Integration of Innovative Sensing Technology and Data Analytics in Transportation Asset Management

Transportation asset management is an important tool to maintaining good physical status, quality service and trustworthy safety of infrastructure. Timely repair, rehabilitation, and preventive maintenance are critically important to maintaining such quality status and service, and prolonging service life at reduced costs. Infrastructure (bridges and pavements) degradation is a non-linear process and critical points where degradation rates change are important in decision making on rehabilitation. Nevertheless, it is challenging to predict the time of occurrence of such critical points. A number of modeling methods or models have been developed and yet the accuracy is very limited. Without reliable performance models, maintenance scheduling and life cycle cost assessments are not reliable and essentially just a mathematics manipulation. The limitations of such models are 1) models mainly based on mixture property testing in laboratories; 2) without considering the complicated loading and environmental conditions; 3) no integration of mix design lab test results and as constructed pavement properties; 4) having only relatively simple methods based on cause effect analysis of single or few causes. Recently a number of sensing techniques such as self-powered sensing, vibration sensor arrays and data analytics methods such as deep learning approaches have emerged and shown some promising features but not yet solidly developed to warrant implementation and realistic applications in asset management.

• Supplemental Notes:
  • Project funded from core funds award

Language

• English

Project

• Status: Active
• Funding: $300000
• Contract Numbers:

  69A3551847103

• Sponsor Organizations:

  Office of the Assistant Secretary for Research and Technology

  University Transportation Centers Program
  Department of Transportation
  Washington, DC  United States  20590
• Managing Organizations:

  Center for Integrated Asset Management for Multimodal Transportation Infrastructure Systems (CIAMTIS)

  Pennsylvania State University
  University Park, PA  United States  16802
• Project Managers:

  Donnell, Eric

  Rajabipour, Farshad

• Performing Organizations:

  Virginia Tech Transportation Institute

  3500 Transportation Research Plaza
  Blacksburg, Virginia  United States  24061
• Principal Investigators:

  Wang, Linbing

• Start Date: 20190311
• Expected Completion Date: 20230310
• Actual Completion Date: 0
• USDOT Program: University Transportation Centers

Subject/Index Terms

• TRT Terms: Asset management; Data analysis; Data collection; Degradation failures; Forecasting; Infrastructure; Sensors; Technological innovations
• Subject Areas: Data and Information Technology; Maintenance and Preservation; Planning and Forecasting; Transportation (General);

Filing Info

• Accession Number: 01699759
• Record Type: Research project
• Source Agency: Center for Integrated Asset Management for Multimodal Transportation Infrastructure Systems (CIAMTIS)
• Contract Numbers: 69A3551847103
• Files: UTC, RIP
• Created Date: Mar 25 2019 5:08PM