Jerome Daleiden

Effectiveness of Maintenance Treatments of Flexible Pavements

To achieve effective pavement maintenance, the life expectancy and timing of treatment applications need to be determined. The Long Term Pavement Performance (LTPP) program includes the Specific Pavement Study-3 (SPS-3), which focuses on this subject. The treatments applied are chip seals, crack seals, slurry seals, and thin overlays. In studying the life expectancy it is not feasible to wait for all the sections in the experiment to fail. Thus, there is a need to determine the life expectancy while making efficient use of the available data collection funds. Survival data analysis is a statistical technique that meets this need by accounting for the portion of the sections in which the exact time the treatment lasted is not known. The application of this technique to flexible-pavement maintenance is presented. In addition, some results of the LTPP SPS-3 experiment are presented to the highway community. The focus is on the LTPP Southern Region. The results showed that the probability of failure was two to four times higher for the sections that were in poor condition at the time the treatment was applied than those sections that were in better condition. The median survival times for thin overlays, slurry seals, and crack seals were 7, 5.5, and 5 years, respectively. The chip-seal sections had not yet reached the 50 percent failure probability after 8 years of the SPS-3 experiment. Accordingly, chip seals appear to have outperformed the other treatments investigated in this study in delaying the reappearance of distress.

OFF-THE-WALL PAVEMENT DISTRESS VARIABILITY STUDY

Variability of pavement surface distress data collection has always been an area of significant concern. When conducting evaluations of distress data manually (with raters observing pavements in question, interpreting what they see, and recording on paper) the process is subject to human errors. To minimize the impact of such human errors on these important pavement performance data, sophisticated equipment has been developed to eliminate as much of the human intervention as possible. Such technology is not without its own limitations of precision and bias. With both methodologies being used for the collection of surface distress data for the long-term pavement performance (LTPP) program, questions regarding precision and bias have been identified. In attempting to define the variability of the data for incorporation in stochastic analyses, it has become apparent how diverse and complex these distress data truly are. To adequately quantify the precision and bias, a detailed experiment was designed to evaluate the errors inherent in the different distress data collection methodologies. The facet of the experiment reported targets the variability of human distress surveyors and the biases associated with conducting surveys from film, using a slightly different projection system. Specifically, a collection of surveyors was assembled to establish the variability associated with experienced raters versus novice raters, engineers versus engineering technicians, and teams versus individuals.

Subsurface Drainage Systems in Roadway Construction

The installation of subsurface drainage systems has been a common practice in roadway construction for many years. Until recently, however, the ability to inspect and report on the condition of these systems once they are in place has been limited. The use of a high-tech, closed-circuit video monitoring system for the inspection of subsurface drainage systems has been developed and utilized with a high degree of success. The use of this system is beneficial for maintenance and rehabilitation of existing systems and as a quality control measure for new highway systems. In an ongoing project for FHWA, video monitoring has identified crushed mainline drainage pipes in new systems that have yet to be open to traffic. All of the components of this monitoring system can be easily operated by one person in the field. Substantial cost savings can be realized by accurately identifying the specific areas that need repair rather than assuming that an entire system needs to be replaced in highway rehabilitation projects. Results from use of this new technology to date are presented here.

Error sensitivity of the connected vehicle approach to pavement performance evaluations

Abstract The international roughness index (IRI) is the prevalent indicator used to assess and forecast road maintenance needs. The fixed parameters of its simulation model provide the advantage of requiring relatively few traversals to produce a consistent index. However, the static parameters also cause the model to under-represent roughness that riders experience from profile wavelengths outside of the model’s response range. A connected vehicle method that uses a similar but different index to characterise roughness can do so by accounting for all vibration wavelengths that the actual vehicles experience. This study characterises and compares the precision of each method. The field studies indicate that within seven traversals, the connected vehicle approach could achieve the same level of precision as the procedure used to produce the IRI. For a given vehicle and segment lengths longer than 50 m, the margin-of-error diminished below 1.5% after 50 traversals, and continued to improve further as the traversal volume grew. Practitioners developing new tools to evaluate pavement performance will benefit from this study by understanding the precision trade-off to recommend the best practices in utilising the connected vehicle method.

Wavelength sensitivity of roughness measurements using connected vehicles

ABSTRACT Researchers previously demonstrated that a roughness index called the road impact factor (RIF) is directly proportional to the international roughness index (IRI) when measured under identical conditions. A RIF-transform converts inertial signals from connected vehicle accelerometers and speed sensors to produce RIF-indices in real time. This research examines the relative sensitivities of the RIF and the IRI to variations in dominant profile wavelengths. The findings are that both indices characterise roughness from spatial wavelengths up to 2 m with equal sensitivity. However, the RIF-transform maintains its sensitivity when characterising roughness from wavelengths beyond that. The case studies used a certified inertial profiler to collect both RIF and IRI data simultaneously from five different pavement surface types. The RIF/IRI proportionality factors distributed normally among the profiles tested. This result affirms that the RIF and IRI generally agrees. However, differences in the dominant profile wavelength among pavements will produce some spread in the degree of roughness that the indices express.

Use of Connected Vehicles to Characterize Ride Quality

The United States relies on the performance of more than 4 million miles of roadways to sustain its economic growth and to support the dynamic mobility needs of its growing population. The funding gap to build and maintain roadways is ever widening. Hence the continuous deterioration of roads from weathering and usage poses significant challenges. Transportation agencies measure ride quality as the primary indicator of roadway performance. The international roughness index is the prevalent measure of ride quality that agencies use to assess and forecast maintenance needs. Most jurisdictions use a laser-based inertial profiler to produce the index. However, technical, practical, and budget constraints preclude that use for some facility types, particularly local and unpaved roads that make up more than 90% of the road network in the United States. This study expands on previous work that developed a method to transform sensor data from many connected vehicles to characterize ride quality continuously, for all facility types and at any speed. The case studies used a certified and calibrated inertial profiler to produce the international roughness index. A smartphone aboard the inertial profiler produced simultaneously the roughness index of the connected vehicle method. The results validate the direct proportionality relationship between the inertial profiler and connected vehicle methods within a margin of error that diminished below 5% and 2% after 30 and 80 traversal samples, respectively.

Evaluation Framework for Automated Pavement Distress Identification and Quantification Applications

Tracking types and extent of pavement deterioration is critical for maintaining road networks in a serviceable condition. The prevailing methods for obtaining pavement condition data include manual and semiautomated surveys, which are time-consuming and involve significant human intervention. Extensive research has been performed in automating the process for more efficient, objective, and repeatable distress evaluations. This paper highlights the preliminary results from an effort sponsored by the Florida Department of Transportation to develop and implement automated software for identification and quantification of pavement surface cracking distresses. A technical framework was developed for systematic evaluation of available automated technologies in contrast to manual methods. Pertinent performance measures were identified to evaluate the accuracy, precision, repeatability, reproducibility, and efficiency of various methods. This framework was implemented to determine the gaps in effectiveness of automated applications, to design corresponding solutions, and to gauge reliability expectations accordingly. The evaluation follows two main steps: (a) comparison of the cumulative quantities of various distress types found in manual surveys versus automated surveys and (b) verification of the automatically detected distresses against reference crack maps generated through a semiautomated process of manually rating the collected images. Although the overall comparison of distress quantities indicates strengths and weaknesses of the evaluated algorithm, the distress by distress verification of software performance is used to identify design solutions for addressing the indicated weaknesses. The guidelines in this systematic framework can be modified with context-sensitive considerations to be applicable to other highway agencies transitioning to automated applications.

Performance Trends on Interstate Highway Sections of the Long-Term Pavement Performance Program

The Moving Ahead for Progress in the 21st Century Act required FHWA to identify pertinent performance measures and to establish minimum acceptable levels for infrastructure condition. Because of differences in data collection and analysis between state highway agencies (SHAs), a comparison of the performance data from states is not viable. The Long-Term Pavement Performance (LTPP) sections are spread across various states but have been monitored following the same standards. With the use of LTPP data, analyses were conducted to gain insight into actual deterioration rates and the impact of maintenance and rehabilitation activities on the performance of Interstate highway pavements. An evaluation of the decline in longitudinal and transverse profiles showed that about 90% of pavement sections had experienced nominal changes from year to year. The reason for these changes could be that SHAs had been actively applying preservation strategies. The average annual rate of roughness progression increases when the surface ages. The highest annual rate of increase in the international roughness index (IRI) occurs when the surface is between 8 and 12 years old for flexible pavements and between 16 and 20 years old for rigid pavements. The percentages of significant annual changes (more than 20%) were approximately the same between increasing and decreasing IRI rates. These figures could mean that SHAs had been addressing roughness with proper treatments at the same rate as roughness had been progressing. In agreement with previous research findings, the current work found that milling before overlay increased the average IRI reduction but did not improve the effectiveness of overlays in reducing rutting.