16,000–17,999 lb for tandem axles; 27,000–29,999 lb for 

tridem and quad axles 

MEPDG_LG08 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 9,000–9,999 lb for 

single axles; 18,000–19,999 lb for tandem axles; 30,000–32,999 lb for 

tridem and quad axles 
74 

Field Name Data Type Description 

MEPDG_LG09 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 10,000–10,999 lb for 

single axles; 20,000–21,999 lb for tandem axles; 33,000–35,999 lb for 

tridem and quad axles 

MEPDG_LG10 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 11,000–11,999 lb for 

single axles; 22,000–23,999 lb for tandem axles; 36,000–38,999 lb for 

tridem and quad axles 

MEPDG_LG11 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 12,000–12,999 lb for 

single axles; 24,000–25,999 lb for tandem axles; 39,000–41,999 lb for 

tridem and quad axles 

MEPDG_LG12 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 13,000–13,999 lb for 

single axles; 26,000–27,999 lb for tandem axles; 42,000–44,999 lb for 

tridem and quad axles 

MEPDG_LG13 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 14,000–14,999 lb for 

single axles; 28,000–29,999 lb for tandem axles; 45,000–47,999 lb for 

tridem and quad axles 

MEPDG_LG14 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 15,000–15,999 lb for 

single axles; 30,000–31,999 lb for tandem axles; 48,000–50,999 lb for 

tridem and quad axles 

MEPDG_LG15 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 16,000–16,999 lb for 

single axles; 32,000–33,999 lb for tandem axles; 51,000–53,999 lb for 

tridem and quad axles 

MEPDG_LG16 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 17,000–17,999 lb for 

single axles; 34,000–35,999 lb for tandem axles; 54,000–56,999 lb for 

tridem and quad axles 

MEPDG_LG17 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 18,000–18,999 lb for 

single axles; 36,000–37,999 lb for tandem axles; 57,000–59,999 lb for 

tridem and quad axles 

MEPDG_LG18 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 19,000–19,999 lb for 

single axles; 38,000–39,999 lb for tandem axles; 60,000–62,999 lb for 

tridem and quad axles 

MEPDG_LG19 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 20,000–20,999 lb for 

single axles; 40,000–41,999 lb for tandem axles; 63,000–65,999 lb for 

tridem and quad axles 

MEPDG_LG20 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 21000–21999 lb for 

single axles; 42,000–43,999 lb for tandem axles; 66,000–68,999 lb for 

tridem and quad axles 

MEPDG_LG21 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 22,000–22,999 lb for 

single axles; 44,000–45,999 lb for tandem axles; 69,000–71,999 lb for 

tridem and quad axles 

MEPDG_LG22 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 23,000–23,999 lb for 

single axles; 46,000–47,999 lb for tandem axles; 72,000–74,999 lb for 

tridem and quad axles 

MEPDG_LG23 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 24,000–24,999 lb for 

single axles; 48,000–49,999 lb for tandem axles; 75,000–77,999 lb for 

tridem and quad axles 

MEPDG_LG2,4 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 25,000–25,999 lb for 

single axles; 50,000–51,999 lb for tandem axles; 78,000–80,999 lb for 

tridem and quad axles 

MEPDG_LG25 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 26,000–26,999 lb for 

single axles; 52,000–53,999 lb for tandem axles; 81,000–83,999 lb for 

tridem and quad axles 

MEPDG_LG26 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 27,000–27,999 lb for 

single axles; 54,000–55,999 lb for tandem axles; 84,000–86,999 lb for 

tridem and quad axles 
75 

Field Name Data Type Description 

MEPDG_LG27 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 28,000–28,999 lb for 

single axles; 56,000–57,999 lb for tandem axles; 87,000–89,999 lb for 

tridem and quad axles 

MEPDG_LG28 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 29,000–29,999 lb for 

single axles; 58,000–59,999 lb for tandem axles; 90000–92,999 lb for 

tridem and quad axles 

MEPDG_LG29 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 30,000–30,999 lb for 

single axles; 60,000–61,999 lb for tandem axles; 93,000–95,999 lb for 

tridem and quad axles 

MEPDG_LG30 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 31,000–31,999 lb for 

single axles; 62,000–63,999 lb for tandem axles; 96,000–98,999 lb for 

tridem and quad axles 

MEPDG_LG31 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 32,000–32,999 lb for 

single axles; 64,000–65,999 lb for tandem axles; 99,000–101,999 lb 

for tridem and quad axles 

MEPDG_LG32 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 33,000–33,999 lb for 

single axles; 66,000–67,999 lb for tandem axles 

MEPDG_LG33 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 34,000–34,999 lb for 

single axles; 68,000–69,999 lb for tandem axles 

MEPDG_LG34 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 35,000–35,999 lb for 

single axles; 70,000–71,999 lb for tandem axles 

MEPDG_LG35 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 36,000–36,999 lb for 

single axles; 72,000–73,999 lb for tandem axles 

MEPDG_LG36 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 37,000–37,999 lb for 

single axles; 74,000–75,999 lb for tandem axles 

MEPDG_LG37 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 38,000–38,999 lb for 

single axles; 76,000–77,999 lb for tandem axles 

MEPDG_LG38 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 39,000–39,999 lb for 

single axles; 78,000–79,999 lb for tandem axles 

MEPDG_LG39 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 40,000–40,999 lb for 

single axles; 80,000–81,999 lb for tandem axles 

Description VARCHAR2(255) Text description for NALS_CLUSTERS field 

Recommended_Road

_Usage VARCHAR2(255) 

Text description indicating the recommended road usage for the 

selected cluster 

Table 25. Field names and descriptions for LTPP_CODES 

Field Name Data Type Description 

CODETYPE VARCHAR2(40) Name assigned to a set of codes for a field in another table 

CODE NUMBER(2,0) Unique text value whose meaning is defined in CODES.DETAIL 

DETAIL VARCHAR2(200) Textual description defining the meaning of the code 

ADDL_CODE VARCHAR2(2) 

Additional code needed to uniquely define the meaning of a code. For 

example, both State and county code are needed to uniquely identify a 

county 

ADDL_CODETYPE VARCHAR2(20) Codetype of the code entered in the ADDL_CODE field 
76 

Table 26. Field names and descriptions for PLUG_LEF_FOR_ESAL 

Field Name Data Type Description 

PAVEMENT_TYPE VARCHAR2(255) Code indicating pavement type 

AXLE_TYPE NUMBER(1,0) Type of axle for which these values apply 

AX_01 NUMBER(2,20) 

LEF for axles in bin with mid-point weight equal to 0.5 times 

WEIGHT_BIN_SIZE 

AX_02 NUMBER(2,20) 

LEF for axles in bin with mid-point weight equal to 1.5 times 

WEIGHT_BIN_SIZE 

AX_03 NUMBER(2,20) 

LEF for axles in bin with mid-point weight equal to 3.5 times 

WEIGHT_BIN_SIZE 

AX_04 NUMBER(2,20) 

LEF for axles in bin with mid-point weight equal to 4.5 times 

WEIGHT_BIN_SIZE 

AX_05 NUMBER(2,20) 

LEF for axles in bin with mid-point weight equal to 5.5 times 

WEIGHT_BIN_SIZE 

AX_06 NUMBER(2,20) 

LEF for axles in bin with mid-point weight equal to 6.5 times 

WEIGHT_BIN_SIZE 

AX_07 NUMBER(2,20) 

LEF for axles in bin with mid-point weight equal to 7.5 times 

WEIGHT_BIN_SIZE 

AX_08 NUMBER(2,20) 

LEF for axles in bin with mid-point weight equal to 8.5 times 

WEIGHT_BIN_SIZE 

AX_09 NUMBER(2,20) 

LEF for axles in bin with mid-point weight equal to 9.5 times 

WEIGHT_BIN_SIZE 

AX_10 NUMBER(2,20) 

LEF for axles in bin with mid-point weight equal to 10.5 times 

WEIGHT_BIN_SIZE 

AX_11 NUMBER(2,20) 

LEF for axles in bin with mid-point weight equal to 11.5 times 

WEIGHT_BIN_SIZE 

AX_12 NUMBER(2,20) 

LEF for axles in bin with mid-point weight equal to 12.5 times 

WEIGHT_BIN_SIZE 

AX_13 NUMBER(2,20) 

LEF for axles in bin with mid-point weight equal to 13.5 times 

WEIGHT_BIN_SIZE 

AX_14 NUMBER(2,20) 

LEF for axles in bin with mid-point weight equal to 14.5 times 

WEIGHT_BIN_SIZE 

AX_15 NUMBER(2,20) 

LEF for axles in bin with mid-point weight equal to 15.5 times 

WEIGHT_BIN_SIZE 

AX_16 NUMBER(2,20) 

LEF for axles in bin with mid-point weight equal to 16.5 times 

WEIGHT_BIN_SIZE 

AX_17 NUMBER(2,20) 

LEF for axles in bin with mid-point weight equal to 17.5 times 

WEIGHT_BIN_SIZE 

AX_18 NUMBER(2,20) 

LEF for axles in bin with mid-point weight equal to 18.5 times 

WEIGHT_BIN_SIZE 

AX_19 NUMBER(2,20) 

LEF for axles in bin with mid-point weight equal to 19.5 times 

WEIGHT_BIN_SIZE 

AX_20 NUMBER(2,20) 

LEF for axles in bin with mid-point weight equal to 20.5 times 

WEIGHT_BIN_SIZE 

AX_21 NUMBER(2,20) 

LEF for axles in bin with mid-point weight equal to 21.5 times 

WEIGHT_BIN_SIZE 

AX_22 NUMBER(2,20) 

LEF for axles in bin with mid-point weight equal to 22.5 times 

WEIGHT_BIN_SIZE 

AX_23 NUMBER(2,20) 

LEF for axles in bin with mid-point weight equal to 23.5 times 

WEIGHT_BIN_SIZE 

AX_24 NUMBER(2,20) 

LEF for axles in bin with mid-point weight equal to 24.5 times 

WEIGHT_BIN_SIZE 

AX_25 NUMBER(2,20) 

LEF for axles in bin with mid-point weight equal to 25.5 times 

WEIGHT_BIN_SIZE 
77 

Field Name Data Type Description 

AX_26 NUMBER(2,20) 

LEF for axles in bin with mid-point weight equal to 26.5 times 

WEIGHT_BIN_SIZE 

AX_27 NUMBER(2,20) 

LEF for axles in bin with mid-point weight equal to 27.5 times 

WEIGHT_BIN_SIZE 

AX_28 NUMBER(2,20) 

LEF for axles in bin with mid-point weight equal to 28.5 times 

WEIGHT_BIN_SIZE 

AX_29 NUMBER(2,20) 

LEF for axles in bin with mid-point weight equal to 29.5 times 

WEIGHT_BIN_SIZE 

AX_30 NUMBER(2,20) 

LEF for axles in bin with mid-point weight equal to 30.5 times 

WEIGHT_BIN_SIZE 

AX_31 NUMBER(2,20) 

LEF for axles in bin with mid-point weight equal to 31.5 times 

WEIGHT_BIN_SIZE 

AX_32 NUMBER(2,20) 

LEF for axles in bin with mid-point weight equal to 32.5 times 

WEIGHT_BIN_SIZE 

AX_33 NUMBER(2,20) 

LEF for axles in bin with mid-point weight equal to 33.5 times 

WEIGHT_BIN_SIZE 

AX_34 NUMBER(2,20) 

LEF for axles in bin with mid-point weight equal to 34.5 times 

WEIGHT_BIN_SIZE 

AX_35 NUMBER(2,20) 

LEF for axles in bin with mid-point weight equal to 35.5 times 

WEIGHT_BIN_SIZE 

AX_36 NUMBER(2,20) 

LEF for axles in bin with mid-point weight equal to 36.5 times 

WEIGHT_BIN_SIZE 

AX_37 NUMBER(2,20) 

LEF for axles in bin with mid-point weight equal to 37.5 times 

WEIGHT_BIN_SIZE 

AX_38 NUMBER(2,20) 

LEF for axles in bin with mid-point weight equal to 38.5 times 

WEIGHT_BIN_SIZE 

AX_39 NUMBER(2,20) 

LEF for axles in bin with mid-point weight equal to 39.5 times 

WEIGHT_BIN_SIZE 

AX_40 NUMBER(2,20) 

LEF for axles in bin with mid-point weight equal to 40.5 times 

WEIGHT_BIN_SIZE 

AX_41 NUMBER(2,20) 

LEF for axles in bin with mid-point weight equal to 41.5 times 

WEIGHT_BIN_SIZE 

WEIGHT_BIN_SIZE NUMBER(4,0) 

Value of the increment for a bin for the axle type as loaded. 1,000 for 

single axles; 2,000 for tandem axles; 3,000 for tridem axles; 3,000 or 

4,000 for quad axles, depending on the software version used to load 

the data 

Table 27. Field names and descriptions for PLUG_W_FACTORS_FOR_RPPIF 

Field Name Data Type Description 

Axle_Type NUMBER(1, 0) Type of axle for which these W-factors apply 

AX_CT_01 NUMBER(2,20) 

W-factors for axles whose weight falls in the lowest bin 0–999 lb for 

single axles; 0–1,999 lb for tandem axles; 0–2,999 lb for tridem and 

quad axles 

AX_CT_02 NUMBER(2,20) 

W-factors for axles whose weight falls in the lowest bin 1,000–1,999 

lb for single axles; 2,000–3,999 lb for tandem axles; 3,000–5,999 lb for 

tridem and quad axles 

AX_CT_03 NUMBER(2,20) 

W-factors for axles whose weight falls in the lowest bin 

2,000–2,999 lb for single axles; 4,000–5,999 lb for tandem axles; 

6,000–8,999 lb for tridem and quad axles 

AX_CT_04 NUMBER(2,20) 

W-factors for axles whose weight falls in the lowest bin 

3,000–3,999 lb for single axles; 6,000–7,999 lb for tandem axles; 

9,000–11,999 lb for tridem and quad axles 
78 

Field Name Data Type Description 

AX_CT_05 NUMBER(2,20) 

W-factors for axles whose weight falls in the lowest bin 

4,000–4,999 lb for single axles; 8,000–9,999 lb for tandem axles; 

12,000–14,999 lb for tridem and quad axles 

AX_CT_06 NUMBER(2,20) 

W-factors for axles whose weight falls in the lowest bin 

5,000–5,999 lb for single axles; 10,000–11,999 lb for tandem axles; 

15,000–17,999 lb for tridem and quad axles 

AX_CT_07 NUMBER(2,20) 

W-factors for axles whose weight falls in the lowest bin 

6,000–6,999 lb for single axles; 12,000–13,999 lb for tandem axles; 

18,000–20,999 lb for tridem and quad axles 

AX_CT_08 NUMBER(2,20) 

W-factors for axles whose weight falls in the lowest bin 

7,000–7,999 lb for single axles; 14,000–15,999 lb for tandem axles; 

21,000–23,999 lb for tridem and quad axles 

AX_CT_09 NUMBER(2,20) 

W-factors for axles whose weight falls in the lowest bin 8,000–8,999 

lb for single axles; 16,000–17,999 lb for tandem axles; 24,000–26,999 

lb for tridem and quad axles 

AX_CT_10 NUMBER(2,20) 

W-factors for axles whose weight falls in the lowest bin 

9,000–9,999 lb for single axles; 18,000–19,999 lb for tandem axles; 

27,000–29,999 lb for tridem and quad axles 

AX_CT_11 NUMBER(2,20) 

W-factors for axles whose weight falls in the lowest bin 

10,000–10,999 lb for single axles; 20,000–21,999 lb for tandem axles; 

30,000–32,999 lb for tridem and quad axles 

AX_CT_12 NUMBER(2,20) 

W-factors for axles whose weight falls in the lowest bin 

11,000–11,999 lb for single axles; 22,000–23,999 lb for tandem axles; 

33,000–35,999 lb for tridem and quad axles 

AX_CT_13 NUMBER(2,20) 

W-factors for axles whose weight falls in the lowest bin 

12,000–12,999 lb for single axles; 24,000–25,999 lb for tandem axles; 

36,000–38,999 lb for tridem and quad axles 

AX_CT_14 NUMBER(2,20) 

W-factors for axles whose weight falls in the lowest bin 

13,000–13,999 lb for single axles; 26,000–27,999 lb for tandem axles; 

39,000–41,999 lb for tridem and quad axles 

AX_CT_15 NUMBER(2,20) 

W-factors for axles whose weight falls in the lowest bin 

14,000–14,999 lb for single axles; 28,000–29,999 lb for tandem axles; 

42,000–44,999 lb for tridem and quad axles 

AX_CT_16 NUMBER(2,20) 

W-factors for axles whose weight falls in the lowest bin 

15,000–15,999 lb for single axles; 30,000–31,999 lb for tandem axles; 

45,000–47,999 lb for tridem and quad axles 

AX_CT_17 NUMBER(2,20) 

W-factors for axles whose weight falls in the lowest bin 

16,000–16,999 lb for single axles; 32,000–33,999 lb for tandem axles; 

48,000–50,999 lb for tridem and quad axles 

AX_CT_18 NUMBER(2,20) 

W-factors for axles whose weight falls in the lowest bin 

17,000–17,999 lb for single axles; 34,000–35,999 lb for tandem axles; 

51,000–53,999 lb for tridem and quad axles 

AX_CT_19 NUMBER(2,20) 

W-factors for axles whose weight falls in the lowest bin 

18,000–18,999 lb for single axles; 36,000–37,999 lb for tandem axles; 

54,000–56,999 lb for tridem and quad axles 

AX_CT_20 NUMBER(2,20) 

W-factors for axles whose weight falls in the lowest bin 

19,000–19,999 lb for single axles; 38,000–39,999 lb for tandem axles; 

57,000–59,999 lb for tridem and quad axles 

AX_CT_21 NUMBER(2,20) 

W-factors for axles whose weight falls in the lowest bin 

20000–20999 lb for single axles; 40,000–41,999 lb for tandem axles; 

60,000–62,999 lb for tridem and quad axles 

AX_CT_22 NUMBER(2,20) 

W-factors for axles whose weight falls in the lowest bin 

21,000–21,999 lb for single axles; 42,000–43,999 lb for tandem axles; 

63,000–65,999 lb for tridem and quad axles 
79 

Field Name Data Type Description 

AX_CT_23 NUMBER(2,20) 

W-factors for axles whose weight falls in the lowest bin 

22000–22999 lb for single axles; 44,000–45,999 lb for tandem axles; 

66,000–68,999 lb for tridem and quad axles 

AX_CT_24 NUMBER(2,20) 

W-factors for axles whose weight falls in the lowest bin 

23,000–23,999 lb for single axles; 46,000–47,999 lb for tandem axles; 

69,000–71,999 lb for tridem and quad axles 

AX_CT_25 NUMBER(2,20) 

W-factors for axles whose weight falls in the lowest bin 

24,000–24,999 lb for single axles; 48,000–49,999 lb for tandem axles; 

72,000–74,999 lb for tridem and quad axles 

AX_CT_26 NUMBER(2,20) 

W-factors for axles whose weight falls in the lowest bin 

25,000–25,999 lb for single axles; 50,000–51,999 lb for tandem axles; 

75,000–77,999 lb for tridem and quad axles 

AX_CT_27 NUMBER(2,20) 

W-factors for axles whose weight falls in the lowest bin 

26,000–26,999 lb for single axles; 52,000–53,999 lb for tandem axles; 

78,000–80,999 lb for tridem and quad axles 

AX_CT_28 NUMBER(2,20) 

W-factors for axles whose weight falls in the lowest bin 

27,000–27,999 lb for single axles; 54,000–55,999 lb for tandem axles; 

81,000–83,999 lb for tridem and quad axles 

AX_CT_29 NUMBER(2,20) 

W-factors for axles whose weight falls in the lowest bin 

28,000–28,999 lb for single axles; 56,000–57,999 lb for tandem axles; 

84,000–86,999 lb for tridem and quad axles 

AX_CT_30 NUMBER(2,20) 

W-factors for axles whose weight falls in the lowest bin 

29,000–29,999 lb for single axles; 58,000–59,999 lb for tandem axles; 

87,000–89,999 lb for tridem and quad axles 

AX_CT_31 NUMBER(2,20) 

W-factors for axles whose weight falls in the lowest bin 

30,000–30,999 lb for single axles; 60,000–61,999 lb for tandem axles; 

90,000–92,999 lb for tridem and quad axles 

AX_CT_32 NUMBER(2,20) 

W-factors for axles whose weight falls in the lowest bin 

31,000–31,999 lb for single axles; 62,000–63,999 lb for tandem axles; 

93,000–95,999 lb for tridem and quad axles 

AX_CT_33 NUMBER(2,20) 

W-factors for axles whose weight falls in the lowest bin 

32,000–32,999 lb for single axles; 64,000–65,999 lb for tandem axles; 

96,000–98,999 lb for tridem and quad axles 

AX_CT_34 NUMBER(2,20) 

W-factors for axles whose weight falls in the lowest bin 

33,000–33,999 lb for single axles; 66,000–67,999 lb for tandem axles; 

99,000–101,999 lb for tridem and quad axles 

AX_CT_35 NUMBER(2,20) 

W-factors for axles whose weight falls in the lowest bin 

34,000–34,999 lb for single axles; 68,000–69,999 lb for tandem axles; 

102,000–104,999 lb for tridem and quad axles 

AX_CT_36 NUMBER(2,20) 

W-factors for axles whose weight falls in the lowest bin 

35,000–35,999 lb for single axles; 70,000–71,999 lb for tandem axles; 

105,000–107,999 lb for tridem and quad axles 

AX_CT_37 NUMBER(2,20) 

W-factors for axles whose weight falls in the lowest bin 

36,000–36,999 lb for single axles; 72,000–73,999 lb for tandem axles; 

108,000–110,999 lb for tridem and quad axles 

AX_CT_38 NUMBER(2,20) 

W-factors for axles whose weight falls in the lowest bin 

37,000–37,999 lb for single axles; 74,000–75,999 lb for tandem axles; 

111,000–113,999 lb for tridem and quad axles 

AX_CT_39 NUMBER(2,20) 

W-factors for axles whose weight falls in the lowest bin 

38,000–38,999 lb for single axles; 76,000–77,999 lb for tandem axles; 

114,000–116,999 lb for tridem and quad axles 

AX_CT_40 NUMBER(2,20) 

W-factors for axles whose weight falls in the lowest bin 

39,000–39,999 lb for single axles; 78,000–79,999 lb for tandem axles; 

117,000–119,999 lb for tridem and quad axles 
80 

Table 28. Field names and descriptions for SITE_SPECIFIC_AxlesPerTruck 

Field Name Data Type Description 

STATE_CODE NUMBER(2,0) 

Numerical code for State or Province. U.S. codes are consistent with 

Federal Information Processing Standards 

SHRP_ID VARCHAR2(255) 

Test section identification number assigned by LTPP program. Must 

be combined with STATE_CODE to be unique 

classNumber NUMBER(2,0) 

Code indicating the 13-bin classification into which trucks have been 

grouped 

numberAxle NUMBER(1,0) 

Type of axle for which the values in the field “truckAxleConfig” 

apply 

truckAxleConfig NUMBER(1,2) Number of this type of axle for a vehicle in this class 

Table 29. Field names and descriptions for SITE_SPECIFIC_NALS 

Field Name Data Type Description 

STATE_CODE NUMBER(2,0) 

Numerical code for State or Province. U.S. codes are consistent with 

Federal Information Processing Standards 

SHRP_ID VARCHAR2(255) 

Test section identification number assigned by LTPP program. Must 

be combined with STATE_CODE to be unique 

VEH_CLASS NUMBER(2,0) 

Code indicating the 13-bin classification into which trucks have been 

grouped 

AXLE_GROUP NUMBER(1,0) Type of axle for which these percentages of axles apply 

MEPDG_LG01 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 0–2,999 lb for single 

axles; 0–5,999 lb for tandem axles; 0–11,999 lb for tridem and quad 

axles 

MEPDG_LG02 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 3,000–3,999 lb for 

single axles; 6,000–7,999 lb for tandem axles; 12,000–14,999 lb for 

tridem and quad axles 

MEPDG_LG03 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 4,000–4,999 lb for 

single axles; 8,000–9,999 lb for tandem axles; 15,000–17,999 lb for 

tridem and quad axles 

MEPDG_LG04 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 5,000–5,999 lb for 

single axles; 10,000–11,999 lb for tandem axles; 18,000–20,999 lb for 

tridem and quad axles 

MEPDG_LG05 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 6,000–6,999 lb for 

single axles; 12,000–13,999 lb for tandem axles; 21,000–23,999 lb for 

tridem and quad axles 

MEPDG_LG06 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 7,000–7,999 lb for 

single axles; 14,000–15,999 lb for tandem axles; 24,000–26,999 lb for 

tridem and quad axles 

MEPDG_LG07 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 8,000–8,999 lb for 

single axles; 16,000–17,999 lb for tandem axles; 27,000–2,9999 lb for 

tridem and quad axles 

MEPDG_LG08 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 9,000–9,999 lb for 

single axles; 18,000–19,999 lb for tandem axles; 30,000–32,999 lb for 

tridem and quad axles 

MEPDG_LG09 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 10,000–10,999 lb for 

single axles; 20,000–21,999 lb for tandem axles; 33,000–35,999 lb for 

tridem and quad axles 

MEPDG_LG10 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 11,000–11,999 lb for 

single axles; 22,000–23,999 lb for tandem axles; 36,000–38,999 lb for 

tridem and quad axles 
81 

Field Name Data Type Description 

MEPDG_LG11 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 12,000–12,999 lb for 

single axles; 24,000–25,999 lb for tandem axles; 39,000–41,999 lb for 

tridem and quad axles 

MEPDG_LG12 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 13,000–13,999 lb for 

single axles; 26,000–27,999 lb for tandem axles; 42,000–44,999 lb for 

tridem and quad axles 

MEPDG_LG13 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 14,000–14,999 lb for 

single axles; 28,000–29,999 lb for tandem axles; 45,000–47,999 lb for 

tridem and quad axles 

MEPDG_LG14 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 15,000–15,999 lb for 

single axles; 30,000–31,999 lb for tandem axles; 48,000–50,999 lb for 

tridem and quad axles 

MEPDG_LG15 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 16,000–16,999 lb for 

single axles; 32,000–33,999 lb for tandem axles; 51,000–53,999 lb for 

tridem and quad axles 

MEPDG_LG16 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 17,000–17,999 lb for 

single axles; 34,000–35,999 lb for tandem axles; 54,000–56,999 lb for 

tridem and quad axles 

MEPDG_LG17 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 18,000–18,999 lb for 

single axles; 36,000–37,999 lb for tandem axles; 57,000–5,9999 lb for 

tridem and quad axles 

MEPDG_LG18 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 19,000–1,9999 lb for 

single axles; 38,000–39,999 lb for tandem axles; 60,000–62,999 lb for 

tridem and quad axles 

MEPDG_LG19 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 20,000–20,999 lb for 

single axles; 4,0000–41,999 lb for tandem axles; 63,000–65,999 lb for 

tridem and quad axles 

MEPDG_LG20 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 21,000–21,999 lb for 

single axles; 42,000–43,999 lb for tandem axles; 66,000–68,999 lb for 

tridem and quad axles 

MEPDG_LG21 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 22,000–22,999 lb for 

single axles; 44,000–45,999 lb for tandem axles; 69,000–71,999 lb for 

tridem and quad axles 

MEPDG_LG22 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 23,000–23,999 lb for 

single axles; 46,000–47,999 lb for tandem axles; 72,000–74,999 lb for 

tridem and quad axles 

MEPDG_LG23 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 24,000–24,999 lb for 

single axles; 48,000–49,999 lb for tandem axles; 75,000–77,999 lb for 

tridem and quad axles 

MEPDG_LG24 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 25,000–25,999 lb for 

single axles; 50,000–51,999 lb for tandem axles; 78,000–80,999 lb for 

tridem and quad axles 

MEPDG_LG25 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 26,000–26,999 lb for 

single axles; 52,000–53,999 lb for tandem axles; 81,000–83,999 lb for 

tridem and quad axles 

MEPDG_LG26 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 27,000–27,999 lb for 

single axles; 54,000–55,999 lb for tandem axles; 84,000–86,999 lb for 

tridem and quad axles 

MEPDG_LG27 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 28,000–28,999 lb for 

single axles; 56,000–57,999 lb for tandem axles; 87,000–89,999 lb for 

tridem and quad axles 

MEPDG_LG28 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 29,000–29,999 lb for 

single axles; 58,000–59,999 lb for tandem axles; 90,000–92,999 lb for 

tridem and quad axles 
82 

Field Name Data Type Description 

MEPDG_LG29 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 30,000–30,999 lb for 

single axles; 60,000–61,999 lb for tandem axles; 93,000–95,999 lb for 

tridem and quad axles 

MEPDG_LG30 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 31,000–31,999 lb for 

single axles; 62,000–63,999 lb for tandem axles; 96,000–98,999 lb for 

tridem and quad axles 

MEPDG_LG31 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 32,000–32,999 lb for 

single axles; 64,000–65,999 lb for tandem axles; 99,000–101,999 lb 

for tridem and quad axles 

MEPDG_LG32 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 33,000–33,999 lb for 

single axles; 66,000–67,999 lb for tandem axles 

MEPDG_LG33 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 34,000–34,999 lb for 

single axles; 68,000–69,999 lb for tandem axles 

MEPDG_LG34 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 35,000–35,999 lb for 

single axles; 70,000–71,999 lb for tandem axles 

MEPDG_LG35 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 36,000–36,999 lb for 

single axles; 72,000–73,999 lb for tandem axles 

MEPDG_LG36 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 37,000–37,999 lb for 

single axles; 74,000–75,999 lb for tandem axles 

MEPDG_LG37 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 38,000–38,999 lb for 

single axles; 76,000–77,999 lb for tandem axles 

MEPDG_LG38 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 39,000–39,999 lb for 

single axles; 78,000–79,999 lb for tandem axles 

MEPDG_LG39 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 40,000–40,999 lb for 

single axles; 80,000–81,999 lb for tandem axles 

Table 30. Field names and descriptions for SITE_SPECIFIC_NVCD 

Field Name Data Type Description 

STATE_CODE NUMBER(2,0) 

Numerical code for State or Province. U.S. codes are consistent with 

Federal Information Processing Standards 

SHRP_ID VARCHAR2(255) 

Test section identification number assigned by LTPP program. Must 

be combined with STATE_CODE to be unique 

YEAR NUMBER(4,0) Year for which values apply 

VEHICLE_CLASS NUMBER(2,0) 

Code indicating the 13-bin classification into which trucks have been 

grouped 

Pct_Trucks_Class NUMBER(3,2) Percentage of the truck population represented by this class 

Table 31. Field names and descriptions for USER_DEFINED_NALS 

Field Name Data Type Description 

VEH_CLASS NUMBER(2,0) 

Code indicating the 13-bin classification into which trucks have been 

grouped 

AXLE_GROUP NUMBER(1,0) Type of axle for which these percentages of axles apply 

NALS_CLUSTERS VARCHAR2(255) Text field indicating the type of NALS cluster 

MEPDG_LG01 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 0–2,999 lb for single 

axles; 0–5,999 lb for tandem axles; 0–11,999 lb for tridem and quad 

axles 

MEPDG_LG02 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 3,000–3,999 lb for 

single axles; 6,000–7,999 lb for tandem axles; 12,000–14,999 lb for 

tridem and quad axles 

MEPDG_LG03 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 4,000–4,999 lb for 

single axles; 8,000–9,999 lb for tandem axles; 15,000–17,999 lb for 

tridem and quad axles 
83 

Field Name Data Type Description 

MEPDG_LG04 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 5,000–5,999 lb for 

single axles; 10,000–11,999 lb for tandem axles; 18,000–20,999 lb for 

tridem and quad axles 

MEPDG_LG05 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 6,000–6,999 lb for 

single axles; 12,000–13,999 lb for tandem axles; 21,000–23,999 lb for 

tridem and quad axles 

MEPDG_LG06 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 7,000–7,999 lb for 

single axles; 14,000–15,999 lb for tandem axles; 24,000–26,999 lb for 

tridem and quad axles 

MEPDG_LG07 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 8,000–8,999 lb for 

single axles; 16,000–17,999 lb for tandem axles; 27,000–2,9999 lb for 

tridem and quad axles 

MEPDG_LG08 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 9,000–9,999 lb for 

single axles; 18,000–19,999 lb for tandem axles; 30,000–32,999 lb for 

tridem and quad axles 

MEPDG_LG09 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 10,000–10,999 lb for 

single axles; 20,000–21,999 lb for tandem axles; 33,000–35,999 lb for 

tridem and quad axles 

MEPDG_LG10 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 11,000–11,999 lb for 

single axles; 22,000–23,999 lb for tandem axles; 36,000–38,999 lb for 

tridem and quad axles 

MEPDG_LG11 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 12,000–12,999 lb for 

single axles; 24,000–25,999 lb for tandem axles; 39,000–41,999 lb for 

tridem and quad axles 

MEPDG_LG12 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 13,000–13,999 lb for 

single axles; 26,000–27,999 lb for tandem axles; 42,000–44,999 lb for 

tridem and quad axles 

MEPDG_LG13 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 14,000–14,999 lb for 

single axles; 28,000–29,999 lb for tandem axles; 45,000–47,999 lb for 

tridem and quad axles 

MEPDG_LG14 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 15,000–15,999 lb for 

single axles; 30,000–31,999 lb for tandem axles; 48,000–50,999 lb for 

tridem and quad axles 

MEPDG_LG15 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 16,000–16,999 lb for 

single axles; 32,000–33,999 lb for tandem axles; 51,000–53,999 lb for 

tridem and quad axles 

MEPDG_LG16 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 17,000–17,999 lb for 

single axles; 34,000–35,999 lb for tandem axles; 54,000–56,999 lb for 

tridem and quad axles 

MEPDG_LG17 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 18,000–18,999 lb for 

single axles; 36,000–37,999 lb for tandem axles; 57,000–5,9999 lb for 

tridem and quad axles 

MEPDG_LG18 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 19,000–19,999 lb for 

single axles; 38,000–39,999 lb for tandem axles; 60,000–62,999 lb for 

tridem and quad axles 

MEPDG_LG19 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 20,000–20,999 lb for 

single axles; 40,000–41,999 lb for tandem axles; 63,000–65,999 lb for 

tridem and quad axles 

MEPDG_LG20 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 21,000–21,999 lb for 

single axles; 42,000–43,999 lb for tandem axles; 66,000–68,999 lb for 

tridem and quad axles 

MEPDG_LG21 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 22,000–22,999 lb for 

single axles; 44,000–45,999 lb for tandem axles; 69,000–71,999 lb for 

tridem and quad axles 
84 

Field Name Data Type Description 

MEPDG_LG22 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 23,000–23,999 lb for 

single axles; 46,000–47,999 lb for tandem axles; 72,000–74,999 lb for 

tridem and quad axles 

MEPDG_LG23 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 24,000–24,999 lb for 

single axles; 48,000–49,999 lb for tandem axles; 75,000–77,999 lb for 

tridem and quad axles 

MEPDG_LG24 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 25,000–25,999 lb for 

single axles; 50,000–51,999 lb for tandem axles; 78,000–80,999 lb for 

tridem and quad axles 

MEPDG_LG25 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 26,000–26,999 lb for 

single axles; 52,000–53,999 lb for tandem axles; 81,000–83,999 lb for 

tridem and quad axles 

MEPDG_LG26 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 27,000–27,999 lb for 

single axles; 54,000–55,999 lb for tandem axles; 84,000–86,999 lb for 

tridem and quad axles 

MEPDG_LG27 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 28,000–28,999 lb for 

single axles; 56,000–57,999 lb for tandem axles; 87,000–89,999 lb for 

tridem and quad axles 

MEPDG_LG28 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 29,000–29,999 lb for 

single axles; 58,000–59,999 lb for tandem axles; 90,000–92,999 lb for 

tridem and quad axles 

MEPDG_LG29 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 30,000–30,999 lb for 

single axles; 60,000–61,999 lb for tandem axles; 93,000–95,999 lb for 

tridem and quad axles 

MEPDG_LG30 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 31,000–31,999 lb for 

single axles; 62,000–63,999 lb for tandem axles; 96,000–98,999 lb for 

tridem and quad axles 

MEPDG_LG31 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 32,000–32,999 lb for 

single axles; 64,000–65,999 lb for tandem axles; 99,000–101,999 lb 

for tridem and quad axles 

MEPDG_LG32 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 33,000–33,999 lb for 

single axles; 66,000–67,999 lb for tandem axles 

MEPDG_LG33 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 34,000–34,999 lb for 

single axles; 68,000–69,999 lb for tandem axles 

MEPDG_LG34 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 35,000–35,999 lb for 

single axles; 70,000–71,999 lb for tandem axles 

MEPDG_LG35 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 36,000–36,999 lb for 

single axles; 72,000–73,999 lb for tandem axles 

MEPDG_LG36 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 37,000–37,999 lb for 

single axles; 74,000–75,999 lb for tandem axles 

MEPDG_LG37 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 38,000–38,999 lb for 

single axles; 76,000–77,999 lb for tandem axles 

MEPDG_LG38 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 39,000–39,999 lb for 

single axles; 78,000–79,999 lb for tandem axles 

MEPDG_LG39 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 40,000–40,999 lb for 

single axles; 80,000–81,999 lb for tandem axles 

Description VARCHAR2(255) User-defined description for the NALS 

Cluster_Description VARCHAR2(255) Text description for NALS_CLUSTERS field 

Recommended_Road

_Usage VARCHAR2(255) 

Text description indicating the recommended road usage for the 

selected cluster 
85 

Table 32. Field names and descriptions for XMLGen_AxleLoadDistribution 

Field Name Data Type Description 

classNumber NUMBER(2,0) 

Code indicating the 13-bin classification into which trucks have been 

grouped 

numberAxle NUMBER(1,0) Type of axle (1–4) for which these values apply 

month NUMBER(2,0) Code specifying the month in numeric format (1–12) 

axleLoad NUMBER(2,0) Code specifying load bins in DARWin-ME (1–39) 

percentTrucksPerLoad NUMBER(3,14) 

Percentage of axles whose weight falls in the specified DARWin-ME 

load bin 

Table 33. Field names and descriptions for XMLGen_AxleLoadMain_Template 

Field Name Data Type Description 

classNumber NUMBER(2,0) 

Code indicating the 13-bin classification into which trucks have been 

grouped 

numberAxle NUMBER(1,0) Type of axle (1–4) for which these values apply 

month NUMBER(2,0) Code specifying the month in numeric format (1–12) 

axleLoad NUMBER(2,0) Code specifying load bins in DARWin-ME (1–39) 

Table 34. Field names and descriptions for 

XMLGen_DEFAULT_NALS_By_Loading_Cluster 

Field Name Data Type Description 

VEH_CLASS NUMBER(2,0) 

Code indicating the 13-bin classification into which trucks have been 

grouped 

AXLE_GROUP NUMBER(1,0) Type of axle for which these percentages of axles apply 

MEPDG_LG01 NUMBER(3,14) 

Percent of axles whose weight falls in the bin 0–2,999 lb for single axles; 

0–5,999 lb for tandem axles; 0–11,999 lb for tridem and quad axles 

MEPDG_LG02 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 3,000–3,999 lb for single 

axles; 6,000–7,999 lb for tandem axles; 12,000–14,999 lb for tridem and 

quad axles 

MEPDG_LG03 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 4,000–4,999 lb for single 

axles; 8,000–9,999 lb for tandem axles; 15,000–17,999 lb for tridem and 

quad axles 

MEPDG_LG04 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 5,000–5,999 lb for single 

axles; 10,000–11,999 lb for tandem axles; 18,000–20999 lb for tridem and 

quad axles 

MEPDG_LG05 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 6,000–6,999 lb for single 

axles; 12,000–13,999 lb for tandem axles; 21,000–23999 lb for tridem and 

quad axles 

MEPDG_LG06 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 7,000–7,999 lb for single 

axles; 14,000–15,999 lb for tandem axles; 24,000–26,999 lb for tridem and 

quad axles 

MEPDG_LG07 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 8,000–8,999 lb for single 

axles; 16,000–17,999 lb for tandem axles; 27,000–29,999 lb for tridem and 

quad axles 

MEPDG_LG08 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 9,000–9,999 lb for single 

axles; 18,000–19,999 lb for tandem axles; 30,000–32,999 lb for tridem and 

quad axles 

MEPDG_LG09 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 10,000–10,999 lb for 

single axles; 20,000–21,999 lb for tandem axles; 33,000–35,999 lb for 

tridem and quad axles 
86 

Field Name Data Type Description 

MEPDG_LG10 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 11,000–11,999 lb for 

single axles; 22,000–23,999 lb for tandem axles; 36,000–38,999 lb for 

tridem and quad axles 

MEPDG_LG11 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 12,000–12,999 lb for 

single axles; 24,000–25,999 lb for tandem axles; 39,000–41,999 lb for 

tridem and quad axles 

MEPDG_LG12 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 13,000–13,999 lb for 

single axles; 26,000–27,999 lb for tandem axles; 42,000–44,999 lb for 

tridem and quad axles 

MEPDG_LG13 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 14,000–14,999 lb for 

single axles; 28,000–29,999 lb for tandem axles; 45,000–47,999 lb for 

tridem and quad axles 

MEPDG_LG14 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 15,000–15,999 lb for 

single axles; 30,000–31,999 lb for tandem axles; 48,000–50,999 lb for 

tridem and quad axles 

MEPDG_LG15 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 16,000–16,999 lb for 

single axles; 32,000–33,999 lb for tandem axles; 51,000–53,999 lb for 

tridem and quad axles 

MEPDG_LG16 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 17,000–17,999 lb for 

single axles; 34,000–35,999 lb for tandem axles; 54,000–56,999 lb for 

tridem and quad axles 

MEPDG_LG17 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 18,000–18,999 lb for 

single axles; 36,000–37,999 lb for tandem axles; 57,000–59,999 lb for 

tridem and quad axles 

MEPDG_LG18 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 19,000–19,999 lb for 

single axles; 38,000–39,999 lb for tandem axles; 60,000–62,999 lb for 

tridem and quad axles 

MEPDG_LG19 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 20,000–20,999 lb for 

single axles; 40,000–41,999 lb for tandem axles; 63,000–65,999 lb for 

tridem and quad axles 

MEPDG_LG20 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 21,000–21,999 lb for 

single axles; 42,000–43,999 lb for tandem axles; 66,000–68,999 lb for 

tridem and quad axles 

MEPDG_LG21 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 22,000–22,999 lb for 

single axles; 44,000–45,999 lb for tandem axles; 69,000–71,999 lb for 

tridem and quad axles 

MEPDG_LG22 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 23,000–23,999 lb for 

single axles; 46,000–47,999 lb for tandem axles; 72,000–74,999 lb for 

tridem and quad axles 

MEPDG_LG23 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 24,000–24,999 lb for 

single axles; 48,000–49,999 lb for tandem axles; 75,000–77,999 lb for 

tridem and quad axles 

MEPDG_LG24 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 25,000–25,999 lb for 

single axles; 50,000–51,999 lb for tandem axles; 78,000–80,999 lb for 

tridem and quad axles 

MEPDG_LG25 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 26,000–26,999 lb for 

single axles; 52,000–53,999 lb for tandem axles; 81,000–83,999 lb for 

tridem and quad axles 

MEPDG_LG26 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 27,000–27,999 lb for 

single axles; 54,000–55,999 lb for tandem axles; 84,000–86,999 lb for 

tridem and quad axles 

MEPDG_LG27 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 28,000–28,999 lb for 

single axles; 56,000–57,999 lb for tandem axles; 87,000–89,999 lb for 

tridem and quad axles 
87 

Field Name Data Type Description 

MEPDG_LG28 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 29,000–29,999 lb for 

single axles; 58,000–59,999 lb for tandem axles; 90,000–92,999 lb for 

tridem and quad axles 

MEPDG_LG29 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 30,000–30,999 lb for 

single axles; 60,000–61,999 lb for tandem axles; 93,000–95,999 lb for 

tridem and quad axles 

MEPDG_LG30 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 31,000–31,999 lb for 

single axles; 62,000–63,999 lb for tandem axles; 96,000–98,999 lb for 

tridem and quad axles 

MEPDG_LG31 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 32,000–32,999 lb for 

single axles; 64,000–65,999 lb for tandem axles; 99,000–101,999 lb for 

tridem and quad axles 

MEPDG_LG32 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 33,000–33,999 lb for 

single axles; 66,000–67,999 lb for tandem axles 

MEPDG_LG33 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 34,000–34,999 lb for 

single axles; 68,000–69,999 lb for tandem axles 

MEPDG_LG34 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 35,000–35,999 lb for 

single axles; 70,000–71,999 lb for tandem axles 

MEPDG_LG35 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 36,000–36,999 lb for 

single axles; 72,000–73,999 lb for tandem axles 

MEPDG_LG36 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 37,000–37,999 lb for 

single axles; 74,000–75,999 lb for tandem axles 

MEPDG_LG37 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 38,000–38,999 lb for 

single axles; 76,000–77,999 lb for tandem axles 

MEPDG_LG38 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 39,000–39,999 lb for 

single axles; 78,000–79,999 lb for tandem axles 

MEPDG_LG39 NUMBER(3,14) 

Percentage of axles whose weight falls in the bin 4,0000–40,999 lb for 

single axles; 80,000–81,999 lb for tandem axles 

89 

REFERENCES 

1. AASHTO. Mechanistic-Empirical Pavement Design Guide, A Manual of Practice, Interim 

Edition. American Association of State Highway and Transportation Officials, Washington, 

DC, 2008. 

2. AASHTO. Guide for Design of Pavement Structures, American Association of State 

Highway and Transportation Officials, Washington, DC, 1993. 

3. FHWA, FHWA Traffic Monitoring Guide, 2001 Edition, page 4–6. 

4. NCHRP. Guide for Mechanistic-Empirical Design of New and Rehabilitated Pavement 

Structures, “Appendix AA—Traffic Loadings,” National Cooperative Highway Research 

Program, Transportation Research Board, Washington, DC, December 1999. 

http://onlinepubs.trb.org/onlinepubs/archive/mepdg/guide.htm. 

5. NCHRP Report 538. Traffic Data Collection, Analysis, and Forecasting for Mechanistic 

Pavement Design, National Research Council, Transportation Research Board, Washington, 

DC, 2005. 

6. NCHRP Report 509. Equipment for Collecting Traffic Load Data, National Research 

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7. ASTM. Standard Specification for Highway Weigh-in-Motion (WIM) Systems with User 

Requirements and Test Method. ASTM Committee E-17 on Vehicle-Pavement Systems, 

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Administration, McLean, VA, May 2009. 

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Reference Guide, Federal Highway Administration, McLean, VA, November 2009. 

10. Selezneva, O.I., Ayres, M., Hallenbeck, M., Ramachandran, A., Shirazi, H., and H. Von 

Quintus, “MEPDG Traffic Loading Defaults Derived from LTPP Transportation Pooled 

Fund Study.” Publication No. FHWA-HRT-13-090. In review. 
 

HRDI-30/10-13(500)E Recycled

Recyclable