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Publication Number: FHWA-HRT-05-079
Date: May 2006
Optimization of Traffic Data Collection for Specific Pavement Design Applications
Chapter 7. Summary
This study presented a comprehensive approach for establishing the minimum traffic data collection effort required for pavement design applications satisfying a maximum acceptable error under a prescribed confidence level. This approach consists of simulating the traffic data input to the new NCHRP 1-37A design guide for 17 distinct traffic data collection scenarios using extended-coverage WIM data from the LTPP database.
Extended coverage was defined as 299 or more days per year of level E WIM data. Analysis of Data Release 16.0 revealed a total of 178 GPS sites that satisfied this requirement. For all of these sites, CTDB data were extracted in the form of daily summaries (level 3). From these sites, a total of 30 sites (15 flexible and 15 rigid) were selected for NCHRP 1-37A design guide simulation. The selection was based on the widest possible distribution of AADTT volumes and structural thicknesses.
A number of the traffic data collection scenarios simulated involved continuous site-specific data coverage for axle loads, classification, or counts, while others involved discontinuous site-specific data coverage (e.g., 1 month per season, 1 week per season, and so on). Data elements that were assumed to be unavailable at a site for simulation purposes were estimated from regional data. Regional vehicle classification and load data were obtained from the remaining LTPP sites identified using clustering techniques. Scenarios involving national data used the default traffic input in the NCHRP 1-37A design guide. For each of the traffic data collection scenarios involving discontinuous coverage of site-specific data, statistics for each traffic data element were computed by considering all possible time-coverage combinations. This allowed establishment of the lowest percentiles for each of these input to simulate underestimation of the actual traffic volumes/loads at a site. This was considered to be critical because it would result in thinner pavement designs that failed prematurely. Three confidence levels were selected: 75 percent, 85 percent, and 95 percent. Traffic inputs for the continuous-coverage traffic data collection scenarios involved no variation because of the sampling scheme used. All scenarios were simulated using a 4-percent annual growth in AADTT. Additional analyses were conducted to compute the annual growth rate in AADTT and its effect on pavement life predictions.
The NCHRP 1-37A design guide pavement life predictions for each scenario were analyzed to compute percentage errors in pavement life predictions with respect to the life predictions obtained under continuous site-specific WIM data (scenario 1-0). Reasonable life predictions were obtained for 17 of the 30 sections analyzed (the remainder experienced either premature failures or no failure at all). Two error components were identified:
Computing statistics for error component "A" for all 17 sections revealed that its mean is negligible for all of the scenarios analyzed. Its standard deviation allowed for the establishment of a range of errors by confidence level (table 29 and figure 22). Statistics for error component "B" were processed to yield the mean error and the standard deviation in the mean error by traffic data collection scenario. This allowed computation of the range in mean error resulting from specifying the lowest percentile for all of the traffic input simultaneously. It was noted that this is very conservative; however, it addresses the question of reliability, guaranteeing the designer that given a level of confidence, a particular error level will not be exceeded. Overall error was computed by adding the range in error from component "A" to the range in mean error from component "B." The results were plotted in a three-dimensional plot, indicating the maximum error by confidence level for each of the traffic data collection scenarios analyzed (table 32 and figure 23). Figure 23 can be used to establish the minimum required traffic data collection effort given the acceptable error and the desirable level of confidence.