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Publication Number: FHWA-RD-03-094
Date: March 2005

Estimating Cumulative Traffic Loads, Volume II:
Traffic Data Assessment and Axle Load Projection for The Sites With Acceptable Axle Weight Data, Final Report for Phase 2

CHAPTER 4. COMPUTED PARAMETER TABLES FOR PROJECTED TRAFFIC DATA

This chapter describes computational procedures used to generate projected annual axle load spectra, explains how the projected data are stored in the computed parameter tables in the IMS Traffic Module, and describes relationships between computed traffic parameters and other data elements in the IMS database. The computational procedure described here applies only to sites with site–specific annual axle load data.

Description of Computed Parameter Tables

The projection of traffic loads for all in–service years for the LTPP traffic sites resulted in the five computed parameter tables. These tables contain both the projected annual axle load spectra and the intermediate variables. The intermediate variables carry important information documenting how the projected axle load spectra were calculated. The following list represents a set of the projected traffic computed parameter tables. Each table is named twice: the descriptive name is first, and the proposed IMS name follows in bold type.

Main Table:

  • Projected Annual Axle Load Spectra (TRF_PRJ_YR_AXLE_DISTRIB).
Intermediate Tables:
  • Normalized Base Annual Axle Load Spectra (TRF_PRJ_BAS_ANL_PCT_AXLE).
  • Base Annual Axle Load Summary (TRF_PRJ_BAS_ANL_AXLE_SUM).
  • Annual Projection Factors (TRF_PRJ_YR_MULTIPLIER).
  • Projection Summary Table (TRF_PRJ_MASTER).

Figure 25 presents an overview of the IMS Traffic Module that includes historical, monitoring, and projected traffic data. The relationship between the projected and other traffic tables stored in IMS is shown in figure 26. Figure 26 also provides a flowchart used for the calculation of variables stored in the computed parameter tables. The main computed parameter table is highlighted by heavy borderlines. Below the main table, in the oval shape, is the provision for calculating "cumulative axle loads." The cumulative axle load spectra are not available in the IMS database; they can be obtained by adding up annual axle load spectra for any combination of in–service years.

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Figure 25. Overview of the IMS Traffic Module
showing the proposed addition of projected traffic data.

Generation of Projected Annual Axle Load Spectra

This section describes the computational procedure used to generate projected annual axle load spectra for all in–service years, and the relationships among the variables in the computed parameter tables. The description builds on the outline of the traffic projection procedure provided in chapter 2. Since only traffic projections for Category 1 and 2 sites were carried out during the study, the description herein is based on methodology developed for Category 1 and 2 projections (see p. 8 of this report for descriptions of the categories).

Computation of the projected annual axle load spectra for all in–service years and preparation of the computed parameter tables involves the following major steps:

  1. Computation of normalized base annual axle load spectra (table TRF_PRJ_BAS_ANL_PCT_AXLE).
  2. Computation of base annual axle load summary (table TRF_PRJ_BAS_ANL_AXLE_SUM).
  3. Computation of annual projection factors (table TRF_PRJ_YR_MULTIPLIER).
  4. Computation of projected annual axle load spectra (table TRF_PRJ_YR_AXLE_DISTRIB).
  5. Reporting projection summary (table TRF_PRJ_MASTER).

These steps are described in more detail in the following sections.

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Figure 26. Flowchart used for calculating computed parameter tables.

Computation of Normalized Base Annual Axle Load Spectra

Normalized base annual axle load spectra for single, tandem, triple, and quad axle groups are given in table TRF_PRJ_BAS_ANL_PCT_AXLE. The normalized base annual axle load spectrum is the base annual load spectrum with the axle load counts for a given weight range (and axle type) expressed as percentages of the total axle counts for the given axle type. This spectrum is computed for the same set of weight ranges that are used in table TRF_MONITOR_AXLE_DISTRIB. Normalized spectrum provides a characteristic shape of axle weight distribution for each LTPP traffic site.

To develop normalized base annual spectrum, available monitoring annual spectra from the IMS table TRF_MONITOR_AXLE_DISTRIB were critically assessed and base annual spectrum was computed by averaging annual axle load data for selected years as described in chapter 2. Then, the computed base annual spectrum was normalized with respect to the total annual axle load counts for each axle type. The computational procedure for obtaining normalized base annual axle load spectrum is shown in figure 27.

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Figure 27. Flowchart for computation of the normalized base annual load spectra.

Computation of Base Annual Axle Load Summary

The base total annual numbers of axles for single, tandem, and triple axle groups contained in the base annual spectrum are given in table TRF_PRJ_BAS_ANL_AXLE_SUM (base annual axle load summary). The base total annual number of axles is associated with normalized base number of axles from TRF_PRJ_BAS_ANL_PCT_AXLE and is used to calculate projected annual axle load spectra. The base total annual number of axles provides information about overall truck volume (in terms of total axle counts) that is representative for each LTPP traffic site.

The total base annual number of axles was computed (see figure 28) by summing axles from the computed base annual spectrum across all weight ranges. This summation was done separately for each axle type.

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Figure 28. Flowchart for computation of the base annual axle load summary.

Computation of Annual Projection Factors

Annual projection factors, calculated for each in–service year for LTPP sites, are given in table TRF_PRJ_YR_MULTIPLIER. These factors define an annual truck traffic growth pattern and adjust the base total annual axle counts up or down to fit the selected projection model. Annual projection factors are used to compute projected annual axle load spectra.

The annual projection factors are selected based on critical review of the available historical and monitoring traffic data for all available years from the following IMS tables:

  • MONITOR_BASIC INFO.
  • ST_ANL_TOT_GPS_LN.
  • ONITOR_AXLE_DISTRIB.
  • ONITOR_VEHICLE_DIST.

The computational procedure for the annual projection factors is shown in figure 29.

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Figure 29. Flowchart for computation of the annual projection factors.

Computation of Projected Annual Axle Load Spectra

Projected annual axle load spectra (for single, tandem, and triple axle groups) are the main product of the LTPP traffic projection process. These results are presented in the table TRF_PRJ_YR_AXLE_DISTRIB. Projected annual load spectra for each year are computed (see figure 30) by multiplying the base annual load spectrum with annual traffic projection factors from table TRF_PRJ_YR_MULTIPLIER. The base annual load spectrum is computed by multiplying the normalized base annual axle load spectrum for single, tandem, and triple axle groups from the table TRF_PRJ_BAS_ANL_PCT_AXLE with the total base annual number of axles for single, tandem, and triple axle groups from the table TRF_PRJ_BAS_ANL_AXLE_SUM. The projected load spectra are reported in terms of annual axle counts for the same set of load ranges used in table TRF_MONITOR_AXLE_DISTRIB.

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Figure 30. Flowchart for computation of projected annual axle load spectra.

Reporting Projection Summary

The summaries of projection results (including applicable traffic projection interval; information about traffic projection category used for each LTPP traffic site; the assigned traffic projection codes; and any specific traffic characteristic for each LTPP site) are stored in the table TRF_PRJ_MASTER.

To assign projection confidence codes and for QA purposes,the projected annual axle load spectra were used to calculate ESALs. Calculated ESALs were then compared with the available historical ESAL trends. Also, TFs were computed and compared with historical TFs and with typical TFs based on FHWA functional highway classification. Analysts assigned initial projection confidence codes to the results using the guidelines described in chapter 2. After the traffic projection results were reviewed by the participating highway agencies, the changes were made to the initial projections, and reviewed projection confidence codes were assigned to each site.

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