Chenxi Yuan

Enhanced Boundary Condition–Based Approach for Construction Location Sensing Using RFID and RTK GPS

AbstractThe radio frequency identification (RFID) technology has proven its potential in locating and tracking construction resources, a critical task in construction project control. However, the main challenge is how to achieve desired levels of locating accuracy. This paper presents an enhanced boundary condition method that incorporates the tag-reader angle and the reader geometric configuration factors to control the accuracy of a locating system that integrates RFID and real time kinematic (RTK) global positioning system (GPS). Controlled laboratory experiments were conducted to assess their effects and create quality control filters. This study demonstrated the relationship between the detecting range and the tag-reader angle and used it to separate valid/invalid boundary points. Spatial dilution of precision (SDOP) was formulated to measure the geometric configuration of readers forming the boundary constraint. Correlating SDOP to the locating error through a polynomial regression model, a mechani...

Integrated Processing of Image and GPR Data for Automated Pothole Detection

AbstractA pothole is a severe pavement distress that can compromise pavement rideability and safety and can be the cause of expensive damage claims. The detection and evaluation of potholes are predominantly manual and time-consuming. Although sensing technologies such as global positioning systems (GPS), stereovision systems, and ground penetrating radar (GPR) now can be combined to collect pavement condition data for assessment, the raw data returned by these sensors are often processed individually and separately. This isolated approach to data processing hinders the potential efficiency and effectiveness of multisensor systems. This paper proposes a method to integrate the processing of two-dimensional images and GPR data to automate accurate and efficient pothole detection. First, the images and GPR scans are preprocessed to filter out noise and enhance the essential clues related to potholes. Second, a novel pothole detector was designed by investigating the patterns of GPR signals reflected by poth...

Life-Cycle Approach to Collecting, Managing, and Sharing Transportation Infrastructure Asset Data

AbstractTransportation asset management (TAM) demands a data-driven decision-making process to proactively maintain, preserve, and extend the long-term service life of transportation assets. State ...

Vision-Based Excavator Detection and Tracking Using Hybrid Kinematic Shapes and Key Nodes

AbstractEnhancing workplace safety continues to be a major task in the construction industry. Approximately 75% of struck-by fatalities are caused by inappropriate spatial-temporal relationships between construction workers and heavy equipment. Construction safety can be improved if the location and movement of heavy equipment are tracked in real time. However, detecting and tracking heavy equipment with kinematic joints and changing poses, such as excavators, is still a challenge for vision-based sensing methods. This study proposes to detect and track excavators using stereo cameras based on hybrid kinematic shape and key node features. Specifically, templates of excavator components are synthesized for detection following kinematic constraints of each component. Thereafter, a fast directional chamfer matching algorithm is used to detect the excavator components, and the detected components are articulated at the key nodes. Finally, the three-dimensional positions of the key nodes are tracked through tr...

Survey on the Practice Hurdles in Collecting, Managing, and Sharing Transportation Infrastructure Asset Data

Transportation infrastructure asset management is a data-driven process. Great efforts have been made by state highway agencies (SHAs) in asset management in recent years. To investigate the challenges that SHAs are still facing in current practice, a web-based survey was distributed across different functional divisions of SHAs through American Association of State and Highway Transportation Officials (AASHTO’s) Standing Committee on Highways. SHAs responded to questions about their current practice in transportation infrastructure asset data collecting, managing and sharing. The key implementation hurdles were summarized, which indicated that in current practice, the construction documentation process and the asset in-place data collection process in SHAs are two separate entities, and that this discrepancy caused data loss and duplicate data collection. Further, the survey included questions aimed at seeking the expectations from SHAs towards future improvement. To overcome the data blockage in the current practice, the paper-based data is expected to be replaced with electronic data, and a mechanism is needed to facilitate the flow of data items collected in construction documentation to asset management information systems from the long-term operation and maintenance (O&M) perspective. The results and findings are valuable in emphasizing the current practice hurdles in collecting, managing and sharing transportation infrastructure assets, as well as assisting SHAs to make efficient decisions for future research and implementation.

A Synthesis Study on Collecting, Managing, and Sharing Road Construction Asset Data

Accurate and complete construction records and as‐built data are the key prerequisites to the effective management of transportation infrastructure assets throughout their life cycle. The construction phase is the best time to collect such data. Assets such as underground drainage and culverts are visible and physically accessible only during construction. For assets such as guardrails, signals, and pavement, it is safer and more efficient to collect data during construction than after construction when the road segment is open to traffic. The purpose of this project was to conduct a synthesis study to 1) assess the current status at Indiana Department of Transportation (INDOT) regarding the collection of asset data during the construction phase and the use of such data in the operation and maintenance (O&M) phase, and 2) develop a framework for INDOT to leverage the construction inspection and documentation process to collect data for assets. Data needs during O&M were identified through rounds of meetings with relevant INDOT business units. The current practice in construction documentation was investigated in detail. A survey of state highway agencies (SHAs) was conducted to assess the state‐of‐the‐practice. A practical framework was developed to leverage the construction inspection and documentation practice to collect asset data that are needed in O&M. The framework uses specific pay items—construction activities that result in physical structures—as the bridge to connect plan assets (i.e. physical structures specified in the design documents) to their corresponding counterparts in the asset management systems. The framework is composed of 1) a data needs component for determining the information requirements from the O&M perspective, 2) a construction documentation module, and 3) a mapping mechanism to link data items to be collected during the construction documentation to data items in the asset management systems. The mapping mechanism was tested and validated using four priority asset classes—underdrains, guardrails, attenuators, and small culverts—from an INDOT construction project. The testing results show that the newly developed framework is viable and solid to collect asset data during the construction phase for O&M use in the future, without adding extra workload to construction crews. The framework can reduce/eliminate the duplicate data collection efforts at INDOT, leading to savings and efficiency gains in the long term.