Collecting Horizontal Curve Data: Mobile Asset Vehicles and Other Techniques

Abstract

Mobile asset data collection vehicles can provide transportation agencies with inventories of various roadway and roadside elements containing location information, element type, and condition data. Horizontal curves are of interest to agencies because they have been shown to be hazardous roadway components and have potential for mobile data collection concurrently with other roadway elements. The cost of manually acquiring horizontal curvature data to develop an inventory can be prohibitive for many agencies, so understanding the applicability of a mobile asset data collection effort for curves is important. The objective of this work was to study the ability of multiple commercial roadway inventory vehicles and to compare them to other methods for determining the geometric characteristics of horizontal curves. The comparison is based on data from three commercial vendors of roadway asset inventory data on a 38.8-km (24.1-mi) course in central North Carolina. Among the 16 curves studied, at least one vendor was within 10% of the radius value found with the manual chord method for six of the curves and within 25% for 13 of the curves. Only three curves had a larger radius variant. For the length measurements of the 16 curves, at least one vendor was within 10% of the length from the chord method for eleven of the curves and within 25% for fifteen of the curves. Only one curve had a larger length variant. The mobile vehicle vendors provided more accurate and consistent curve length measurements than radius measurements. Agencies that consider using mobile data collection vehicles for horizontal alignments should understand the limitations of each horizontal curve estimating technique and the changes that can occur in the radius within the curve. Collaborating with vendors to define the changes in roadway alignment that constitute a curve, the associated beginning and ending of the curve, and geometric characteristics can provide agencies the most appropriate data to meet their needs.