2013 Session: 610

• Quality Control for Weigh-in-Motion Data Incorporating Threshold Values and Rational Procedures
  Abstract: One of the major improvements with using the Mechanistic-Empirical Pavement Design Guide (MEPDG) occurs in its characterization of traffic. Instead of converting all Class 4 to Class 13 truck axles to 18,000 lb equivalent single axles (ESALs), the MEPDG simulates every truck axle, and the associated stresses and strains imposed on the pavement structure, from a wide range of axle load spectra (ALS). For this reason, the MEPDG needs traffic inputs in more detail than previous empirical pavement design methods, and thus, a higher requirement of weigh-in-motion (WIM) data quality. This paper presents a new and objective approach to quality control (QC) of WIM data to ensure data quality for pavement design purposes. Instead of using subjective visual comparisons of gross vehicle weight (GVW) distributions, this research implements a peak-range check, peak-shift check and correlation analysis to quantify the ALS comparison process of rational checks. A number-of-axles check that calculates the average number of axles per vehicle class is also introduced herein. The entire QC procedure has been applied to 12 WIM stations in Alabama. As a result, 30.6% of data were filtered out, and data from one entire WIM station were removed. Therefore, QC of WIM data is strongly recommended, regardless of the extent of WIM system calibration.
  Authors: Mai, Derong; Turochy, Rod E.; Timm, David H.
  Authors: Mai, Derong; Turochy, Rod E.; Timm, David H.
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology
  Session: 610
  Paper Number: 13-0606
• Correlation-Based Clustering of Traffic Data for Mechanistic-Empirical Pavement Design
  Abstract: Development of traffic data clusters is crucial for use of the mechanistic-empirical pavement design guide (MEPDG) when site-specific traffic data are not available, but statewide data are too general. In current clustering practice, subjective decisions are made on issues such as determination of the number of clusters. This paper presents a new clustering combination method, correlation-based clustering, that can be used to quantify similarity of traffic data from different sites as an input to the clustering process. For each particular traffic input required in the MEPDG, the similarity between two sites is evaluated using Pearson’s correlation coefficient. This approach evaluates the sensitivity of pavement design thickness to each traffic input in order to quantify cut locations of hierarchical clustering trees, and thereby determine the number of clusters in an objective manner. The MEPDG requires many traffic inputs, including vehicle class distributions, four types of axle load spectra (per vehicle class), monthly and hourly distribution factors, and distributions of axle groups per vehicle. This clustering approach is performed for each traffic input such that a unique set of clusters can be developed for each traffic input. This method has been implemented for 22 direction-specific WIM stations to identify clusters of sites with similar pavement performance for each traffic input of the MEPDG. This paper illustrates the clustering process for one traffic input (single axle distribution) and also presents clustering results for vehicle class distribution.
  Authors: Mai, Derong; Turochy, Rod E.; Timm, David H.
  Authors: Mai, Derong; Turochy, Rod E.; Timm, David H.
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology
  Session: 610
  Paper Number: 13-0607
• Generating Site-Specific Axle Load Factors for Florida's MEPDG Implementation
  Abstract: This study was undertaken to develop the axle load factors for the Mechanistic-Empirical Pavement Design Guide software. As originally designed, these data are presented to the pavement designers at one of three levels. The MEPDG Level 1 data are site-specific. The data are collected either at the site or at a nearby location on the same route that has similar traffic characteristics. This paper presents detailed information about the axle load data requirements of the Guide, the process followed for deriving Florida’s input values, and the resulting recommended values.
  Authors: Cunagin, Wiley; Reel, Richard Lowell; Ghanim, Mohammad; Roark, Drew; Leggett, Michael
  Authors: Cunagin, Wiley; Reel, Richard Lowell; Ghanim, Mohammad; Roark, Drew; Leggett, Michael
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology
  Session: 610
  Paper Number: 13-2649
• Impact of Different Trucks on Pavement Design and Analysis: MEPDG Sensitivity Study Based on Data from Long-Term Pavement Performance Specific Pavement Studies Traffic Pooled Fund Study
  Abstract: This investigation was conducted to assess sensitivity of Mechanistic-Empirical Pavement Design Guide (MEPDG) outcomes to normalized axle load spectra (NALS) representing different loading conditions observed in Long Term Pavement Performance (LTPP) Specific Pavement Studies Traffic Pooled Fund Study (SPS TPF). The goal was to determine what vehicle classes and axle types are likely to cause differences in pavement design outcomes using the MEPDG, considering range of axle loading conditions. Significant differences in the outcomes would support the need for axle loading characterization beyond simple default value, while the absence of differences would indicate that load spectra from different sites could be combined to develop a default for a given vehicle class and axle type. The analysis also investigated when use of different default load spectra for class 9 vehicles would provide only marginal benefit due to low sensitivity of MEPDG outcomes. These results were used to develop recommendations for creation of axle loading defaults for MEPDG.
  Authors: Selezneva, Olga I.; Ramachandran, Aditya N.; Mustafa, Endri; Carvalho, Regis L.
  Authors: Selezneva, Olga I.; Ramachandran, Aditya N.; Mustafa, Endri; Carvalho, Regis L.
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology
  Session: 610
  Paper Number: 13-2890
• Practical Guidelines for Development of MEPDG Axle Loading Defaults Based on Findings from Long-Term Pavement Performance Specific Pavement Studies Traffic Pooled Fund Study
  Abstract: This paper presents methodology for development of MEPDG axle loading defaults and practical guidelines based on the findings from LTPP SPS TPF study. It introduces a concept of Tier 1 and Tier 2 axle loading defaults and provides recommendations when these defaults should be used, along with step-by-step instructions how to create these defaults. Because many truck characteristics differ from state to state, it would be beneficial for state highway agency to develop their own axle loading defaults. Methodology presented in this paper can be utilized by state highway agencies to develop their MEPDG axle loading defaults.
  Authors: Selezneva, Olga I.; Hallenbeck, Mark E.
  Authors: Selezneva, Olga I.; Hallenbeck, Mark E.
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology
  Session: 610
  Paper Number: 13-2908
• Reexamination of Traffic Data Preparation for the Mechanistic-Empirical Pavement Design Guide
  Abstract: An initial study to characterize traffic data for the Mechanistic Empirical Pavement Design Guide (MEPDG), performed in 2004, was reexamined. The objectives were (1) to update the traffic data library with the latest available data, (2) to compare the difference between the initial and new datasets, (3) to investigate the possible influence on pavement design due to different traffic datasets, and (4) to establish a workflow for traffic data operations at the Arkansas State Highway and Transportation Department (AHTD). Traffic data collected from weigh-in-motion stations between 2002 and 2010 were analyzed. The new dataset provided better quality than old dataset; overall, 91% of classification data and 13% of weight data passed the quality check. While statewide traffic patterns did not change significantly over the past 10 years, different Truck Traffic Classification (TTC) groups were observed – primarily due to the sensitivity of TTC to the amount of Class 13 trucks. New statewide and TTC-based volume adjustment factors and axle load spectra were developed. The influence of the adjusted traffic inputs on pavement design was studied by modeling two existing projects in DARWin-ME. The adjusted traffic data resulted in 8 years difference for the predicted design life. It is recommended that state-specific data should be applied in pavement design whenever possible. In addition, the traffic data library for the MEPDG should be periodically reviewed and updated as necessary.
  Authors: Hall, Kevin D.; Xiao, Danny X.; Nguyen, Vu T. D.; Wang, Kelvin C. P.
  Authors: Hall, Kevin D.; Xiao, Danny X.; Nguyen, Vu T. D.; Wang, Kelvin C. P.
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology
  Session: 610
  Paper Number: 13-3213
• Comparison of MEPDG Nationally Calibrated Traffic Inputs with Weigh-in-Motion Measurements in Alberta, Canada
  Abstract: Mechanistic-Empirical Pavement Design Guide (MEPDG) uses load spectra and number of axle applications to characterize traffic loads for the pavement designs, as a substitute for the equivalent single axle load (ESAL) approach. Alberta Transportation (AT) installed six weigh-in-motion (WIM) systems to collect the traffic inputs for a reliable pavement design using the MEPDG. The traffic data from the six WIM in Alberta was compared to the default values in the MEPDG Software for two consecutive years of 2009 and 2010. Reasonable agreements were observed for hourly and monthly adjustment factors; while truck traffic classifications and axle load distributions deviated from the MEPDG’s default values at some WIM stations. The influence of these differences on the performance of a typical Asphalt Concrete (AC) pavement for Alberta conditions was established through a sensitivity analysis. It was found that alligator cracking is the most sensitive to truck traffic classifications (specifically the distribution of truck Class 13). Using the truck distribution for Highway 16:06 based on the WIM measurements required an increase in the pavement thickness design. AC rutting was also found to be sensitive to all the studied variables including truck distribution, single and tandem axle load spectra; while IRI was not affected significantly by the changes in the variables under study.
  Authors: Nassiri, Somayeh; Farkhideh, Naser; Bayat, Alireza
  Authors: Nassiri, Somayeh; Farkhideh, Naser; Bayat, Alireza
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology
  Session: 610
  Paper Number: 13-3220
• Identification of Patterns for Traffic Inputs to Mechanistic-Empirical Pavement Design Guide in New York State
  Abstract: Proper characterization of traffic data is a prerequisite for the determination of appropriate traffic inputs to Mechanistic-Empirical Pavement Design Guide (MEPDG). The objective of the study was to characterize the traffic data and suggest the site-specific, regional or state wide average values for traffic inputs to MEPDG for New York. Vehicle class distribution (VCD), monthly distribution factors (MDF), hourly distribution factors (HDF), average number of axle groups per vehicle (AGPV) and axle load spectra data were obtained from 52 vehicle classification sites and 19 WIM sites in New York State. These traffic data were processed with TrafLoad software. Cluster analysis was adopted for the processed data of VCD, MDF and HDF for the data collected in 2010. This statistical analysis could not be done for AGPV values and axle load spectra due to the unavailability of sufficient number of WIM sites. MEPDG runs were also carried out to investigate the effect of the variability of traffic inputs on the pavement performance of a typical new flexible pavement structure. Cluster specific values were recommended for VCD. Statewide average values were recommended for MDF, HDF, AGPV and axle load spectra.
  Authors: Romanoschi, Stefan A.; Intaj, Ferdous; Bendana, Luis Julian
  Authors: Romanoschi, Stefan A.; Intaj, Ferdous; Bendana, Luis Julian
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology
  Session: 610
  Paper Number: 13-4584
• Simplified Truck Traffic Classification Groupings for DARWin-ME
  Abstract: Traffic loads obtained using automated traffic collection techniques such as Weight-In-Motion (WIM) are one of the key data elements required in the Mechanistic-Empirical Pavement Design Guide (MEPDG) and the subsequent DARWin-ME. Due to the limited number of WIM stations within a state agency, a key to the successful use of WIM traffic data in the new design guide is to be able to recognize traffic loading clusters so as to estimate the full axle load spectrum data occurring at a particular site. Even though various clustering approaches have been proposed, they are either computationally extensive or requiring site-specific truck count data. In most cases for designing new pavements, site-specific traffic data are not available before a pavement is open to the traffic; therefore it is desirable to develop a simplified truck grouping technique for DARWin-ME design when such information is missing. Following the Truck Traffic Classification (TTC) concept in DARWin-ME, K-Means cluster analysis algorithm is applied using the historical WIM data from Arkansas Highway Transportation Department (AHTD) and simplified TTC clusters are developed. Traffic input data generated based on DARWin-ME TTC grouping and simplified cluster approach are compared and analyses conducted. A case study is provided to demonstrate the applicability of using the simplified clusters to generate Level 2 traffic inputs for DARWin-ME design. The simplified TTC grouping method developed in the paper only requires prior knowledge of the trucking patterns that occur on specific roads and will alleviate the preparation of the traffic load spectra inputs based on WIM data for the new design guide procedure.
  Authors: Wang, Kelvin C. P.; Li, Qiang; Nguyen, Vu T. D.; Qiu, Shi; Zhang, Zhongjie; Moravec, Michael M
  Authors: Wang, Kelvin C. P.; Li, Qiang; Nguyen, Vu T. D.; Qiu, Shi; Zhang, Zhongjie; Moravec, Michael M
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology
  Session: 610
  Paper Number: 13-5238
• Reexamination of Traffic Data Preparation for the Mechanistic-Empirical Pavement Design Guide
  Authors: Hall, Kevin
  Keywords: poster presentation; poster design; poster template
  Authors: Hall, Kevin
  Year: 2013
  Document Type: Presentation; Poster
  Subject: Data and Information Technology
  Session: 610
  Paper Number: 13-3213
• Simplified Truck Traffic Classification Groupings for DARWin-ME
  Authors: Li, Qiang
  Authors: Li, Qiang
  Year: 2013
  Document Type: Presentation; Poster
  Subject: Data and Information Technology
  Session: 610
  Paper Number: 13-5238
• Practical Guidelines for Development of MEPDG Axle Loading Defaults Based on Findings from Long-Term Pavement Performance Specific Pavement Studies Traffic Pooled Fund Study
  Authors: Selezneva, Olga
  Authors: Selezneva, Olga
  Year: 2013
  Document Type: Presentation; Poster
  Subject: Data and Information Technology
  Session: 610
  Paper Number: 13-2908
• Impact of Different Trucks on Pavement Design and Analysis: MEPDG Sensitivity Study Based on Data from Long-Term Pavement Performance Specific Pavement Studies Traffic Pooled Fund Study
  Authors: Selezneva, Olga
  Authors: Selezneva, Olga
  Year: 2013
  Document Type: Presentation; Poster
  Subject: Data and Information Technology
  Session: 610
  Paper Number: 13-2890