Traffic Speed Deflectometer Devices (TSDD)s Are They A Blessing Or A Curse?

Abstract: The use of Traffic Speed Deflectometer Devices (TSDDs) for pavement evaluation has introduced a transformative approach to network-level pavement structural assessment – yet they present several challenges spanning from data measurement to data analysis. Unlike conventional Falling Weight Deflectometer (FWD) technology that applies static impact loading at discrete points, TSDD technology operates at rolling speeds (e.g., 11mph– 60mph), continuously measuring pavement response under a moving load. While this capability greatly enhances operational efficiency and operator safety in network-level evaluation projects by eliminating the need for lane closures, it also introduces complex challenges related to data accuracy, signal processing, sensor calibration, and data interpretation. In recent years, several TSDD technologies have been developed relying on imagery, lasers, and geophone technologies to measure the deflection basin of a pavement under load. While each of these technologies offers advantages, they each possess their own challenges as well. In the United States, currently implemented TSDDs leverage Doppler laser sensors to record surface velocity slopes in the wheel path of the moving load. However, environmental conditions (e.g., temperature) can significantly influence laser readings and the stability of velocity slope signals. Variations in vehicle dynamics, (e.g., suspension behavior, tire pressure, and load distribution) further complicate the repeatability and reliability of Doppler measurements. These factors necessitate frequent calibration and the use of inertial sensors, gyroscopes, and accelerometers to correct for vehicle motion and external vibrations, adding layers of complexity to the raw data acquisition process.

Another major challenge lies in the interpretation of the measured deflection velocity slope data into meaningful deflection profiles comparable to those obtained from traditional methods. The transformation involves numerical integration and filtering processes that are highly sensitive to noise and signal drift. Moreover, as TSDDs do not measure absolute deflection directly, data comparison with legacy FWD datasets, traditionally used for back-calculating layer moduli and predicting pavement performance, becomes increasingly difficult.
Data management presents another set of challenges. The TSDDs collect vast amounts of high-resolution data at short spatial intervals. The processing, cleaning, and storing of this data requires robust computational infrastructure and automated quality control procedures to identify anomalies. Furthermore, analytical models for accurately interpreting TSDD data are still evolving. While research has explored methods to estimate pavement stiffness, remaining life, or structural capacity from continuous deflection measurements, there is no universally accepted framework for converting TSDD results into engineering decision parameters. This lack of standardized analysis procedures inherently limits the widespread adoption of TSDD technologies by transportation agencies.
This presentation will go over all these challenges regarding TSDD technology and objectively state both the pros and cons of each technology in comparison to the standard FWD testing procedure. Potential solutions to these problems will be discussed.