scholarly journals On the Applicability of Laser Scanning for Evaluation of the Pavement Serviceability Parameters

2021 ◽  
Vol 906 (1) ◽  
pp. 012138
Author(s):  
Veronika Valaskova ◽  
Jozef Vlcek ◽  
Alicja Kowalska-Koczwara
Keyword(s):  
Laser Scanning ◽  
Surface Condition ◽  
The State ◽  
Pavement Management ◽  
International Roughness Index ◽  
Pavement Management System ◽  
Operational Conditions ◽  
Pavement Surface ◽  
Roughness Surface ◽  
Complex Knowledge

Abstract Pavement performance is influenced by man factors such as climate and environmental conditions, traffic and operational conditions and type of pavement. These factors cause a pavement deterioration what leads to the restriction of the pavement serviceability or pavement efficiency. The pavement serviceability is the ability of the pavement to fulfil the service function represented by the actual values of variable parameters such as pavement surface roughness, surface evenness, pavement surface condition. The state of the pavement is assessed using different performance indicators when International Roughness Index (IRI) is most used. This approach allows to classify the state of the pavement in the pavement management system as a most used indexing, generalizes the pavement surface to the response of the testing car tire and the pavement. Laser scanning presented in this paper is able to bring the knowledge about the real pavement surface considering the accuracy of the method and equipment. Realized laser scanning proved the applicability of this method for the measurement of the pavement surface. Because of the complex knowledge of the pavement surface morphology, we can evaluate the pavement serviceability in terms of roughness, surface evenness or even pavement surface condition (rutting or cracks).

Investigating the performance of Superpave through the mechanistic–empirical (M-E) approach, field-evaluated performance, and laboratory test results: a case study on Ontario highways

2020 ◽  
Vol 47 (8) ◽  
pp. 954-961
Author(s):  
Gulfam E. Jannat ◽  
Sina Varamini ◽  
Susan L. Tighe
Keyword(s):  
Permanent Deformation ◽  
Asphalt Binder ◽  
Pavement Management ◽  
Test Results ◽  
International Roughness Index ◽  
Pavement Management System ◽  
Evaluation Of Performance ◽  
Laboratory Test Results ◽  
Analysis System

In North America, highway agencies have started using Superpave as it incorporates a performance-based asphalt binder specification and a mix design analysis system. However, in a pavement management system (PMS), the performance of the pavement structure significantly influences management decisions. In this regard, accurate prediction and evaluation of performance is a very important aspect. With this in mind, this study investigates the performance of Superpave through the mechanistic–empirical (M-E) approach, field-evaluated performance, and laboratory performance tests. It considers 15 sections of highways from Ontario. The investigation found that the international roughness index (IRI) and permanent deformation are overpredicted in the M-E approach compared with field observations. Additionally, to better understand the performance, the dynamic modulus of asphalt mixtures and binder rheological testing are also performed. The master curve developed for the surface mixtures suggests a lower level of fatigue resistance that justifies the bottom-up fatigue failure in the field-observed scenarios.

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.

scholarly journals Evaluating the asphalt pavement's surface characteristics by field testing

2020 ◽  
Vol 19 (3) ◽  
pp. 474-485
Author(s):  
Derya Kaya Ozdemir ◽  
◽  
Ali Topal ◽  
Bulent Kacmaz ◽  
Burak Sengoz
Keyword(s):  
Laser Scanning ◽  
Asphalt Pavement ◽  
Heavy Traffic ◽  
Textural Properties ◽  
Surface Characteristics ◽  
Pavement Management ◽  
Driving Safety ◽  
Scanning System ◽  
Frictional Properties ◽  
Pavement Surface

Pavement management systems are crucial because of monitoring the current pavement condition to supply safe, efficient, comfortable and durable riding surface for vehicles. Driving safety is the most important issue, which is closely related to pavement surface texture. The texture of the pavement surface and its ability to resist the polishing effect of heavy traffic is an important parameter in providing necessary skidding resistance during the service life. In this study, 4 different asphalt pavement sections located in Izmir/TURKEY with having different traffic characteristics were investigated every three months for two years aiming to evaluate the effect of traffic volume on the surface textural and frictional properties of the pavement. The textural properties were evaluated using sand patch test (SPT) and a 3D Laser Scanning System (LSS), while Dynamic Friction Tester (DFT) was employed to assess the frictional properties. As a result, lower Mean Texture Depth (MTD) and Mean Profile Depth (MPD) values were obtained for the increased traffic volumes. High correlation was derived between macro and micro textural properties of the asphalt pavement. Additionally, the textural and frictional properties were found highly related for the investigated asphalt pavement surfaces.

Forecasting Overall Pavement Condition with Neural Networks: Application on Florida Highway Network

2003 ◽  
Vol 1853 (1) ◽  
pp. 3-12 ◽  
Author(s):  
Jidong Yang ◽  
Jian John Lu ◽  
Manjriker Gunaratne ◽  
Qiaojun Xiang
Keyword(s):  
Neural Networks ◽  
Surface Condition ◽  
Composite Index ◽  
Critical Issue ◽  
Pavement Management ◽  
Pavement Condition ◽  
Pavement Surface ◽  
Condition Rating ◽  
Highway Network ◽  
Ann Models

Timely identification of undesirable crack, ride, and rut conditions is a critical issue in pavement management systems at the network level. The overall pavement surface condition is determined by these individual pavement surface conditions. A research project was carried out to implement an overall methodology for pavement condition prediction that uses artificial neural networks (ANNs). In the research, three ANN models were developed to predict the three key indices—crack rating, ride rating, and rut rating—used by the Florida Department of Transportation (FDOT) for pavement evaluation. The ANN models for each index were trained and tested by using the FDOT pavement condition database. In addition to the three key indices, FDOT uses a composite index called pavement condition rating (PCR), which is the minimum of the three key indices, to summarize overall pavement surface condition for pavement management. PCR is forecast with a combination of the three ANN models. Results of the research suggest that the ANN models are more accurate than the traditional regression models. These ANN models can be expected to have a significant effect on FDOT's pavement management system.

Engineering Application of Washington State’s Pavement Management System

1998 ◽  
Vol 1643 (1) ◽  
pp. 25-33
Author(s):  
Michael J. Baker ◽  
Joe P. Mahoney ◽  
Nadarajah “Siva” Sivaneswaran
Keyword(s):  
Management System ◽  
Construction Material ◽  
Engineering Application ◽  
Structural Condition ◽  
Washington State ◽  
The State ◽  
Pavement Management ◽  
Pavement Performance ◽  
Pavement Management System ◽  
Analysis Group

Previous investigation into the Washington State Department of Transportation’s (WSDOT) Pavement Management System (WSPMS) revealed pavement sections on the state route system that were outperforming or underperforming other pavement sections constructed of similar materials and subjected to similar traffic and environmental conditions. Reasons were not clear. The WSPMS was used to identify superior and inferior candidate pavements for further investigation. All state route pavements were stratified into 18 distinct analysis groups, and population statistics were generated for each group providing WSDOT with a snapshot of the current “state of the state route system” and providing the basis for selecting candidate pavements. The five performance measures considered included: age of the surface course, a distress-based pavement structural condition score, annual design-lane equivalent single axle loads, roughness (in terms of International Roughness Index), and rutting. Results of the analysis suggest that WSDOT is properly designing layer thicknesses at appropriate reliability levels. Also, in 6 of 10 analysis group comparisons, inferior pavements were actually thicker than superior pavements. Both findings suggest that thickness design factors are not the primary cause of inferior performance in Washington State; construction, material and site specific factors are likely the cause. Additionally, in an international effort to exchange information on pavement performance and construction practices, highlights of a comparative study of pavement performance with South Africa’s Gauteng Department of Transportation are presented.

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.

Pavement surface friction and noise: integration into the pavement management system

2010 ◽  
Vol 37 (10) ◽  
pp. 1331-1340 ◽  
Author(s):  
M. Alauddin Ahammed ◽  
Susan L. Tighe
Keyword(s):  
Noise Exposure ◽  
Surface Friction ◽  
Surface Characteristics ◽  
Pavement Management ◽  
Value Engineering ◽  
Asphalt Pavements ◽  
Pavement Management System ◽  
Pavement Surface ◽  
Sound Barriers ◽  
Using Data

Pavement surface friction is an essential attribute of highway safety. The desired surface friction should also accommodate the seasonal and long-term variations. The available surface friction depends mainly on microtexture and macrotexture on pavement surfaces. An increased surface texture for increased and durable friction may increase the roadway noise, which is also a growing problem. Traditional sound barriers, constructed to reduce noise exposure, are very expensive. As the pavement surface characteristics play a key role in roadway noise generation, it provides a window for noise reduction by altering the pavement surface. The challenge, however, is to provide a smooth, quiet, long-lasting, and economic pavement with adequate and durable surface friction. This paper addresses this challenge and provides a realistic guideline. The correlation of tire–road noise and surface friction is examined using data collected from five different asphalt pavements. Frameworks for desired minimum surface friction and maximum roadway noise are provided. A modified value-engineering approach is proposed to accommodate the construction and maintenance costs, longevity, smoothness, safety, and noise in the selection of pavement surfaces.

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