Functional Requirements for a Comprehensive Transportation Location Referencing System

Functional Requirements for a Comprehensive Transportation Location Referencing System

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  • Abstract:
    Transportation agencies manage data that is referenced in one, two, three, and four dimensions. Location referencing system (LRS) data models vary across transportation agencies and often within organizations as well. This has resulted in failed attempts and abandoned efforts to interoperate business functions and/or integrate data. A number of transportation agencies, through recognition of the significance of spatially-referenced information to their operations, have identified the need for comprehensive management of location referencing. What is lacking is a clear set of functional requirements for a comprehensive location referencing system. Detailed functional requirements and a comprehensive data model are necessary so transportation agencies can implement improved transportation information systems and advanced geographic information systems technology for transportation (GIS-T). Linearly-referenced data constitutes the majority of data managed by transportation agencies. However, agencies are now using global positioning system (GPS) technology for applications ranging from highway inventory to incident management. Much more detail is needed on functional requirements for data in higher dimensions and for integration across dimensions. This paper reviews the functional requirements for a comprehensive spatial/temporal referencing system that were identified by a workshop of stakeholders in asset management, highway operations, traffic management, and transit. Among the requirements identified by the stakeholders is that a comprehensive LRS data model supports temporal referencing. Temporal aspects of transportation data impact applications ranging from pavement management (for historical records) to transit (for arrival times), to commercial vehicle operations (for vehicle tracking), to congestion management (for dynamic network modeling). 13 p.
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