Increasingly, roading authorities are collecting a variety of datasets related to the state of their networks, including horizontal/vertical alignment, cross-section, traffic volumes, crashes, and the location of featuressuch as intersections and passing lanes. This data may be a mixture of point locations, fixed-length records, and variable-length records. A critical question, both in terms of computational ease and practical usefulness,is how best to aggregate or section the available data into appropriate road elements for operational and safety analyses. This issue is becoming more pertinent with the development of tools such as Interactive Highway Safety Design Model (IHSDM) and the Highway Safety Manual, which require a logical partition of roads based on many different attributes. The guidanceon how to do this however is rather scant. Traffic exposure versus crash risk is also affected by using fixed or variable length elements. Researchis currently underway in New Zealand to combine road feature, geometry and crash data on the national rural State Highway network. The resulting database will enable better analysis of crash patterns against different types of road elements and is also being used to calibrate IHSDM for New Zealand use. This paper outlines the investigation done to determine a rational method for aggregating the available data into logical road elements. The resulting method used considers horizontal alignment, significant cross-section changes, and changes in land-use. It also attempts to minimize thenumber of very short elements. The resulting dataset contains approximately 83,400 elements generated from 20,900 lane-km of highway.
Samenvatting