No full-text available
To read the full-text of this research,
you can request a copy directly from the authors.
An economic approach to road condition assessment using road user feedback: A new model and its application
Abstract
Assessing roadway assets condition is the prerequisite of an efficient road management system. It requires participation from the top management, equipment, trained human resources, and dedicated funding. Newfoundland and Labrador have 13,500 lane kilometers of roads, of which almost 7,700 kilometers belong to the local jurisdictions. Local agencies typically consult the Transportation Association of Canada's pavement management guidelines for managing the road networks. But, municipality roads require more specified guidelines considering issues like lack of human resources, equipment, inadequate funding, environmental factors, and public expectations. To better maintain these roads, evaluation of road conditions is the first step. However, a proper evaluation system needs considerable funding, a trained workforce, and necessary equipment. Hence, the idea of using road users’ feedback is introduced in this paper. Citizens from 108 municipalities of the province participated in a feedback survey where they were asked questions about roadway assets condition. The survey resulted in a significant amount of data. First, an exploratory analysis of the road users’ feedback data was conducted. Then, a simple distress-based pavement performance model was developed. This model can be adopted by the local agencies as a simple decision-making tool. To make the model practical, a smartphone application called MUNPave is also introduced in this paper.
... Pavement structures exhibit different types of distress due to traffic loading and environmental conditions, such as rutting (Kim et al., 2000;Perraton et al., 2010;Wang et al., 2022), fatigue cracking (Di Benedetto et al., 2004;Luo et al., 2018;Mbarki et al., 2012), thermal cracking (Alavi et al., 2015;Dave & Buttlar, 2010;Epps, 2000), or surface texture deterioration (Mansura et al., 2018;Xiao et al., 2020). These distress types have multiple effects on road networks; they increase the pavement roughness (Múčka, 2016;Sandra & Sarkar, 2013), reduce road user comfort (Ahlin & Granlund, 2011;Guha & Hossain, 2022), increase vehicle fuel consumption (Perrotta et al., 2019;Svenson & Fjeld, 2015) which increases CO 2 emissions, raise the number of road user compensation claims (Asphalt Industry Alaiance, 2022), and increase the risks of traffic accidents (Chan et al., 2010;Tamakloe et al., 2021). It is therefore of paramount importance to monitor pavement surface condition and assess the extent of the distress to minimise these effects and manage road networks efficiently. ...
... For example, many municipalities in Newfoundland and Labrador are run by volunteers as there are not enough people to operate municipality offices. In that case, road users' feedback can be utilized to develop a pavement performance model (36). An approach to this type of model has been described in a journal. ...
Regional pavement management agencies often suffer from inadequate resources and technical people to carry out maintenance tasks efficiently. Though funding shortage is an issue for most agencies, regional agencies confront it primarily for various reasons such as the class of the roads managed by them, traffic intensity, the size of service population, and the jurisdiction. Regional agencies generally manage lower functional classes of roads that usually carry smaller traffic. Though low-volume roads (LVRs) take just 20% of the traffic, LVRs include approximately 80% of transportation system mileage. With only 20% of the traffic volume and 80% mileage in transportation, LVRs can barely compete with the return on investment of highways. As a result, regional road networks are always subject to less attention from policymakers. In this context, this research proposes a pavement management framework for the regional agencies which is economical, requires minimum technical expertise, and is easy to implement. This study includes two surveys: The Canada-wide Pavement Management Survey and the Road Users Feedback Survey. The Canada-wide Pavement Management Survey provides an overview of pavement management practices in Canada at the regional level. The concept of Pavement Management System (PMS) score is also developed utilizing the same survey responses. Findings from the Road Users Feedback Survey have been used to understand the feasibility of using road users’ feedbacks in making management decisions. Overall results from these two surveys have been utilized to develop various components of the proposed PMS framework.
There exists two factors to assist in deciding whether or not a municipality should expect to have a roadway management system, these being population size and road network size. A large population tends to contribute more vehicles to the roads, which leads to frequent maintenance needs and therefore requires a road management system. Municipalities with large road networks may choose to follow a road management guideline to optimize their maintenance schedules. But, in some cases, municipalities with only a few kilometers of roadway can play a vital role in the provincial road network, especially when those roads link important destinations. So, a few pertinent questions arise. Do population size and road network length determine whether a municipality or town adopts a road management system? How do municipalities with small population size and shorter road networks manage their roads? What can be the most feasible way for those municipalities to manage their roads? To answer these questions, a province-wide municipality staff survey was conducted in Newfoundland and Labrador (NL), Canada. Most of the municipalities in this province are sparsely populated, and the internal road networks are very small. The survey was conducted to determine the condition of the roadway assets in these small municipalities, the resources available, and the requirements of roadwork by transportation departments to do in order to improve their roads. This project was not a government-funded project, and there was no incentive for the participants. Therefore, participation was completely voluntary. The results provide significant information about roadway asset conditions and management systems in the municipalities.
Roads are an important aspect of the efficiency gains that stem from population density: the more people live on a given road network, the less each person must pay for paving, maintenance, and snow clearing. While density is related to the road length per resident, the two variables are not synonymous. Two urban areas may have the same spatial extent and population, yet feature distinct road network morphologies, resulting in different values for road length per resident. Road length per resident measures a major category of costs directly, as a large proportion of many municipal budgets are dedicated to road maintenance. A better understanding of road length per resident can therefore support financially prudent urban development policy. The primary objective of this research is therefore to investigate how road length per resident varies with density between the sub-geographies of cities. Nine cities from across Canada were selected and the road length per resident and net density of their census tracts were calculated. The results present a strong and consistent non-linear association between population density and road length per resident. The present analysis is most valuable for distinguishing between medium-density and low-density suburbs. The results suggest that a shift may be necessary in how urban theorists communicate the costs of low-density growth.
In many current state-of-the-art bridge management systems, Markov models are used for both the prediction of deterioration and the determination of optimal intervention strategies. Although transition probabilities of Markov models are generally estimated using inspection data, it is not uncommon that there are situations where there are inadequate data available to estimate the transition probabilities. In this article, a methodology is proposed to estimate the transition probabilities from mechanistic-empirical models for reinforced concrete elements. The proposed methodology includes the estimation of the transition probabilities analytically when possible and when not through the use of Bayesian statistics, which requires the formulation of a likelihood function and the use of Markov Chain Monte Carlo simulations. In an example, the difference between the average condition predicted over a 100-year time period with a Markov model developed using the proposed methodology and the condition predicted using mechanistic-empirical models were found to be 54% of that when the state-of-the-art methodology, i.e., a methodology that estimates the transition probabilities using best fit curves based on yearly condition distributions, was used. The variation in accuracy of the Markov model as a function of the number of deterioration paths generated using the mechanistic-empirical models is also shown.
The road section of Palur-Sragen-Mantingan categorized as a national road and serve 43.00km long arterial road, is the part of the middle lane that connects the important cities in Java Island. The damage that frequently occurs will certainly affect the safety and comfort of road users. Road surface condition assessment is one step to determine the type of program evaluation needs to be done. This study aims to determine the functional condition of the road by three methods and to assess the closeness of the relationship between these three methods. The descriptive study is carried out to conduct the comparability of the road condition assessment data resulted from three methods for analyzing the results of the assessment of road conditions between the years of 2011-2013. The assessment method of road conditions consists of the International Roughness Index, the Pavement Condition Index and the Surface Distress Index. The correlation between these methods were obtained from the Pearson correlation analysis based on CurveExpert program. The results showed that the linear regression analysis between the methods of IRI and PCI showed the value of PCI=0.966+10.919IRI, it means there is a positive correlation between the two methods and the r value is 0.976 indicates a very close correlation between the two methods. IRI and SDI method show the value of SDI=32.684+3.355IRI, it means a positive correlation between the two methods and the r value is 0.203 indicates a poor relation between the two methods. PCI and SDI method show the value of SDI=18.023+0.592PCI, it means there is a positive correlation between the two methods and the r value is 0.381 indicates a poor relation between the two methods. Limited from this research, the conclusion could be drawn that the different method of functional measurements could potentially result in the different pavement index, consequently the different decision for pavement and rehabilitation scheme.
Nonstructural factors, such as surface distresses and ride quality, have been commonly used as the main indicators of in-service pavement conditions. In the last decade, the concept of implementing a structural condition index in pavement management system (PMS) to complement functional condition indices has become an important goal for many highway agencies. The rolling wheel deflectometer (RWD) provides the ability to measure pavement deflection while operating at the posted speed limits causing no user delays. The objective of this study was to develop a model to predict pavement structural capacity at a length interval of 0.16 km (0.1 mi) based on RWD measurements and to assess its effectiveness in identifying structurally deficient pavement sections. Rolling wheel deflectometer data collected from 153 road sections (more than 1,600 km) in District 05 of Louisiana were used in this study. The predicted structural number (SNRWD0.16) showed an acceptable accuracy with a root-mean square error (RMSE) of 0.8 and coefficient of determination (R²) of 0.80 in the validation stage. Core samples showed that sections that were predicted to be structurally deficient suffered from asphalt stripping and material deterioration distresses. Results support that the developed model is a valuable tool that could be used in PMS at the network level to predict pavement structural condition with an acceptable level of accuracy.
Traffic on a road pavement is characterized by a large number of different vehicle types, and these can be considered in pavement design by using truck factors to transform the damage they apply to the pavement to the damage that would be applied by a standard axle. The truck factors to convert trucks into standard axles or the load equivalent factors to convert axles into standard axles are defined by considering the average loads for each axle. This process includes the vehicles that travel with axle loads above the maximum legal limit. There are also a substantial number of overloaded vehicles in terms of total vehicle weight. These axles/vehicles cause significant damage to the pavements, increasing the pavement construction and rehabilitation cost. Thus, this paper investigates the impact of overloaded vehicles on road pavements by studying the truck factors for different vehicle cases applied to a set of pavements composed of five different asphalt layer thicknesses and five different subgrade stiffness moduli. The study revealed that the presence of overloaded vehicles can increase pavement costs by more than 100% compared to the cost of the same vehicles with legal loads. (C) 2013 American Society of Civil Engineers.
The pavement performance modeling is an essential part of pavement
management system (PMS). It estimates the long-range investment requirement and
the consequences of budget allocation for maintenance treatments of a particular
road segment on the future pavement condition. The performance models are also
applied for life-cycle economic evaluation and for the prioritization of pavement
maintenance treatments. This chapter discusses various deterministic and stochastic
approaches for calculating the pavement performance curves. The deterministic
models include primary response, structural performance, functional performance,
and damage models. The deterministic models may predict inappropriate pavement
deterioration curves because of uncertain pavement behavior under fluctuating
traffic loads and measurement errors. The stochastic performance models assume
the steady-state probabilities and cannot consider the condition and budget constraints
simultaneously for the PMS. This study discusses the Backpropagation
Artificial Neural Network (BPN) method with generalized delta rule (GDR) learning
algorithm to offset the statistical error of the pavement performance modeling.
This study also argues for the application of reliability analyses dealing with the
randomness of pavement condition and traffic data.
This paper proposes a mechanistic-empirical pavement damage model to predict changes in 3D road profiles due to dynamic axle loads. The traffic is represented by a fleet of quarter cars which allows for statistical variability in model parameters such as velocity, suspension stiffness, suspension damping, sprung mass, unsprung mass and tyre stiffness. The fleet model generates statistical distributions of dynamic force at each point which are used to predict pavement damage. As the pavement deteriorates, the distributions of dynamic axle force are changed by the changing road profile. This paper introduces a 3D approach – the transverse position of the wheel is represented by a Laplace probability distribution. This influences the extent to which the force patterns are spatially repeatable. Differences in the range of 10–30% are found between 2D and 3D predictions of pavement life.
The Chi-square statistic is a non-parametric (distribution free) tool designed to analyze group differences when the dependent variable is measured at a nominal level. Like all non-parametric statistics, the Chi-square is robust with respect to the distribution of the data. Specifically, it does not require equality of variances among the study groups or homoscedasticity in the data. It permits evaluation of both dichotomous independent variables, and of multiple group studies. Unlike many other non-parametric and some parametric statistics, the calculations needed to compute the Chi-square provide considerable information about how each of the groups performed in the study. This richness of detail allows the researcher to understand the results and thus to derive more detailed information from this statistic than from many others.
The Chi-square is a significance statistic, and should be followed with a strength statistic. The Cramer’s V is the most common strength test used to test the data when a significant Chi-square result has been obtained. Advantages of the Chi-square include its robustness with respect to distribution of the data, its ease of computation, the detailed information that can be derived from the test, its use in studies for which parametric assumptions cannot be met, and its flexibility in handling data from both two group and multiple group studies. Limitations include its sample size requirements, difficulty of interpretation when there are large numbers of categories (20 or more) in the independent or dependent variables, and tendency of the Cramer’s V to produce relative low correlation measures, even for highly significant results.
A method is described for modeling the sensitivity, specificity, and positive and negative predictive values of a diagnostic test. To model sensitivity and specificity, the dependent variable (Y) is defined to be the dichotomous results of the screening test, and the presence or absence of disease, as defined by the "gold standard", is included as a binary explanatory variable (X1), along with variables used to define the subgroups of interest. The sensitivity of the screening test may then be estimated using logistic regression procedures. Modeled estimates of the specificity and predictive values of the screening test may be similarly derived. Using data from a population-based study of peripheral arterial disease, the authors demonstrated empirically that this method may be useful for obtaining smoothed estimates of sensitivity, specificity, and predictive values. As an extension of this method, an approach to the modeling of the relative sensitivity of two screening tests is described, using data from a study of screening procedures for colorectal disease as an example.
Pavement Life Cycle Assessment (LCA) is a comprehensive method to evaluate the environmental impacts of a pavement section. It employs a cradle-to-grave approach assessing critical stages of the pavement's life. Previous LCA case studies used a wide variety of different functional units and factors in order to achieve different goals and scopes. These inconsistent functional units and factors create confusion in understanding the complete picture of environmental impact during the initial construction. Therefore, a set of models of pavement LCA considering every factor of the pavement life cycle phases is needed. Canada is a very large country and the different provinces have different pavement construction practices. Therefore, the goal of this work is to develop a set of useful models for quantifying CO 2 emission from pavement construction in Canada. A total of 141 Canadian road sections from the Long Term Pavement Performance (LTPP) database are considered to develop models using machine learning algorithms: multiple linear regression, polynomial regression, decision tree regression and support vector regression. These models determine the significant contributors and quantify the CO 2 emission in material production, initial construction, maintenance and use phase. The study also reveals the contribution of Canadian provinces' CO 2 emission involved in the life of a pavement.
Pavement conditions will reduce the level of service over time. It is characterized by the occurrence of structural damage of the road pavement layers in which the neglect for a long period can worsen the condition of the pavement layers that can affect the traffic safety and comfort. Road pavement performance is determined based on the requirements of the functional and structural condition. The functional conditional requirements relate to roughness, pavement surface aggravation, while the structural condition requirements relate to the pavement strength or carrying capacity in serving the load and the traffic flow. The aim of this research is to evaluate the functional and structural of the flexible pavement on south arterial road in Yogyakarta and to provide recommendation of maintenance and rehabilitation. The functional evaluation of pavement is based on DGH and PCI method, which combines International Roughness Index (IRI) and Pavement Condition Index (PCI) values, while structural pavement evaluation is performed by analyzing the deflection value of Falling Weight Deflectometer (FWD) measurement analyzed by AASHTO 1993 with the output being the Structural Number (SN) value, where SN effective/SNfuture ratio results Structural Condition Index (SCI) value which determines whether a pavement requires overlay or not. The results of functional analysis based on IRI and PCI values indicate that the road conditions for each segment are good, damaged and heavily damaged. The structural analysis for 2018 shows all segments yield SCI value<1, which means they require an overlay. The segments requiring functional overlay are Km 00 + 000 up to 02 + 400, Km 04 + 400 up to 05 + 600, Km 07 + 600 up to 13 + 200, Km and Km 16 + 000 up to 18 + 400. Meanwhile, the segments that require structural overlay are: Km 02 + 400 up to 04 + 400, Km 05 + 600 up to 07 + 600 and Km 13 + 200 up to 16 + 000.
A simple phenomenological damage model based on the number of load applications, the critical response, and the material modulus was used with three sets of experimental data: (a) the decrease in the modulus of an asphalt concrete (AC) under laboratory, direct tension fatigue testing; (b) the decrease in the modulus of a pozzolan–lime-stabilized sand under accelerated loading in a full-scale pavement testing facility; and (c) the increase in the permanent strain at three levels of two subgrade materials, also under full-scale accelerated loading. The model is shown to be capable of describing the damage reasonably well for all three cases, though with some limitations. For the direct tension tests with AC, the rate of damage was underpredicted for two of six samples under controlled stress testing, whereas the prediction for all 10 controlled strain tests was good. For freeze–thaw conditions, the model for permanent strain in the subgrade also tended to underpredict the damage rate. The simple damage model may be useful for incremental–recursive pavement design or for pavement management systems.
Comprehensive and practical, Pavement Asset Management provides an essential resource for educators, students and those in public agencies and consultancies who are directly responsible for managing road and airport pavements. The book is comprehensive in the integration of activities that go into having safe and cost-effective pavements using the best technologies and management processes available. This is accomplished in seven major parts, and 42 component chapters, ranging from the evolution of pavement management to date requirements to determining needs and priority programming of rehabilitation and maintenance, followed by structural design and economic analysis, implementation of pavement management systems, basic features of working systems and finally by a part on looking ahead.
Many modifications build on Tukey's original box plot. A proposed further adaptation, the violin plot, pools the best statistical features of alternative graphical representations of batches of data. It adds the information available from local density estimates to the basic summary statistics inherent in box plots. This marriage of summary statistics and density shape into a single plot provides a useful tool for data analysis and exploration.
The coming of the new millennium provides an excellent time to pause and consider where the low-volume road (LVR) community is headed. This paper summarizes issues and opportunities for the LVR community worldwide in the new millennium. LVRs provide the primary links to the highway transportation system. They provide links from homes and farms to markets and for raw materials from forests and mines to mills, and they provide public access to essential health, education, civic, and outdoor recreational facilities. The LVR link between raw materials and markets is critical to economies locally and nationally in all countries around the world. Just what constitutes an LVR depends on an individual's perspective. At the high end, LVRs may be two-lane asphalt paved roads with up to 2,000 vehicles per day. A widely recognized LVR definition sets the upper limit at 400 vehicles per day. Some differentiate urban LVRs from farm-to-market rural LVRs. Many LVRs around the world consist of a single lane with gravel or even native surfacing. In some remote areas of the world, LVRs follow travel routes many centuries old. In developing areas, LVRs may be the first steps up from human and animal pack trails, or they may be all-new roads opening new territory. Even in developed areas, low traffic volumes at the ends of the transportation network may warrant roads with low conventional design standards. LVRs often just evolved, and engineering was an afterthought. Traditionally, LVRs have not provided the volume of business, funding, or glamour to attract and support a specialized field of engineering. When involved with LVRs, engineers used the best information available. They extended their experience and training in higher-standard roads, pavements, or structures to LVR situations, even though they may have recognized the standards as excessive. The Committee on Low-Volume Roads was established to fill this technology gap, to provide a forum for exploring and exchanging experiences on engineering appropriate to LVRs. Interest in LVRs spans the full range of transportation engineering—planning, route investigation, geometric design, pavements, structures, construction, operations, maintenance, safety, and so forth. It is essential to adopt the rather nonspecific definition for LVRs to include rather than exclude people in this forum, while recognizing that the actual engineering standards may vary significantly even within the range of LVRs. Hence, developing liaisons with people with expertise in other specific areas of technology is essential. The fewer the road users, the less funding is available for road maintenance and restoration, much less engineering. Consequently, LVRs around the world typically need reconstruction and improvement. Many factors in addition to funding further complicate LVR engineering: Transportation in the New Millennium 2 • Whereas they carry only 20 percent of the traffic, LVRs include 80 percent of the transportation system mileage. • Although traffic volumes may be low, vehicle loads may be high. • Traditional high-volume highway engineering standards may not be appropriate. • The highest-volume, highest-rate-of-return proposals receive priority for limited research funding. • Existing LVR conditions sometimes constrain and camouflage high traffic volume demand. • LVRs often mix unconventional traffic (e.g., farm machinery, bicycles, and oxcarts) with highway passenger cars, buses, and trucks. • Few data concerning LVR performance, cost, use, and so forth are available. These challenges provide a wealth of opportunities for enhancing LVR engineering.
Many government agencies and private consulting companies manage large pavement networks in terms of infrastructure condition assessment and maintenance planning. Efficient pavement management is supported by pavement management systems (PMSs), which includes models for pavement condition assessments considered “valuable” by agency's engineers. The objective of this article is to define a pavement condition model able to overcome surveyors’ subjectivity in rating distresses and thus provide meaningful pavement conditions for the agencies to employ in project planning. The article proposes a fuzzy inference model for calculating pavement condition ratio (PCR) specifically tailored on the Alabama Department of Transportation Pavement (ALDOT) guidelines and policies. Applied to several surveyors’ ratings, the proposed model has the ability to smooth distress extent differences among surveyors producing PCR values within acceptable range of variability. The proposed approach has the intention of not only enhancing pavement condition characterization but also to exploit the opportunity made available by automation in the collection and interpretation of pavement data which are anyway characterized by an inherent subjectivity.
Many modifications build on Tukey's original box plot. A proposed further adaptation, the violin plot, pools the best statistical features of alternative graphical representations of batches of data. It adds the information available from local density estimates to the basic summary statistics inherent in box plots. This marriage of summary statistics and density shape into a single plot provides a useful tool for data analysis and exploration.
A simple phenomenological damage model based on the number of load applications, the critical response, and the material modulus was used with three sets of experimental data: (a) the decrease in the modulus of an asphalt concrete (AC) under laboratory, direct tension fatigue testing; (b) the decrease in the modulus of a pozzolan-lime-stabilized sand under accelerated loading in a full-scale pavement testing facility; and (c) the increase in the permanent strain at three levels of two subgrade materials, also under full-scale accelerated loading. The model is shown to be capable of describing the damage reasonably well for all three cases, though with some limitations. For the direct tension tests with AC, the rate of damage was underpredicted for two of six samples under controlled stress testing, whereas the prediction for all 10 controlled strain tests was good. For freeze-thaw conditions, the model for permanent strain in the subgrade also tended to underpredict the damage rate. The simple damage model may be useful for incremental-recursive pavement design or for pavement management systems.
The state of Michigan has 191 432 km (118,950 mi) of roadway (paved and unpaved), including highways, roads, and streets. Local government agencies, which are responsible for 176 270 km (109,529 mi) of these roads and streets, commonly use a pavement management system (PMS) called RoadSoft to assist in managing their pavement network. A key element of any PMS is its ability to predict future pavement performance. A study is described in which various deterministic and probabilistic models were evaluated using data from two Michigan counties. It was found that the logistic growth model and the Markov model provided the best combination of predictive ability and potential for applicability in Michigan counties. A comparison between these models found that their predictive ability for four pavement segments with different deterioration rates was good, with the Markov model offering the added advantage of representing future performance as a probability distribution, not as a single condition state. Current plans are to implement the logistic growth model in RoadSoft by the end of 1999 and to add the Markov model as local organizations gather sufficient pavement condition data over the next 5 years. It is hoped that these two pavement deterioration models can be implemented in the RoadSoft PMS to improve pavement performance prediction.
The object of this investigation was to develop a procedure for making optimal maintenance decisions for a deteriorating system. The particular system chosen for study is a pavement, and a methodology is developed to ensure that pavements meet certain performance criteria while minimizing the expected maintenance cost. A cumulative damage model based upon a Markov process was developed to model pavement deterioration. The optimal repair action for each possible pavement state in the planning horizon was found by means of probabilistic dynamic programming. Sample sequences of repair actions were generated during a simulation in which the optimal repair policy was applied to sample pavement condition histories. Several sensitivity studies were performed to study the variation in expected cost, including the effect of delaying the optimal program.
The objective of this study is to evaluate pavement damage due to new tire designs using accelerated pavement testing (APT) and finite element (FE) modeling. Three tire configurations were investigated in this study, including the newly developed wide-base tire (455/55R22.5), an older generation of wide-base tire (425/65R22.5), and the conventional dual-tire configuration. Four full-depth flexible pavement sections with three various hot-mix-asphalt (HMA) thicknesses (6, 10 and 16.5 in. [152, 254, and 420 mm]) were exposed to APT. The measured tensile strains at the bottom of the HMA were compared under various tire loading conditions. A three-dimensional (3D) FE model was successfully developed to predict the pavement responses caused by various tire configurations and validated by field measurements. The developed 3D FE model incorporates the measured 3D tire-pavement contact stresses, HMA linear viscoelasticity, continuous moving load, and implicit dynamic analysis. Results of pavement damage analysis indicate that the wide-base 455 tire causes greater fatigue damage and subgrade rutting than the conventional dual-tire assembly does when carrying the same load. However, the relative damage ratios between various configurations at the same load decrease as the pavement thickness increases. On the other hand, the wide-base 455 tire causes less top-down cracking, “near-surface” cracking, and HMA rutting damage than the conventional dual-tire assembly does. Generally, the results show that using a wide-base 455 tire results in the least amount of pavement damage for an interstate road, slightly greater damage for a primary road, and more damage for a local road. ICT-R59 published or submitted for publication is peer reviewed
Items such as physical exam findings, radiographic interpretations, or other diagnostic tests often rely on some degree of subjective interpretation by observers. Studies that measure the agreement between two or more observers should include a statistic that takes into account the fact that observers will sometimes agree or disagree simply by chance. The kappa statistic (or kappa coefficient) is the most commonly used statistic for this purpose. A kappa of 1 indicates perfect agreement, whereas a kappa of 0 indicates agreement equivalent to chance. A limitation of kappa is that it is affected by the prevalence of the finding under observation. Methods to overcome this limitation have been described.
Pavement management for low-volume roads
- C W Blair
- E G Bates
- D M Drevinsky
Blair, C. W., Bates, E. G., and Drevinsky, D. M, 1984. Pavement management for low-volume roads. Transportation Research Record, 2, 43-54.
Decision making for maintenance and rehabilitation of municipal pavements
- J Hajek
- D Hein
- C Olidis
Hajek, J., Hein, D., and Olidis, C, 2004. Decision making for maintenance and rehabilitation of municipal pavements. In: Tac/ATC 2004
-2004 Annual Conference and exhibition of the Transportation
Association of Canada: Transportation innovation -accelerating the
pace.
Concepts of pavement performance prediction and modeling
- R Lytton
Lytton, R., 1987. Concepts of pavement performance prediction and modeling. In: Second north American Conference on managing pavements,
p. G-1-G-33.
Development of pavement performance models for Delhi township, ohio pavement management system
- A Sotil
- K E Kaloush
Sotil, A., and Kaloush, K.E., 2004. Development of pavement performance
models for Delhi township, ohio pavement management system. In:
Compendium of papers CD-ROM 83rd Annual meeting of the
Transportation Research board.