Caltrans – Linear Referencing System (LRS) Data Model



To effectively operate California’s state highway network, the Department of Transportation Division of Transportation System Information (Caltrans) manages a wide array of system data such as physical conditions, traffic related measurements, and highway related projects. Each piece of data can be associated with a location along the state highway network via geographic coordinates or location range, with location often expressed as linear distance.

Caltrans required an accurate and consistent system that converted location descriptions into a format that could be accessed and maintained, using a linear referencing system (LRS). Within an LRS, dynamic segmentation represents the process of converting a location described in terms of locations along routes into geometric entities that can be displayed on a map and used for business processes. Unfortunately, Caltrans’ existing LRS was marked by inaccuracies and inefficiencies such as inefficient file system storage and poor positional and attribute accuracy of the highway data.


Farallon developed a highway network in Oracle that uses an LRS along with multiple (including Caltrans-specific) linear referencing methods. Farallon integrated custom applications within the network to perform dynamic segmentation and reverse dynamic segmentation. Farallon employed legacy conventions that maintain a link to all the institutional knowledge and processes at Caltrans.

Caltrans can now access geospatial data (road conditions, terrain specifics, surrounding properties) for specific sections of transportation lines down to the exact geographic coordinates. With quicker access to detailed and accurate information, Caltrans has the ability to more efficiently assess and improve areas of California transportation lines.

The solution provides

  • Improved road accuracy
  • Seamless highway network with measure basis of distance
  • Seamless dynamic segmentation across county boundaries
  • Dynamic segmentation capabilities based on distance measure or postmile
  • Centralized data, multi-departmental use
  • Web-based dynamic segmentation capabilities