Creation of Truck Axle Load Spectra Using Weigh-in-Motion Data

To assure a smooth transition from the existing pavement design methods to the new mechanistic-empirical design method in the Indiana Department of Transportation, a study was conducted to create truck traffic inputs and axle load spectra of major interstate and state-owned highways in Indiana. The existing pavement design method is based on the equivalent single-axle loads (ESAL), which converts wheel loads of various magnitudes and repetitions to an equivalent number of "standard" or "equivalent" axle loads. The new design method uses axle load spectra as the measure of vehicle loads on pavements. These spectra represent the percentage of the total axle applications within each load interval for single, tandem, tridem, and quad axles. In this study, the truck traffic and axle load spectra were developed based on the historical traffic data collected at 47 sites with weigh-in-motion technology. The truck traffic information includes hourly, daily, and monthly distributions of various types of vehicles and corresponding adjustment factors, the distributions of the number of axles of each type of truck, the weights of the axles, the spaces between the axles, the proportions of vehicles on roadway lanes, and the proportions of vehicles in driving directions. This paper presents the truck traffic and axle load spectra generated from the weigh-in-motion sites as required by the new pavement design method.

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Development of Mechanistic-Empirical Pavement Design in Minnesota

Transportation Research Record Journal of the Transportation Research Board ◽

10.3141/1629-20 ◽

1998 ◽

Vol 1629 (1) ◽

pp. 181-188 ◽

Cited By ~ 20

Author(s):

David Timm ◽

Bjorn Birgisson ◽

David Newcomb

Keyword(s):

Material Characterization ◽

Design Method ◽

Laboratory Data ◽

Design Procedure ◽

Computer Models ◽

Pavement Design ◽

University Of Minnesota ◽

Motion Data ◽

Load Spectra ◽

Weigh In Motion

The next AASHTO guide on pavement design will encourage a broader use of mechanistic-empirical (M-E) approaches. While M-E design is conceptually straightforward, the development and implementation of such a procedure are somewhat more complicated. The development of an M-E design procedure at the University of Minnesota, in conjunction with the Minnesota Department of Transportation, is described. Specifically, issues concerning mechanistic computer models, material characterization, load configuration, pavement life equations, accumulating damage, and seasonal variations in material properties are discussed. Each of these components fits into the proposed M-E design procedure for Minnesota but is entirely compartmentalized. For example, as better computer models are developed, they may simply be inserted into the design method to yield more accurate pavement response predictions. Material characterization, in terms of modulus, will rely on falling-weight deflectometer and laboratory data. Additionally, backcalculated values from the Minnesota Road Research Project will aid in determining the seasonal variation of moduli. The abundance of weigh-in-motion data will allow for more accurate load characterization in terms of load spectra rather than load equivalency. Pavement life equations to predict fatigue and rutting in conjunction with Miner’s hypothesis of accumulating damage are continually being refined to match observed performance in Minnesota. Ultimately, a computer program that incorporates the proposed M-E design method into a user-friendly Windows environment will be developed.

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Axle Load Distribution Characterization for Mechanistic Pavement Design

Transportation Research Record Journal of the Transportation Research Board ◽

10.3141/1629-03 ◽

1998 ◽

Vol 1629 (1) ◽

pp. 13-23 ◽

Cited By ~ 4

Author(s):

Jong R. Kim ◽

Leslie Titus-Glover ◽

Michael I. Darter ◽

Robert K. Kumapley

Keyword(s):

Load Distribution ◽

Pavement Design ◽

Performance Study ◽

Traffic Loading ◽

Design Procedures ◽

Motion Data ◽

The North ◽

Load Distributions ◽

Weigh In Motion ◽

The 1960S

Proper consideration of traffic loading in pavement design requires knowledge of the full axle load distribution by the main axle types, including single, tandem, and tridem axles. Although the equivalent single axle load (ESAL) concept has been used since the 1960s for empirical pavement design, the new mechanistic-based pavement design procedures under development by various agencies most likely will require the use of the axle load distribution. Procedures and models for converting average daily traffic into ESALs and axle load distribution are presented, as are the relevant issues on the characterization of the full axle load distributions for single, tandem, and tridem axles for use in mechanistic-based pavement design. Weigh-in-motion data from the North Central Region of the Long-Term Pavement Performance study database were used to develop the models for predicting axle load distribution.

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The analysis of overloaded trucks in indonesia based on weigh in motion data (east of sumatera national road case study)

MATEC Web of Conferences ◽

10.1051/matecconf/201814702006 ◽

2018 ◽

Vol 147 ◽

pp. 02006 ◽

Cited By ~ 4

Author(s):

Jongga Jihanny ◽

Bambang Sugeng Subagio ◽

Eri Susanto Hariyadi

Keyword(s):

Service Life ◽

Traffic Control ◽

National Standard ◽

Damage Factor ◽

Simplified Approach ◽

Motion Data ◽

Weigh In Motion ◽

Axle Loads ◽

National Road ◽

The Impact

Overloaded trucks phenomena generally common in developing countries where the traffic control is poor. In Indonesia, the percentage of overloaded trucks can reach more than 60% in the total number of trucks and may be one of the substantial factors that reduce the service life of the road pavements. This paper presents the analysis results of the weigh in motion survey data at East of Sumatera National Road (Jalintim) in Indonesia and the impact of overloaded trucks on the pavement. For the analysis the simplified approach was used, the axle loads were converted into representative single-axle loads based on 4th power formula by AASHTO 1993 equation. The vehicle damage factor of vehicles is presented and will be compared with the Highways National Standard to estimate the remaining service life of pavement and IRI value prediction. The analysis showed that the vehicle damage factor that determined from weigh in motion data is extremely greater than vehicle damage factor of the national standard in Indonesia which may lead to accelerated deterioration, reducing the service life of the pavement structures and significantly influence the IRI value.

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Effects of Revised Toll-by-Weight Policy on Truck Overloading Behavior and Bridge Infrastructure Damage Using Weigh-in-Motion Data: A Comparative Study in China

Advances in Civil Engineering ◽

10.1155/2019/5910463 ◽

2019 ◽

Vol 2019 ◽

pp. 1-13 ◽

Cited By ~ 2

Author(s):

Haiyun Huang ◽

Junyong Zhou ◽

Junping Zhang ◽

Wangxi Xu ◽

Zhixing Chen ◽

...

Keyword(s):

Transportation Network ◽

Structural Safety ◽

Chinese Government ◽

Truck Traffic ◽

Highway Infrastructure ◽

Motion Data ◽

Weigh In Motion ◽

Traffic Volumes ◽

Infrastructure Performance ◽

Equivalent Load

Since 2000, overloaded trucks have caused more than 50 bridges to collapse in China. In an effort to ensure the structural safety and extend the service life of the highway infrastructure, the Chinese government has proposed a series of policies in the past decade to mitigate truck overloading. This study aimed at investigating the effects of China’s recently revised toll-by-weight policy on truck overloading behavior and bridge infrastructure damage using weigh-in-motion data that spanned seven years (January 2011 to March 2018) and two successive toll-by-weight policies (with the new one implemented from August 2016), wherein truck data were measured from a typical national freeway segment. We first compared truck traffic volumes, compositions, and weight distributions under the initial and revised toll-by-weight policies. Next, we compared bridge infrastructure performance with respect to safety and fatigue based on the overloaded truck traffic observed under the initial and revised toll-by-weight policies. The results indicated that the revised toll-by-weight policy, which uses a stepwise incremental fee structure based on vehicle weight, was more effective at controlling truck overloading behavior and reducing bridge infrastructure damage than the initial toll-by-weight policy. Under the current policy, average daily truck volumes, overloaded truck proportions, and maximum truck weights decreased significantly. Concurrently, extreme and equivalent load effects for safety and fatigue assessments, respectively, decreased by an average of 20% for small- to medium-span bridges. Despite these noted improvements, overloaded truck traffic persisted, with loads often exceeding bridge design levels. This study’s findings can support future efforts by the Chinese government to further refine their toll-by-weight policies and subsequently ensure a safe and viable transportation network.

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Truck Traffic and Load Spectra of Indiana Roadways for the Mechanistic-Empirical Pavement Design Guide

10.5703/1288284317227 ◽

2020 ◽

Author(s):

Jieyi Bao ◽

Xiaoqiang Hu ◽

Cheng Peng ◽

Yi Jiang ◽

Shuo Li ◽

...

Keyword(s):

Urban Areas ◽

Critical Role ◽

Fatigue Cracking ◽

Pavement Design ◽

Easy Access ◽

Traffic Data ◽

Truck Traffic ◽

Load Spectra ◽

Design Guide ◽

Input Module

The Mechanistic-Empirical Pavement Design Guide (MEPDG) has been employed for pavement design by the Indiana Department of Transportation (INDOT) since 2009 and has generated efficient pavement designs with a lower cost. It has been demonstrated that the success of MEPDG implementation depends largely on a high level of accuracy associated with the information supplied as design inputs. Vehicular traffic loading is one of the key factors that may cause not only pavement structural failures, such as fatigue cracking and rutting, but also functional surface distresses, including friction and smoothness. In particular, truck load spectra play a critical role in all aspects of the pavement structure design. Inaccurate traffic information will yield an incorrect estimate of pavement thickness, which can either make the pavement fail prematurely in the case of under-designed thickness or increase construction cost in the case of over-designed thickness. The primary objective of this study was to update the traffic design input module, and thus to improve the current INDOT pavement design procedures. Efforts were made to reclassify truck traffic categories to accurately account for the specific axle load spectra on two-lane roads with low truck traffic and interstate routes with very high truck traffic. The traffic input module was updated with the most recent data to better reflect the axle load spectra for pavement design. Vehicle platoons were analyzed to better understand the truck traffic characteristics. The unclassified vehicles by traffic recording devices were examined and analyzed to identify possible causes of the inaccurate data collection. Bus traffic in the Indiana urban areas was investigated to provide additional information for highway engineers with respect to city streets as well as highway sections passing through urban areas. New equivalent single axle load (ESAL) values were determined based on the updated traffic data. In addition, a truck traffic data repository and visualization model and a TABLEAU interactive visualization dashboard model were developed for easy access, view, storage, and analysis of MEPDG related traffic data.

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The Impact of Cold and Snow on Weekday and Weekend Highway Total and Passenger Cars Traffic Volumes

The Open Transportation Journal ◽

10.2174/1874447801408010062 ◽

2014 ◽

Vol 8 (1) ◽

pp. 62-72 ◽

Cited By ~ 6

Author(s):

Hyuk-Jae Roh ◽

Satish Sharma ◽

Sandeep Datla

Keyword(s):

Statistical Significance ◽

Accurate Estimation ◽

Passenger Cars ◽

Passenger Car ◽

Motion Data ◽

Dummy Variable ◽

Weigh In Motion ◽

Traffic Volumes ◽

Adjustment Factors ◽

The Impact

Presented in this paper is an investigation of the impact of cold and snow on daily traffic volumes of total traffic and passenger cars. It is based on a detailed case study of five years of Weigh-In-Motion data recorded continuously at a highway site in Alberta, Canada. Dummy-variable regression models are used to relate daily traffic volumes with snowfall and categorized cold variables. The importance of all the independent variables used in the model are established by conducting tests of statistical significance. The total traffic and passenger car volumes are influenced by both the snowfall and the cold categories. Plots of the partial effect of each independent variable on the dependent variable are generated. It is found that a daily snowfall of 10 cm may cause a 25% reduction in the daily volume of passenger cars, and temperatures below -25°C may reduce the passenger car volumes by 10% or more. It is believed that the developed traffic-weather models of this study can benefit highway agencies in developing more advanced imputation method or identifying weather adjustment factors for accurate estimation of AADT from short duration traffic counts.

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

Transportation Research Record Journal of the Transportation Research Board ◽

10.1177/0361198119853557 ◽

2019 ◽

Vol 2673 (11) ◽

pp. 332-348

Author(s):

Abbas F. Jasim ◽

Hao Wang ◽

Thomas Bennert

Keyword(s):

Cluster Analysis ◽

New Jersey ◽

Hierarchical Cluster ◽

Pavement Design ◽

Traffic Data ◽

Truck Traffic ◽

Vehicle Class ◽

Site Specific ◽

Load Spectra ◽

Pavement Structures

Truck traffic is one of the significant inputs in design and analysis of pavement structures. This paper focuses on comprehensive cluster analysis of truck traffic in New Jersey for implementation of mechanistic-empirical pavement design. Multiple year traffic data were collected from a large number of weigh-in-motion stations across New Jersey. Statistical analysis was first conducted to analyze directional and temporal (yearly) variations of traffic data. Hierarchical cluster analysis was conducted and three optimum clusters were found for axle load spectra (single, tandem, tridem), vehicle class distribution, and axle/truck ratio, respectively. Road functional classifications were employed to identify different clusters as no common geographic trend could be perceived. The results illustrate that the predicted performance using the site-specific traffic data is comparable with that using the traffic cluster for the selected 10 sites. Among four different traffic inputs, the cluster traffic inputs generated the closest predictions of pavement life as compared with those using site-specific traffic input and the default traffic inputs yielded the highest error. It is recommended to use traffic clusters in mechanistic-empirical pavement design when site-specific data is unavailable.

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