Methodology for Developing Generic Performance Curves for Flexible Pavements in Puerto Rico Using Clustering Techniques

1997 ◽  
Vol 1592 (1) ◽  
pp. 116-124
Author(s):  
Benjamín Colucci ◽  
Nazario Ramírez-Beltrán ◽  
Francisco Rodríguez-Dosal
Keyword(s):  
Puerto Rico ◽  
Essential Elements ◽  
Pavement Management ◽  
Remaining Useful Life ◽  
Pavement Management System ◽  
Clustering Techniques ◽  
Climatic Regions ◽  
State Highway ◽  
Performance Curves ◽  
State Highway Agencies

One of the major challenges that state highway agencies face is the need to estimate performance curves for different functional classifications of highways and traffic loads, considering the limitations of resources and equipment required for data collection and management activities. The need to estimate the remaining useful life of pavements in different climatic regions with a variety of subgrade conditions is crucial for the efficient allocation of maintenance and rehabilitation funds. A methodology that addresses both the performance and regional climatic aspects is presented. Essential elements of this methodology include clustering techniques for identifying the homogeneous climatic regions and determining serviceability in terms of accepted relationships of roughness and the use of nonlinear optimization to estimate performance curves based on equivalent 18-kip single axle loads and pavement serviceability index parameters. Generic performance curves have been developed for each climatic region. Application of the methodology for the cluster corresponding to the humid region is presented. The proposed methodology is expected to provide support to the Puerto Rico Highway and Transportation Authority, Strategic Highway Research Program, and the Long-Term Pavement Performance program in their pavement evaluation processes, thus contributing to the ongoing pavement management system in Puerto Rico.

Application of Traffic Speed Deflectometer for Network-Level Pavement Management

2018 ◽  
Vol 2672 (40) ◽  
pp. 348-359 ◽  
Author(s):  
Shivesh Shrestha ◽  
Samer W. Katicha ◽  
Gerardo W. Flintsch ◽  
Senthilmurugan Thyagarajan
Keyword(s):  
Surface Condition ◽  
Structural Condition ◽  
Pavement Management ◽  
Falling Weight Deflectometer ◽  
Pavement Management System ◽  
State Highway ◽  
Structural Evaluation ◽  
Traffic Speed ◽  
State Highway Agencies ◽  
Falling Weight

In this paper, the traffic speed deflectometer (TSD), a device used for network level structural evaluation, is assessed. TSD testing was performed in nine states on a total of 5,928 miles (some repeated) during three time periods: November 2013, May to July 2014, and June to September 2015. This paper presents (1) the results of repeatability and comparison of the TSD with the falling weight deflectometer (FWD), (2) the results of the comparison of TSD measurements with typical pavement management system (PMS) data, and (3) an approach that can be implemented by State Highway Agencies (SHAs) to incorporate indices derived from TSD data into their PMS decision-making process. The results show that repeated TSD measurements follow similar trends and the TSD measurements and FWD measurements on the same pavement sections follow similar trends as well. Comparing TSD measurements with PMS surface condition data confirmed that the TSD provided valuable information about the structural condition of the tested pavement sections that cannot be derived from the already available pavement surface condition as part of an agency’s PMS. An example of how TSD information can be used to refine the triggered maintenance treatment category as part of a network-level PMS analysis is presented for a roughly 75-mile section of I-81 south in Virginia.

Development of Pavement Performance Curves for Individual Distress Indexes in South Dakota Based on Expert Opinion

1996 ◽  
Vol 1524 (1) ◽  
pp. 130-136 ◽  
Author(s):  
Newton C. Jackson ◽  
Richard Deighton ◽  
David L. Huft
Keyword(s):  
South Dakota ◽  
Expert Opinion ◽  
Pavement Management ◽  
Pavement Performance ◽  
Department Of Transportation ◽  
Pavement Management System ◽  
Pavement Condition ◽  
Performance Curves ◽  
Collective Experience ◽  
Work Done

Work done to develop pavement performance curves for use in the enhanced South Dakota Department of Transportation (SDDOT) pavement management system (PMS) is described. Pavement performance curves were developed for various new pavement sections as well as for a range of rehabilitation treatments. The performance curves were developed by using both individual and composite pavement indexes. Because of a lack of sufficient historical data the pavement performance curves could only be developed by using expert opinion. A pavement expert group was established and a questionnaire was developed to quantify their collective experience. The responses were then used to develop quite reasonable pavement performance curves by using individual and composite indexes developed for South Dakota. The resulting pavement performance curves are adequate for the beginning input into the enhanced SDDOT PMS. The pavement performance curves developed should be revised as sufficient historical pavement condition data become available.

scholarly journals Coordinated Pavement Management System between Municipalities and State in Rhode Island

2019 ◽  
Author(s):  
masoud faramarzi
Keyword(s):  
Rhode Island ◽  
Management System ◽  
Surface Condition ◽  
Condition Index ◽  
Pavement Management ◽  
Pavement Management System ◽  
Health Indices ◽  
State Highway ◽  
Budget Analysis ◽  
Transportation Agencies

State of Rhode Island and Providence Plantation (RI) has 6,052 miles roadways: 1,098 miles State-maintained highways, 4,766 miles cities and towns-maintained roadways, 188 miles for other jurisdictions. Most transportation agencies are using their own pavement management system (PMS); however, the coordinated system for state highways and municipally maintained roads appears to be absent. Thus, a coordinated effort has been made successfully among state, municipalities and academia in RI. A standardized PMS with MicroPAVER™ was established for Kingston campus at University of Rhode Island (URI) to help the implementation for cities and towns in 1988. URI team suggested to evaluate only one representative sample unit per section. Condition survey has been performed for 30 years, and current and future condition were determined and predicted for URI campus, respectively. Maintenance and rehabilitation (M&R) strategies were established and budget analysis was performed for needed cities and towns. Rhode Island Department of Transportation (RIDOT) adopted a PMS based on surface condition as well as roughness from 1985. Like MicroPAVER™ pavement condition index (PCI), RIDOT developed and calculated pavement structural health indices (PSHIs) for each 1/10th of mile segment of highway. Gradually RIDOT has been using Deighton Total Infrastructure Management System (dTIMS™) as its PMS for state-maintained highways since 1993. To coordinate two systems, MicroPAVER™ and dTIMS™ were used for network of Cranston city and RI state highway in the present study, respectively. Hope that this model PMS will stimulate more implementation for other transportation agencies.

Implementation of Automated Network-Level Crack Detection Processes in Maryland

2003 ◽  
Vol 1860 (1) ◽  
pp. 109-116 ◽  
Author(s):  
Jonathan L. Groeger ◽  
Peter Stephanos ◽  
Paul Dorsey ◽  
Mark Chapman
Keyword(s):  
Data Collection ◽  
Crack Detection ◽  
Implementation Process ◽  
Lessons Learned ◽  
Pavement Management ◽  
Pavement Management System ◽  
State Highway ◽  
Management Group ◽  
Detection Software ◽  
Insight Into

The Maryland State Highway Administration (MDSHA) has collected cracking data on its roadways for use in its pavement management system since 1984. Through much of this history the pavement cracking survey was performed yearly by teams of inspectors riding in vans. With the reengineering of the administration over the years, this process began to present serious resource and logistical problems. During the past 3 years, the MDSHA pavement management group has developed and implemented a state-of-the-art automated network-level crack detection process that is showing promising results. This process is based upon the use of the automated road analyzer (ARAN) data collection vehicle, Wisecrax crack detection software, and an intensive quality-control (QC) and quality-assurance (QA) procedure. The data collection and data processing tasks are all performed in house with MDSHA resources. An overview of the processes developed and implemented by MDSHA to conduct these surveys is provided. Also discussed are challenges and lessons learned during the implementation process. Presentation of this information will allow others to gain insight into the strengths and weaknesses of adopting such a system and promote information sharing among pavement data collection organizations. Overall, it is concluded that automated network-level crack detection is a workable and efficient tool. However, a strict QC-QA regime must be instituted in order to achieve consistent and repeatable results.

Description of Rehabilitation Scoping Process Used in Washington State Pavement Management System

1996 ◽  
Vol 1524 (1) ◽  
pp. 94-102
Author(s):  
Linda M. Pierce ◽  
Joe P. Mahoney
Keyword(s):  
Management System ◽  
Washington State ◽  
Pavement Management ◽  
Pavement Design ◽  
Analysis Tool ◽  
Department Of Transportation ◽  
Pavement Management System ◽  
State Highway ◽  
Washington State Department ◽  
Highway System

In the early 1980s the Washington State Department of Transportation (WSDOT) developed and implemented a pavement management system (PMS). Over the years, the PMS has evolved into a very useful documentation of the state highway system and an essential analysis tool for pavement design. The various elements of the Washington State Pavement Management System (WSPMS) will be discussed, as will the ways in which the WSPMS is used for the rehabilitation budgeting. Early in the development of the WSPMS, the system had a strong capability to identify the specific projects that required rehabilitation and when the rehabilitation was required. The weakness in the WSPMS was determining the required level of rehabilitation (overlay thickness). The process (referred to as scoping) currently used to estimate the overlay thickness using only the data in the WSPMS will also be discussed.

Using Artificial Intelligence to Estimate Nonlinear Resilient Modulus Parameters from Common Index Properties

2021 ◽  
pp. 036119812110237
Author(s):  
Laura Camarena
Keyword(s):  
Machine Learning ◽  
Material Properties ◽  
Resilient Modulus ◽  
Nonlinear Behavior ◽  
Machine Learning Techniques ◽  
Design Parameters ◽  
Nonlinear Parameters ◽  
State Highway ◽  
Learning Techniques ◽  
State Highway Agencies

The Mechanistic–Empirical Pavement Design Guide (MEPDG) considers a hierarchical approach to determine the input values necessary for most design parameters. Level 1 requires site-specific measurement of the material properties from laboratory testing, whereas other levels make use of equations developed from regression models to estimate the material properties. Resilient modulus is a mechanical property that characterizes the unbound and subgrade materials under loading that is essential for the mechanistic design of pavements. The MEPDG resilient modulus model makes use of a three-parameter constitutive model to characterize the nonlinear behavior of the geomaterials. As the resilient modulus tests are complex, expensive, and require lengthy preparation time, most state highway agencies are unlikely to implement them as routine daily applications. Therefore, it is imperative to make use of models to calculate these nonlinear parameters. Existing models to determine these parameters are frequently based on linear regression. With the development of machine learning techniques, it is feasible to develop simpler equations that can be used to estimate the nonlinear parameters more accurately. This study makes use of the Long-Term Pavement Performance database and machine learning techniques to improve the equations utilized to determine the nonlinear parameters crucial to estimate the resilient modulus of unbound base and subgrade materials.

Development of Structural Condition Index to Support Pavement Maintenance and Rehabilitation Decisions at Network Level

2003 ◽  
Vol 1827 (1) ◽  
pp. 10-17 ◽  
Author(s):  
Zhanmin Zhang ◽  
German Claros ◽  
Lance Manuel ◽  
Ivan Damnjanovic
Keyword(s):  
Evaluation Method ◽  
Surface Condition ◽  
Condition Index ◽  
Structural Condition ◽  
Pavement Management ◽  
Structural Deformation ◽  
Pavement Maintenance ◽  
State Highway ◽  
Structural Reinforcement ◽  
Maintenance And Rehabilitation

Every year, state highway agencies apply large amounts of seal coats and thin overlays to pavements to improve the surface condition, but these measures do not successfully address the problem. Overall pavement condition continues to deteriorate because of the structural deformation of pavement layers and the subgrade. To make effective decisions about the type of treatment needed, one should take into consideration the structural condition of a pavement. Several different structural estimators can be calculated by using falling weight deflectometer data and information stored in the Pavement Management Information System (PMIS) at the Texas Department of Transportation. The analysis considers pavement modulus and structural number as the structural estimators of a pavement. The evaluation method is based on the sensitivity of the structural estimators to deterioration descriptors. The deterioration per equivalent single-axle load of all major scores stored in the Texas PMIS is proposed as the primary indicator of pavement deterioration. In addition, the use of the structural condition index is recommended as a screening tool to discriminate between pavements that need structural reinforcement and those that do not. This index is calibrated for use in maintenance and rehabilitation analysis at the network level.

Determining Minimum Contract Time for Highway Projects

2000 ◽  
Vol 1712 (1) ◽  
pp. 196-201 ◽  
Author(s):  
Jin-Fang Shr ◽  
Benjamin P. Thompson ◽  
Jeffrey S. Russell ◽  
Bin Ran ◽  
H. Ping Tserng
Keyword(s):  
Low Cost ◽  
Road User ◽  
User Cost ◽  
Time Curve ◽  
Highway Projects ◽  
The Road ◽  
State Highway ◽  
Florida Department ◽  
The Cost ◽  
State Highway Agencies

An increasing number of state highway agencies (SHAs) are using A (cost) + B (time cost) bidding ( A + B bidding) for highway construction. The A + B bidding concept is designed to shorten the total contract time by allowing each contractor to bid the number of days in which the work can be accomplished, in addition to the traditional cost bid. The SHA is then presented with the problem of determining a reasonable range of contract time submitted by the bidders. Most SHAs do not currently restrict the range of B. However, several problems may arise from an unrestricted range of B. First, if no minimum is set for B, a bidder may inflate the cost bid and submit an unreasonably low B, using the excess cost bid to cover the disincentives charged for exceeding the time bid. Second, if no maximum is set for B, then a bidder with a high B and a low-cost bid may be awarded the job and make an unreasonable amount of money from incentive payments. This study develops a quantified model of the price-time bidding contract. A construction cost-versus-time curve is developed from Florida Department of Transportation (DOT) data. The contractor’s price-versus-time curve is then combined with the road-user cost to determine the optimum lower limit to be set on B. Finally, several projects completed by the Florida DOT will be used to illustrate this model.

Pay Factor Analysis for Highway Pavements through Percentage of Material within Specification Limits and Monte Carlo Simulation

2021 ◽  
pp. 036119812110255
Author(s):  
Yunpeng Zhao ◽  
Dimitrios Goulias
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Operating Characteristic ◽  
Production Quality ◽  
Specification Limits ◽  
State Highway ◽  
Long Run ◽  
Similar Materials ◽  
Pay Factor ◽  
State Highway Agencies

Many state highway agencies (SHAs) have adopted pay adjustment provisions in their acceptance plans for construction and materials. In these payment adjustment acceptance plans, the percentage of material within specification limits (PWL) has been selected as the quality measure to relate production quality to pay factors, and pay equations are used to determine a pay factor for a lot based on PWL. Various pay equations have been proposed by the highway community for adoption in SHAs’ specifications. However, the effectiveness of these pay equations has not been fully evaluated. Another issue concerning the pay adjustment acceptance plans is the risk associated with single and multiple pay factors. The purpose of this study was to evaluate the effects of different pay equations commonly used by SHAs and the risks associated with pay adjustment acceptance plans. This was achieved by developing operating characteristic curves associated with various pay factors and expected pay curves and Monte Carlo simulation for assessing the effects in the long run. The methodology suggested in this paper is transferable elsewhere where similar materials and specifications are used for the acceptance of pavements.

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