Ensure Proper Fiber Optic Cable Installation for its Effective Use in Real-Time Distributed Acoustic Sensing Supporting Traffic Monitoring.

Fiber Optic Cable Deployed on Two Corridors Near Salt Lake City by the Utah Department of Transportation.

Date Posted
07/27/2026
Identifier
2026-L01294

Utah Connected

Summary Information

The Utah Department of Transportation (UDOT) was awarded a FY 2018 Advanced Transportation and Congestion Management Technologies Deployment (ATCMTD) grant for seven projects under its Utah Connected initiative.

This initiative included the Fiber Sensing project, also known as Distributed Acoustic Sensing (DAS), used fiber optic cable to monitor roadways in real time by detecting acoustic events in the vicinity of the fiber. In this project, UDOT deployed DAS in the 14-mile long Big Cottonwood Canyon and the 12-mile long Little Cottonwood Canyon corridors, two heavily used recreational corridors near Salt Lake City. Because of the terrain, traditional ITS technologies were not providing full coverage. The DAS system was tested for detecting vehicle speed, travel time, direction, and incidents, such as crashes, avalanches, and rockfalls, along the corridors.

The UDOT project team identified several lessons learned from deploying DAS. 

  • Ensure proper installation conditions. Suitable site conditions are required for effective fiber sensing, including appropriate distance from the roadway and installation methods that do not dampen acoustic signals. Several portions of the Salt Lake City corridors did not meet these conditions, limiteding detection capabilities.

  • Anticipate site-specific customization to establish appropriate algorithms for interpreting DAS data, e.g., crashes, mudslides, and avalanches. This requires a specific skillset and significant amount of ground-truth data for calibration.

  • Use fiber sensing to augment and enhance highway monitoring. Fiber sensing should not be considered as a replacement to cameras or radar sensors but should instead complement traditional monitoring methods.