Marquette Interchange Phase I Final Report

This report provides details on the design, installation and monitoring of a pavement instrumentation system for the analysis of load-induced stresses and strains within a perpetual HMA pavement system. The HMA pavement was constructed as part of an urban highway improvement project in the City of Milwaukee, Wisconsin. The outer wheel path of the outside lane was instrumented with asphalt strain sensors, base and subgrade pressure sensors, subgrade moisture and temperature sensors, HMA layer temperature sensors, traffic wander strips and a weigh in motion system. Environmental sensors for air temperature, wind speed and solar radiation are also included. The system captures the pavement response from each axle loading and transmits the data through a wireless link to a resident database at Marquette University. The collected data will be used to estimate the fatigue life of the perpetual HMA pavement and to modify, as necessary, pavement design procedures used within the State of Wisconsin

Perpetual Pavement Instrumentation for the Marquette Interchange Project-Phase 1

This report provides details on the design, installation and monitoring of a pavement instrumentation system for the analysis of load-induced stresses and strains within a perpetual HMA pavement system. The HMA pavement was constructed as part of an urban highway improvement project in the City of Milwaukee, Wisconsin. The outer wheel path of the outside lane was instrumented with asphalt strain sensors, base and subgrade pressure sensors, subgrade moisture and temperature sensors, HMA layer temperature sensors, traffic wander strips and a weigh in motion system. Environmental sensors for air temperature, wind speed and solar radiation are also included. The system captures the pavement response from each axle loading and transmits the data through a wireless link to a resident database at Marquette University. The collected data will be used to estimate the fatigue life of the perpetual HMA pavement and to modify, as necessary, pavement design procedures used within the State of Wisconsin

Marquette Interchange Installation Report

Task three of the Perpetual Pavement Instrumentation Plan for the Marquette Interchange Project called for the installation of the various pavement sensors, data acquisition system, and various other components of the system outlined in the project proposal. The MU-TRC research team has successfully completed the installation of these various components of the system. This report fulfills the requirement of the installation report from task three in the project plan. This report is organized to describe in detail each specific component of the system. Most, but not all, of these details are written in the order they were completed. Not every activity described in this report is associated with the installation of a particular component but have been included because they are thought to have a significant impact on the methodologies and procedures used. This report is intended to describe the installation processes in as much detail as possible. To help accomplish this, many figures, pictures, data, and video were acquired / developed; many of which have obviously been filtered out and only the most pertinent included. All of this material will be compiled into a single archive and will be submitted to WHRP. This report was also written to explain and document any blunders, failures, and/or deviations from any proposed designs regarding this particular project or the Marquette Interchange project itself. These types of details are given so future research can learn from these experiences and make improvements upon them

Marquette Interchange Perpetual Pavement Instrumentation Project - Phase II

This report presents findings from the second phase of the Marquette Interchange instrumentation project and focuses on the maintenance of data recordation systems, development of computer programs to analyze data, and development of data packages for redistribution. The product of this research is a set of data which includes dynamic pavement response due to live traffic, vehicle information (weight, class, length, et cetera), and environmental data for the test site. The tasks within this project were not oriented for findings regarding pavement performance, but important and helpful conclusions can be drawn for similar future projects. The recordation systems have been maintained and recordation has been continuous. A handful of sensors did require attention and only a fraction of the critical strain sensors have ceased to function, making the project a success. The results of the computer programs written to analyze data show that reasonable accuracy has been achieved. Future work can help to generate more intricate programming making the processes more accurate

INDOT ITS: Past, Present, and Future

This presentation will begin with the origins and growth of ITS from a few dynamic message signs to the more than 500 permanent sites deployed today. We will then discuss, in more detail, the current state of ITS deployments in Indiana and how ITS fits into the project development process. This session will conclude with a discussion of future ITS deployments that are currently in the process of being designed or constructed

Structural health monitoring of asphalt pavements using smart sensor networks: A comprehensive review

Abstract Early, effective and continuous monitoring allows to reduce costs and to extend life of road infrastructure. For this reason, over the years, more and more efforts have been made to implement more advanced and effective monitoring systems at ever more contained costs, going from impractical manual and destructive methods through automated in vehicle equipment to the most recent wireless sensor network (WSN) embedded into the pavement. The purpose of this paper is to provide a comprehensive, up-to-date critical literature review of wireless sensor networks for pavement health monitoring, considering, also, the experience gained for wired sensor as fundamental point of reference. This work presents both the methodology used to collect and analyse the current bibliography and provides a description and comments fundamental characteristics of wireless sensor networks for pavement monitoring for damage detection purposes, among which energy supply, the detection method, the hardware and network architecture and the performance validation procedures. A brief analysis of other possible complementary applications of smart sensor networks, such as traffic and surface condition monitoring, is provided. Finally, a comment is provided on the gaps and possible directions that future research could follow to allow the extensive use of wireless sensor networks for pavement health condition monitoring

A Weigh-in-Motion Characterization Algorithm for Smart Pavements Based on Conductive Cementitious Materials

Smart materials are promising technologies for reducing the instrumentation cost required to continuously monitor road infrastructures, by transforming roadways into multifunctional elements capable of self-sensing. This study investigates a novel algorithm empowering smart pavements with weigh-in-motion (WIM) characterization capabilities. The application domain of interest is a cementitious-based smart pavement installed on a bridge over separate sections. Each section transduces axial strain provoked by the passage of a vehicle into a measurable change in electrical resistance arising from the piezoresistive effect of the smart material. The WIM characterization algorithm is as follows. First, basis signals from axles are generated from a finite element model of the structure equipped with the smart pavement and subjected to given vehicle loads. Second, the measured signal is matched by finding the number and weights of appropriate basis signals that would minimize the error between the numerical and measured signals, yielding information on the vehicle’s number of axles and weight per axle, therefore enabling vehicle classification capabilities. Third, the temporal correlation of the measured signals are compared across smart pavement sections to determine the vehicle weight. The proposed algorithm is validated numerically using three types of trucks defined by the Eurocodes. Results demonstrate the capability of the algorithm at conducting WIM characterization, even when two different trucks are driving in different directions across the same pavement sections. Then, a noise study is conducted, and the results conclude that a given smart pavement section operating with less than 5% noise on measurements could yield good WIM characterization results