Road Data Aggregation and Sectioning Considerations for Crash Analysis

Increasingly, road authorities are collecting a variety of data sets related to their networks, including horizontal and vertical alignment, cross section, traffic volumes, crashes, and the location of features such as intersections and passing lanes. These data may be a mixture of point locations, fixed length records, and variable length records. A critical question concerning computational ease and practical usefulness is how best to aggregate or section the available data into appropriate road segments for operational and safety analyses. This issue is becoming more pertinent with the development of tools such as the Interactive Highway Safety Design Model (IHSDM) and the Highway Safety Manual, which require a logical partition of roads based on many different attributes. The guidance on how to do this, however, is rather scant. Analysis of traffic exposure versus crash risk is also affected by the use of fixed or variable length segments. Research is nearing completion 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 will be 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 segments. The resulting method uses horizontal alignment, significant cross-section changes, and changes in speed limit. It also attempts to minimize the number of very short segments. The resulting data set contains approximately 83,400 segments generated from 20,900 lane km (13,000 lane mi) of highway.