The project provided guidelines for collecting traffic data to be used in pavement design and software for analyzing traffic data and producing traffic data inputs required for mechanistic pavement analysis and design as well as guidance on selecting, installing, and operating traffic data-collection equipment and handling traffic data. Traffic information is one of the key data elements required for the design and analysis of pavement structures. In the procedure used in the 1993 AASHTO Guide for Design of Pavement Structures, a mixed traffic stream of different axle loads and axle configurations is converted into a design traffic number by converting each expected axle load into an equivalent number of 18 kip-single- axle loads, known as equivalent single-axle loads (ESALs). Equivalency factors are used to determine the number of ESALs for each axle load and axle configuration. These factors are based on the present serviceability index concept and depend on the pavement type and structure. Studies have shown that these factors also are influenced by pavement condition, distress type, failure mode, and other parameters. A more direct and rational approach to the analysis and design of pavement structures involves procedures that use mechanistic-empirical principles to estimate the effects of actual traffic on pavement response and distress. This approach has been used to develop a guide for the mechanistic-empirical design of new and rehabilitated pavement structures as part of NCHRP Project 1-37A (currently available on-line at http://www.trb.org/mepdg/). Because of the constraints on resources available in state and local highway agencies for traffic data collection, the guide allows for various levels of traffic data collection and analysis. The mechanistic-based distress prediction models used in this guide require specific data for each axle type and axle-load group. Because these traffic data inputs differ from those currently used in pavement design and analysis, there was an apparent need for research to provide clear information on traffic data and forecasting and to provide guidance on selection and operation of the equipment needed for collecting these data. The research produced a variety of information and products, including the following: (1) Results from analysis of the effect of the length of the data-collection period on the accuracy of pavement damage factors developed from short-duration weigh-in-motion data collection. (2) A discussion of three technical issues relating to the design of software for analyzing traffic: traffic ratios versus traffic factors, partial-day classification counts and truck traffic distribution factors, and simple averaging versus weighted averaging of traffic data. (3) A procedures manual documenting the algorithms used in the software. (4) A software user manual. (5) Recommendations for software improvements that could be made at a later time. (6) A discussion of the actions required, at both the state and national level, to promote a successful implementation of the software. In addition, the researchers discussed procedures for forecasting traffic volumes and a procedure for estimating coefficients of variation for estimates of average annual daily traffic by vehicle class, and identified the steps required to select the equipment necessary for collecting traffic load data. (Author/publisher) This report may be accessed by Internet users at http://gulliver.trb.org/publications/nchrp/nchrp_rpt_538.pdf
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