Assessment of Long-Term Pavement Performance Program Manual Distress Data Variability: Bias and Precision

1997 ◽  
Vol 1592 (1) ◽  
pp. 151-168 ◽  
Author(s):  
Gonzalo R. Rada ◽  
Rajesh K. Bhandari ◽  
Gary E. Elkins ◽  
William Y. Bellinger
Keyword(s):  
Prediction Models ◽  
Survey Methods ◽  
Ground Truth ◽  
Condition Index ◽  
Pavement Performance ◽  
Severity Level ◽  
Data Variability ◽  
Rater Variability ◽  
The Individual

The use of manual survey methods within the Long-Term Pavement Performance (LTPP) program for the collection of distress data has drastically increased both in intensity and in coverage over the past couple of years. Because these surveys are conducted by individual raters whose biases can lead to variability between raters, it was hypothesized that distress data variability existed and that it could potentially be quite large. Thus, the purpose of the presented study was to quantify manual distress data variability, with special emphasis on the bias and precision of the data. Results from seven LTPP program distress rater accreditation workshops conducted during the period from 1992 to 1995 were used as the only source of data. On the basis of analyses of these data, both the apparent bias and the precision for the common distress type-severity level combinations were quantified. It was also concluded from this study that individual rater variability for any given distress type-severity level combination is typically large and increases as the distress quantity increases; however, when all distress type-severity level combinations are viewed in terms of a single composite number such as the pavement condition index value, there is excellent agreement between the individual raters, the group mean, and the ground truth value, and individual rater variability is also quite small. Because LTPP program distress data are to be used in the development of pavement performance prediction models, improvements in variability are highly desirable to ensure that they serve their intended purpose. Recognizing that the LTPP program distress raters are experienced individuals, such improvements are not envisioned to come through additional training. It is the authors’ contention that the only way of achieving the desired improvement is through the conduct of group consensus surveys.

Update of Long-Term Pavement Performance Manual Distress Data Variability: Bias and Precision

1998 ◽  
Vol 1643 (1) ◽  
pp. 71-79 ◽  
Author(s):  
Gonzalo R. Rada ◽  
Chung L. Wu ◽  
Gary E. Elkins ◽  
Rajesh K. Bhandari ◽  
William Y. Bellinger
Keyword(s):  
Data Collection ◽  
Prediction Models ◽  
Survey Methods ◽  
Quality Data ◽  
Pavement Performance ◽  
Pavement Condition ◽  
Pavement Distress ◽  
Black And White ◽  
Pavement Performance Prediction

Pavement distress surveys based upon field interpretation and manual mapping and recording of the distress information on paper forms has been used in the Long-Term Pavement Performance (LTPP) program to collect important pavement condition and distress data. Although this manual method was used in the past as a backup to the 35-mm black and white photographic-based method, recently the use of manual distress survey methods has increased in intensity and coverage. To promote uniformity and consistency of distress data collection, one of the early LTPP efforts was to develop standard definitions, measurement procedures and data collection forms. Various quality control and quality assurance functions have also been implemented to provide for high quality data. However, despite these efforts, manual surveys are still based upon a single rater’s subjective classification of distresses present in the field. Recognizing that rater variability exists, a study was undertaken by FHWA to assess the level of variability between individual distress raters and to address the potential precision and bias. Results from nine LTPP distress rater-accreditation workshops conducted during the period of 1992 to 1996 were used as the source of data. Analyses of those data led to numerous observations and conclusions regarding the bias and precision of LTPP distress data. Because LTPP distress data are to be used in the development of pavement performance prediction models, it is believed that the level of variability found in this study should be reduced to increase its potential usage in the development of such models. A number of recommendations to improve the variability associated with manual distress surveys data are included.

Assessment of Long-Term Pavement Performance Plan Wall Projection-Based Distress Data Variability

1998 ◽  
Vol 1643 (1) ◽  
pp. 95-109 ◽  
Author(s):  
A. Raja Shekharan ◽  
Gonzalo R. Rada ◽  
Gary E. Elkins ◽  
William Y. Bellinger
Keyword(s):  
Reference Values ◽  
Statistical Tests ◽  
Ground Truth ◽  
Pavement Performance ◽  
Portland Cement Concrete ◽  
Data Set ◽  
Pavement Distress ◽  
Projection Screen ◽  
The Individual

In the Long-Term Pavement Performance (LTPP) program, 35-mm, black and white, continuous-strip photographs are used as a permanent record of pavement distress development for archival purposes and to quantify the distress severity and extent for pavement performance analysis. The traditional method of interpreting distress from LTPP film utilizes a relatively small image projected onto a digitizing tablet. From quality control checks performed on the interpreted data, it was found that some low severity types of distress, identified from larger magnified images projected onto a wall or projection screen, could not be seen in the smaller image used for distress interpretation. The variability in distresses interpreted directly off of the large format, wall-image projection was assessed through analysis of interpretations performed on six asphalt concrete and six portland cement concrete pavement sections used in the LTPP distress rater accreditation workshops. The data set included distress ratings from eight individuals, four two-person rater teams, and an experienced rater team. Also available were distress ratings performed in the field by the experienced rater team, which are used as reference values which represent the best estimate of ground-truth. Statistical tests show that the film-interpreted distresses from individual raters exhibit much larger variability than those from the rating teams. The most significant contributor to this finding is outlier observations in which one of the individual raters had significantly different ratings than the rest of the group. The spread in the rating teams was much lower. The film interpreted distresses from the experienced group correlated very well with the field-derived reference values.

scholarly journals Seychelles warblers with silver spoons: juvenile condition is a lifelong predictor of annual survival, but not annual reproduction or senescence

2021 ◽  
Author(s):  
Thomas Brown ◽  
Hannah Dugdale ◽  
Martijn Hammers ◽  
Jan Komdeur ◽  
David Richardson
Keyword(s):  
Condition Index ◽  
Wild Populations ◽  
Environmental Complexity ◽  
Annual Survival ◽  
The Individual ◽  
Developmental Conditions ◽  
Somatic Stress ◽  
Term Monitoring ◽  
Intrinsic Condition

1) The environment experienced during development, and its impact on intrinsic condition, can have lasting outcomes for adult phenotypes and could contribute to the individual variation in senescence trajectories. 2) However, the nature of this relationship in wild populations remains uncertain, owing to the difficulties in summarizing environmental complexity and long-term monitoring of individuals from free-roaming long-lived species. 3) In this study, we determine whether juvenile condition (derived from measures of body mass and size) is associated with senescence-related traits of a closely monitored population of Seychelles warblers (Acrocephalus sechellensis). 4) Juveniles with a higher condition index were more likely to survive to adulthood – suggesting these juveniles experienced better developmental conditions. Furthermore, these juveniles as adults were in better condition and had higher rates of annual survival, independently of age. In contrast, there was no association between juvenile condition and declines in adult telomere length (a measure of somatic stress) nor annual reproduction. 5) These results indicate that juvenile condition, while not associated with senescence trajectories, can influence the likelihood of surviving to old age due to silver-spoon effects. This study shows that measures of intrinsic condition in juveniles can provide important insights into long-term fitness of individuals in wild populations.

scholarly journals Comparing of Data Collection for Network Level Pavement Management of Urban Roads and Highways

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Hui Wang ◽  
Zhoucong Xu ◽  
Lei Yue
Keyword(s):  
Data Collection ◽  
Prediction Models ◽  
Condition Index ◽  
Current Data ◽  
Performance Model ◽  
Pavement Management ◽  
Pavement Performance ◽  
Pavement Condition ◽  
Monitoring Frequency ◽  
Maintenance Decisions

Pavement condition data are collected by agencies to support pavement management system (PMS) for decision-making purpose as well as to construct performance model. The cost of pavement data collection increases with the increase of survey frequencies. However, a lower monitoring frequency could lead to unreliable maintenance decisions. It is necessary to understand the influence of monitoring frequencies on maintenance decision by considering the reliability of performance prediction models. Because of different maintenance conditions of urban roads and highways, their performance show different trends. In this paper, the influence of pavement monitoring frequency on the pavement performance models was investigated. The results indicate that low collection frequencies may result in delay in maintenance action by overestimating pavement performance. The collection frequency for Pavement Condition Index (PCI) can be reduced without compromising the accuracy of performance model, more work should be done to ensure the PCI data quality, thus to guarantee the rationality of maintenance decisions. Effect of frequency reduction on pavement performance (IRI) models of urban roads seems greater than on pavement performance (IRI) models of highways, which may lead to heavier monitoring work for urban roads management. This paper provided an example which demonstrated how a comparative analysis can be performed to determine whether the current data collection plan can provide sufficient data for time series analysis.

Transverse Cracking Distress in Long-Term Pavement Performance Jointed Concrete Pavement Sections

1998 ◽  
Vol 1629 (1) ◽  
pp. 6-12 ◽  
Author(s):  
Eric D. Moody
Keyword(s):  
Prediction Models ◽  
Plain Concrete ◽  
Pavement Performance ◽  
Complete Analysis ◽  
Concrete Pavements ◽  
Joint Spacing ◽  
Transverse Cracking ◽  
Design Variables ◽  
Jointed Concrete Pavement

Transverse cracking is one of the more common distress manifestations in jointed concrete pavements. While the extent of transverse cracking is largely related to the specified joint spacing, there are several other primary design variables and distress mechanisms that can cause varying degrees of transverse cracking. These primary mechanisms and their associated variables are well-documented in the literature. However, all of these mechanisms often work on the pavement simultaneously over many years and, as a result, it has historically been difficult to calibrate prediction models with field data. The Strategic Highway Research Program’s Long-Term Pavement Performance (LTPP) program has collected a significant amount of condition survey data on more than 110 jointed plain concrete pavements (JPCP) and 65 jointed reinforced concrete pavements (JRCP) throughout North America over the last 7 years. The occurrence of transverse cracking in these sections is one of the principal distresses documented in the condition surveys and therefore provides an excellent data source for examining the relationships between the various primary distress mechanisms and the actual occurrence of distress in the field. Although it is premature to develop or calibrate purely “mechanistic” models based on the LTPP data, enough data have been collected to begin analyzing this distress and its association with the numerous prediction variables in the LTPP database. A complete analysis of the transverse cracking that has occurred in these LTPP test sections, along with their respective relationships with the primary prediction variables found in the primary distress mechanisms, is provided.

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