The knowledge of traffic loads is a prerequisite for the pavement analysis process, especially for the development of load-related distress prediction models. Furthermore, the emerging mechanistically based pavement performance models and pavement design methods (such as the anticipated "2002 Pavement Design Guide") require the knowledge of the load spectra acting on the pavement during its lifespan. This report describes a procedure for obtaining axle load spectra for Long Term Pavement Performance (LTPP) sections. The procedure has been demonstrated and evaluated by applying it to 12 LTPP sections for which different amounts of monitoring traffic data were available. Typically, for the majority of LTPP sections, there are only a few years for which the traffic load data were collected by automated equipment in the mid-1990s. To obtain axle load spectra for all in-service years, traffic loads must be projected: backcasted (for the years before the installation of traffic monitoring equipment) and forecasted (for the years after the automated equipment no longer provides data). This report also contains a review of the evolution of motor carrier technology (in terms of economical and political changes, regulatory changes in vehicle weights and dimensions, and engineering changes) and its impact on traffic loads, and a proposal to develop and use new summary statistical measures and tools for the management of load spectra. Major findings and recommendations include: (1) Traffic load projections for the majority of LTPP sites are feasible. (2) The accuracy and reliability of the traffic projections for many of the LTPP sites may not be as high as originally anticipated. (3) The involvement of State highway agencies (SHAs) in the traffic projection process is crucial. (4) The traffic projection process is very challenging and labor-intensive. The main reason for the labor-intensive process is the need to carry out extensive quality assurance activities to resolve inconsistencies in the reported traffic data. (5) The quality assurance process would greatly benefit from developing a knowledge base or a catalog documenting a typical range of traffic load variables. The process would also benefit from the availability of summary measures for traffic loads that are independent of pavement variables. (6) Traffic modeling and forecasting is a highly cost-effective way to extend limited sampling data and compensate for the lack of data. To obtain payback on the large investment in the traffic data collection effort by SHAs, it is necessary to allocate sufficient resources to utilize fully the available traffic data through the traffic prediction process. (7) It is recommended to proceed with carrying out traffic load projections for the selected LTPP sites (Phase 2 study). (8) Phase 2 study, and any future projection of traffic loads, should include the input from the representatives of SHAs.

  • Record URL:
  • Corporate Authors:

    ERES Consultants, Incorporated

    9030 Red Branch Road, Suite 210
    Columbia, MD  United States  21045

    Federal Highway Administration

    Turner-Fairbank Highway Research Center, 6300 Georgetown Pike
    McLean, VA  United States  22101
  • Authors:
    • Hajek, J J
    • Selezneva, O I
  • Publication Date: 2000-7


  • English

Media Info

  • Features: Appendices; Figures; References; Tables;
  • Pagination: 202 p.

Subject/Index Terms

Filing Info

  • Accession Number: 00796941
  • Record Type: Publication
  • Report/Paper Numbers: FHWA-RD-00-054,, Final Report,, C6B
  • Contract Numbers: DTFH61-96-C-00003
  • Created Date: Aug 15 2000 12:00AM