Effect of Traffic Load Input Level on Mechanistic–Empirical Pavement Design

Abstract

This study investigated the effect of the input level of axle load spectra on performance predictions obtained with the Mechanistic–Empirical Pavement Design Guide (MEPDG). Traffic monitoring data collected from 50 weigh-in-motion (WIM) stations distributed across the state of Ohio were analyzed to obtain site-specific and regional axle load spectra. The site-specific axle load spectra were calculated for each axle group (single, tandem, tridem, and quad) and truck class (Classes 4 through 13). The regional axle load spectra were developed on the basis of statewide averages and cluster analysis. The statewide average was calculated with information from all sites, whereas the cluster averages were created on the basis of Class 9 tandem axles. Baseline designs for new flexible pavements were defined in the MEPDG for each of the WIM sites having available data, and site-specific, statewide average, cluster average, and MEPDG default axle load spectra were used to assess the impact of the input level of axle load spectra on the performance of the pavement structure. The statewide average and the cluster averages were found to yield similar predictions of pavement performance, with the cluster averages being slightly closer to the site-specific predictions of pavement performance. In addition, the MEPDG default axle load spectra were found to underestimate the pavement service life significantly and, if used for design purposes, would result in overly conservative pavement layer thicknesses. Therefore, the authors recommend the use of site-specific axle load spectra when possible in the design of flexible pavements. However, if site-specific data are not available, statewide average axle load spectra should be used.

Aplicación del pesaje de vehículos en movimiento al dimensionamiento de firmes. Influencia de la precisión de los pesajes

“…Es siempre delicado tratar la representatividad estadística de los resultados obtenidos en muestras tan pequeñas, y más A este respecto puede destacarse el trabajo de Abbas et al (18), que evaluó la diferencia en la estimación de la vida de servicio de varios diseños básicos de pavimentos flexibles de la MEPDG según se utilizaban diferentes espectros de cargas: los específicos para cada lugar obtenidos mediante pesaje dinámico o algunos dados por defecto en la norma. Tras el análisis se observó que los espectros dados por defecto en la MEPDG infraestimaban claramente la vida de servicio del pavimento (del orden del 50 %) y, por tanto, si se utilizaban para el dimensionamiento resultaban unos espesores de capas muy conservadores.…”

A data fusion approach for estimating traffic distribution characteristics of expressway: A case study of guangdong province, china

“…Certainly, they did not take some factors such as the distribution of traffic flow in different road sections, lanes, time periods (day and nights), and vehicle speed into consideration at the same time. Nevertheless, with the development of radio frequency identification technology, dynamic weighing technology, and high-definition image recognition technology, network tolling systems, weightcalculating charge systems, and high-definition video surveillance systems have been widely used in highway operation management faced with increasing traffic volume (Abbas et al, 2014;Ren et al, 2019;Feng et al, 2020). Massive traffic data are being collected on every expressway every day.…”

Evaluation of Clustered Traffic Inputs for Mechanistic-Empirical Pavement Design: Case Study in New Jersey

“…Although previous studies have employed similar clustering techniques, it is important to note that different traffic characteristics were used for clustering analysis. Papagiannakis et al used the tandem axle spectra as the only representative axle type, and thus the clustering of single, tridem, and quad axle load spectra followed the identified one for tandem axles ( 4 , 17 ). Sayyady et al and Lu and Harvey conducted cluster analysis on tandem axles, and modified the identified clusters for single, tridem, and quad axles considering the geographic/functional assignment of roads using engineering judgment ( 3 , 6 ).…”