Traffic Speed Deflectometer Data Research Articles

Enhancing pavement performance prediction with traffic speed deflection data

ABSTRACT Pavement performance modelling is an essential part of pavement management. Past research has shown that a structural indicator can be included in pavement performance models to capture differences in performance between weak and strong pavements. Weak pavements are expected to deteriorate more rapidly than strong pavements, as consistently shown in past research. The work presented in this paper uses the Traffic Speed Deflectometer (TSD) to calculate multiple structural indexes and compares their ability to differentiate between poor and well performing pavements. Historical condition data from the US National Parks pavement network is used in this assessment. Two approaches for calculating the subgrade resilient modulus and two approaches for calculating the effective structural number from the TSD results are compared. The temperature corrected centre deflection, surface curvature index and ratio of effective to required structural number are all calculated from the TSD data. Performance models are developed for two condition indexes and the International Roughness Index (IRI). In all cases, the addition of the structural indexes improved the quality of predictions, and the IRI prediction showed the most improvement from including the indexes. Ultimately, it was shown that the TSD testing results can be used to inform the pavement management process.

Use of Traffic Speed Deflectometer Data in Project-Level Pavement Rehabilitation Design

Current traffic speed deflectometer (TSD) analyses have focused on the application of pavement structural-condition data at the network level. Pavement management systems use the deflection data to adjust the treatment as determined from the surface deflections and ride quality, resulting in better treatment selection. However, TSD data can also be used at the project level to inform pavement design decisions, though this has yet to be well documented in the U.S. A pilot study was conducted in 2021 to develop a methodology to analyze the TSD data for the South Carolina Department of Transportation (SCDOT) based on the AASHTO 1993 overlay design methodology. The TSD analysis methodology determines the effective structural number for each TSD datapoint. The results generated from this analysis were used for an ongoing construction project to assess the structural condition of the pavement within the project limits. Grade restrictions on the project presented a challenge in determining limits of pavement reconstruction and pavement overlay. The results of the TSD analysis were used to characterize the effective structural number at a 52 ft interval, allowing for optimization of the limits of pavement reconstruction. This paper presents the TSD analysis methodology used and how SCDOT incorporated the TSD results at the project level to perform rehabilitation designs of an ongoing construction project.

Traffic Speed Deflectometer for Network-Level Pavement Management in Tennessee

The traffic speed deflectometer (TSD) overcomes the limitations of the falling weight deflectometer (FWD) with respect to traffic interruption and test inefficiency and is considered the preferred method for network-level pavement structural evaluation. However, some challenges exist when applying the TSD to routine survey work. This study evaluated the long-term repeatability of TSDs and compared TSD measurements with FWD measurements to examine device-related errors in TSD measurements. In addition, a framework for incorporating TSD measurements into the pavement management system (PMS) was developed by introducing deflection bowl parameters (DBPs). All data analyses were based on TSD data collected in Tennessee. From the current study, the repeatability of the TSD has not been fully validated because of device-related errors. Since TSD measurements and FWD measurements are broadly similar, periodic validation of TSDs by FWDs is recommended for quality control. TSDs provide valuable information about pavement structural conditions that are not reliably or adequately reflected in the current PMS (which focuses mainly on pavement functional conditions). DBPs are a simple and fast method for making initial estimates of pavement structural conditions without the need for layer thickness. In the proposed DBP system, the surface curvature index (SCI_12) and D60 (TSD deflection at 60 in. before the load center) represent the structural strength of the asphalt layer and subgrade, respectively. The combination of pavement functional conditions and TSD-measured structural conditions (PMS+DBPs) may help to make more accurate predictions of pavement performance and to make more appropriate decisions on maintenance and rehabilitation strategies.

Relationship between Fatigue Condition of Asphalt Pavements and Deflection Lag from Traffic Speed Deflectometer

The phase angle is a good indicator of the current fatigue condition of asphalt concrete (AC) layers, but estimating phase angles from drilled core samples is destructive, expensive, and unsuitable for large-scale applications. Similar to the phase angle, a lag between load and response has recently been observed in the deflection basin of the nondestructive traffic speed deflectometer (TSD), i.e., the lag between the loading point and the maximum deflection point, and the deflection lag may be closely related to the phase angle. This study investigated the potential of TSD deflection lag as a nondestructive indicator of pavement fatigue conditions. The relationship between AC phase angle and TSD deflection lag was investigated using the 3D-Move program, and the effects of pavement structure, TSD speed, and test temperature on the deflection lag were also investigated. Field TSD data collected in Tennessee were used to verify the relationship between deflection lag and fatigue cracking. The results show that the lag distance increases uniformly with increasing fatigue levels (phase angles) until fatigue failure occurs. However, the lag distance is also closely related to the asphalt thickness and subgrade modulus; therefore, only the lag distance of pavements with the same structures can be compared to identify the fatigue sections. Overall, the lag distance can be used as an implicit indicator of the fatigue condition of the pavement to predict the initiation and growth of fatigue cracks. Fatigue cracking is expected to occur where the lag distance is relatively large.

Estimating Load Transfer Efficiency for Jointed Pavements from TSD Deflection Velocity Measurements

Transverse joints are the weakest element of jointed pavements, and when these joints lack structural capacity, the onset of load-related distress is imminent. The most widespread measurement of the joints’ structural performance is the Load Transfer Efficiency Index (LTE), a ratio of the deflection of the two adjoining slabs. LTE can easily be assessed with a falling weight deflectometer, but this test procedure is not advisable for evaluation at the network level because of user safety concerns and because it can be excessively time-consuming. Traffic speed deflection devices like the traffic speed deflectometer (TSD) are suitable devices for network-level pavement structural evaluation. Yet, as of today, no interpretation technique to get structural health metrics for jointed pavements from TSD data has been published. In this paper, a backcalculation scheme based on slab theory is proposed to estimate the joints’ LTE from TSD deflection velocity measurements. The backcalculation problem formulation and its numerical solution using fast procedures are described in detail. The approach is tested with TSD data collected on the MnROAD test track. Overall, it was found that the backcalculation converges to reasonable estimates of the pavement structural properties and can furnish LTE estimates for most transverse joints from 5 cm-resolution TSD data, all at a reasonable computational cost. This allows for corridor-wide LTE assessment of a pavement’s joints using TSD measurements.

Mechanistic Assessment of Flexible Pavements in Wisconsin Using Traffic Speed Deflectometer

The traffic speed deflectometer (TSD) has been gaining interest for pavement management practices, as it can continuously collect deflection data at traffic speed without requiring traffic control. TSD data have been typically used to provide an estimate of the structural condition of pavements with a limited range of significant parameters considered in the analysis. To date, limited studies have been conducted in or for cold regions to consider the potential use of TSD data for pavement structural assessment. This study aimed to bridge this gap by developing a twofold approach to: (1) mechanistically characterize the structural integrity and remaining life of pavements; and (2) compare TSD and falling weight deflectometer (FWD) data collected in the field, considering the features of pavement facilities in Wisconsin. A field testing plan was developed to characterize the site-specific features of eight representative pavement sections, with a total length of about 30 mi and distinct pavement structures, truck traffic patterns, and climatic conditions. The postprocessed results underscored the significance of the TSD data and their potential for the structural evaluation of underlying layers in a multilayered pavement system when integrated with the site-specific pavement profile and truck traffic information derived from field testing. A comparison of the normalized deflections and structural parameters characterized by TSD and FWD data showed similar trends, while the average FWD-based deflections were 12%–37% higher than the TSD-based deflections.

Development of structural deterioration models for flexible pavement using traffic speed deflectometer data

ABSTRACT A road's performance is influenced by several factors. Owing to the limited availability of structural data, road agencies are forced to use rutting and fatigue cracking data as a substitute for structural bearing capacity to identify rehabilitation treatment options. However, this approach fails to assist in the development of investment strategies to reduce the life-cycle cost of the road asset nor will it maximise the safety of vulnerable road users. The introduction of traffic speed deflectometer (TSD) has made it more affordable for many road agencies to collect deflection data. The use of TSD has created a knowledge gap on methodology/mechanism as road agencies are yet to identify the best means of utilising and incorporating these structural data at network-level analysis. The structural deterioration model is a critical input in the pavement management system for predicting pavement rehabilitation needs. A practically implementable concept was adopted in this study to develop the models. These deterioration models were developed by utilising five years' time series TSD deflection data as a function of other readily available data. This study successfully established structural deterioration models that will enable road agencies to incorporate available TSD data in the pavement management system for developing investment strategies.

Mechanistic-Based Approach to Utilize Traffic Speed Deflectometer Measurements in Backcalculation Analysis

Backcalculation analysis of pavement layer moduli is typically conducted based on falling weight deflectometer (FWD) deflection measurements; however, the stationary nature of the FWD requires lane closure and traffic control. In recent years, traffic speed deflection devices such as the traffic speed deflectometer (TSD), which can continuously measure pavement surface deflections at traffic speed, have been introduced. In this study, a mechanistic-based approach was developed to convert TSD deflection measurements into the equivalent FWD deflections. The proposed approach uses 3D-Move software to calculate the theoretical deflection bowls corresponding to FWD and TSD loading configurations. Since 3D-Move requires the definition of the constitutive behaviors of the pavement layers, cores were extracted from 13 sections in Louisiana and were tested in the laboratory to estimate the dynamic complex modulus of asphalt concrete. The 3D-Move generated deflection bowls were validated with field TSD and FWD data with acceptable accuracy. A parametric study was then conducted using the validated 3D-Move model; the parametric study consisted of simulating pavement designs with varying thicknesses and material properties and their corresponding FWD and TSD surface deflections were calculated. The results obtained from the parametric study were then incorporated into a Windows-based software application, which uses artificial neural network as the regression algorithm to convert TSD deflections to their corresponding FWD deflections. This conversion would allow backcalculation of layer moduli using TSD-measured deflections, as equivalent FWD deflections can be used with readily available tools to backcalculate the layer moduli.

Visco-Elastic Back-Calculation of Traffic Speed Deflectometer Measurements

The traffic speed deflectometer (TSD) has proven a valuable tool for network level structural evaluation. At the project level, however, the use of TSD data is still quite limited. An obstacle to the use of TSD at the project level is that the standard approaches to back-calculation of pavement properties are based on the falling weight deflectometer (FWD). The FWD experiment is similar, but not equivalent, to the TSD experiment, and therefore it is not straightforward to apply the traditional FWD back-calculation procedures to TSD data. In this paper, a TSD-specific back-calculation procedure is presented. The procedure is based on a layered linear visco-elastic pavement model and takes the driving speed of the vehicle into account. This is in contrast to most existing back-calculation procedures, which treat the problem as static and the pavement as purely elastic. The developed back-calculation procedure is tested on both simulated and real TSD data. The real TSD measurements exhibit significant effects of damping and visco-elasticity. The back-calculation algorithm is able to capture these effects and yields model fits in excellent agreement with the measured values.

Pavement Structural Capacity from Traffic Speed Deflectometer for Network Level Pavement Management System Application

Structural number (SN) represents the structural capacity of a flexible pavement system to sustain anticipated traffic and is among the structural indices most commonly used by pavement design engineers in the U.S. Effective structural number (SNeff) is an indicator of structural capacity of in-service pavement sections and is conventionally estimated from nondestructive testing (NDT) device data such as falling weight deflectometers (FWDs) using methods such as suggested by AASHTO. In addition to pavement design, structural condition is a critical input for the selection of maintenance and rehabilitation strategies in pavement management system (PMS) application. However, use of SN in network level application has not been practical because of limitations of FWD such as stop-and-go operation, lane closures, and low testing frequency. The traffic speed deflectometer (TSD), a continuous deflection device, has recently been gaining worldwide application as a reliable NDT device for network level PMS applications. The objective of this study is to develop a practical approach to compute and utilize SN of in-service flexible pavements from TSD data for network level PMS applications. The study is based on the fundamental that, for the same pavement, SNeff from the TSD using the proposed method should be in good agreement with SNeff from the FWD using AASHTO method. The developed method was field validated with TSD and FWD data collected at in-service pavement sections. In addition, the use of structural number ratio, defined as a ratio of SNeff to required SN, in network level prioritization of structural capacity improvements was illustrated.

Temperature adjustment of Surface Curvature Index from Traffic Speed Deflectometer measurements

ABSTRACT Pavement structural condition evaluation plays an important role in assessing rehabilitation needs and making prudent investment decisions. Recently the use of Traffic Speed Deflectometer (TSD), is being considered for pavement structural evaluation especially for network level pavement management applications. Among various TSD data measurements and indices, Surface Curvature Index (SCITSD), is a widely-used index for assessing the structural condition of the AC layers. Since asphalt modulus is temperature sensitive, measured deflections and consequently the computed SCITSD are also affected by pavement temperature at the time of testing. For consistent pavement evaluation, SCITSD computed across sections and over time should be adjusted to a reference temperature. This study presents an applied method for adjusting SCITSD to a reference temperature. The method was based on a model developed from a dataset built from responses computed with dynamic-viscoelastic analyses under TSD moving load in a wide range of pavement properties. The method was field evaluated with TSD data from three locations within the US and one location each in Europe and Australia. The results showed that the proposed method can reasonably adjust SCITSD to a reference temperature which enables its application in pavement structural assessment and subsequent use in pavement management activities.

Concept Paper: Developing Pavement Structural Deterioration Curves

An SN (structural number) can be calculated for a road pavement from the properties and thicknesses of the surface, basecourse, sub-base and subgrade. Historically, the cost of collecting structural data has been very high. Data were initially collected using Benkelman Beams and now by FWD (falling weight deflectometer). The structural strength of pavements weakens over time due to environmental and traffic loading factors but due to a lack of data, no structural deterioration curve for pavements has been implemented in a PMS (pavement management system). IRI (international roughness index) is a measure of the road longitudinal profile and has been used as a proxy for a pavement’s structural integrity. This paper offers two conceptual methods to develop PSDC (pavement structural deterioration curves). Firstly, structural data are grouped in sets by design ESA (equivalent standard axles). An ISN (initial SN), SNI (intermediate SN) and a TSN (terminal SN), are used to develop the curves. Using FWD data, the ISN is the SN after the pavement is rehabilitated (Financial Accounting Modern Equivalent). Intermediate SNIs, are SNs other than the ISN and TSN. The TSN was defined as the SN of the pavement when it was approved for pavement rehabilitation. The second method is to use TSD (traffic speed deflectometer) data. The road network already divided into road blocks, is grouped by traffic loading. For each traffic loading group, road blocks that have had a recent pavement rehabilitation, are used to calculate the ISN and those planned for pavement rehabilitation to calculate the TSN. The remaining SNs are used to complete the age-based or if available, historical traffic loading-based SNIs.

Application of Traffic Speed Deflectometer for Network-Level Pavement Management

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.

Computation of Pavement Vertical Surface Deflections from Traffic Speed Deflectometer Data: Evaluation of Current Methods

AbstractVertical surface deflections and deflection indices are common parameters used by pavement engineers to the evaluate structural condition of a pavement. At the network level, traffic speed ...

Backcalculation of Flexible Pavement Layer Moduli from Traffic Speed Deflectometer Data

In the past few years, state transportation departments in the United States have been investigating the potential use of the traffic speed deflectometer (TSD) in routine network-level pavement structural evaluation, including efforts to compute parameters typically obtained with the falling weight deflectometer (FWD). However, differences in loading configuration (single plate versus dual tires) and mechanism (impact versus moving load) between the FWD and the TSD necessitate modification of conventional analysis methodologies for use with TSD data. The TSD is a trailer truck that uses Doppler lasers to measure the pavement deflection velocities at normal traffic speed. Deflection velocities are then converted to surface deflections with a computational algorithm. This study proposes two approaches to backcalculating layer moduli from the TSD data. The first method uses 3D-Move software and deflection velocities measured directly by the TSD. The 3D-Move software can closely simulate TSD loading by considering moving load, nonuniform contact pressure of the dual tires, and viscoelastic material properties of asphalt layers. The second method uses TSD-computed surface deflections in a linear elastic analysis backcalculation program modified to incorporate a dual-tire configuration. The two methods were evaluated with field data from the MnROAD test facility and two in-service pavement sections in Pennsylvania and Idaho. The results show that the second method can be reliably used in network-level applications until the first method becomes computationally practical. The limitations of use of the TSD deflection measurement in the conventional FWD backcalculation program was also demonstrated.

Integration of Traffic Speed Deflectometer and Ground-Penetrating Radar for Network-Level Roadway Structure Evaluation

The project has focused on the East Idaho Loop Corridor (EILC), representing 518 mi of primary roadways covering a wide range of geographic conditions. The Idaho Transportation Department (TD) has pursued this effort to support future project planning and design efforts and advance the management of its assets into a more efficient, best-first set of priorities. The EILC was surveyed with a traffic speed deflectometer (TSD) and with ground-penetrating radar (GPR). After preliminary review of the TSD data, segments were selected for falling weight deflectometer (FWD) testing to confirm patterns observed in the TSD data and to adapt FWD analysis methods to the TSD data. Ninety-nine borings were taken to confirm the pavement layer structure and verify thickness calculations. The Idaho TD data were analyzed at a 10-m interval with the GPR layer thickness data to determine subgrade modulus, pavement modulus, and structural number. These values were then used to estimate overlay requirements and, given traffic projections, to calculate the remaining life as a continuous function of roadway position. The data were incorporated into a spatial geodatabase that provides the Idaho TD with a convenient means to visualize and evaluate the overall condition of the network down to the detail of its individual segments. The segments were subdivided into homogenous subsections on the basis of remaining life, and these subsegments were used for identifying and programming rehabilitation projects. The level of condition detail available at the subsegment level allows for pavement design and for scoping restoration projects.

Evaluation of the Traffic Speed Deflectometer Data Using Simplified Deflection Model

Falling Weight Deflectometer (FWD) has been used by many road agencies worldwide for structural evaluation of both flexible and concrete pavements since the 1980s. With the development of Traffic Speed Deflectometer (TSD), the laser-based deflectograph is increasing used to perform continuous bearing capacity measurement at a range of driving speeds. The two main advantages of the TSD technology are; its ability to carry out continuous deflection measurements rather than at discrete points and the tests can be carried out at traffic speed without the need for lane closure in the case a stationary device such as the FWD. The objective of this paper is to study the deflection basins generated by TSD on flexible pavements using Simplified Deflection Model (SDM). The study shows that TSD data can be modelled accurately using SDM that can be represented in a mathematical form of Y = K1exp (-r/K2). K1 is equal to deflection at D0 in micron and K2 is the structural parameter at the respective sensor location r. It is observed that the majority of the pavement sections possess nonlinear subgrade behaviour in the TSD deflection data. The dynamic effects generated by the TSD axle load are likely to be the reason for the pavements to exhibit subgrade nonlinearity. A comparison between the FWD and TSD data shows a high level of correlation and a mathematical model has been established for estimation of FWD deflections using the TSD data. The study also shows that he theoretical deflections generated by the SDM are in good agreement with the actual deflection data obtained from FWD test. Statistical analysis confirms that the SDM generated D0 deflections are not significantly different from the D0 deflections recorded by FWD device.

Alternative Approach for Interpreting Traffic Speed Deflectometer Results

This paper presents an alternative approach for interpreting data collected with the traffic speed deflectometer (TSD). Although the idea of measuring pavement deflections at traffic speeds in a continuous manner is not new, worldwide interest is recent, in part because of the availability of a commercial TSD device. As with any new device, there is a need for robust, scientifically sound, yet practical interpretation procedures. This paper describes the details of such a procedure recently developed at the Road and Bridge Research Institute in Poland. In addition to a detailed description of the proposed algorithm and its unique features, this study demonstrates an example application that uses data collected by the TSD operated by the Road and Bridge Research Institute. The proposed approach can be successfully applied to the TSD data and allows for deep customization for a user's and customer's needs and applications.

Revised approach to assessing traffic speed deflectometer data and field validation of deflection bowl predictions

This study presents a revised approach to conceptualising and analysing data from the traffic speed deflectometer (TSD) which enables full deflection bowl predictions. The approach was successfully applied to TSD surface velocity measurements collected at seven test sites as part of recent Australian trials. More than 1500 deflection bowls produced from the TSD data were validated against approximately 600 40- and 50-kN falling weight deflectometer (FWD) deflection bowl profiles. Overall, the results showed a clear correlation between the shape and magnitude of deflection bowls predicted by both methods. Estimates of maximum deflection (d 0) and structural curvature index (SCI300) from both methods were also compared, showing a strong correlation. The results suggest that the TSD device has significant potential to be used to collect measurements of pavement deflection bowls at highway speeds which are comparable with FWD deflection bowl measurements.