Comparison of Methods for Collecting Highway Horizontal Curve Attributes

Abstract

The design of highway curves has a significant impact on traffic safety. More than 25% of fatal crashes in the US occur on horizontal curves, and the crash rate for curves is approximately three times higher than other highway sections. Furthermore, crashes are over four times more likely to be fatal on horizontal curve sections compared with similar highway tangent sections. A key contributor to highway curve-related crashes is excessive vehicle speed. Safe highway speed on a curve is influenced by the curve’s radius and superelevation. Although these data are useful for determining curve advisory speeds or the need for curve warning signage, radius, superelevation, and other curve data have additional uses by state highway agencies. Unfortunately, many states’ highway inventory systems do not include this information, except as shown on individual roadway project design drawings. This paper compares three different methods for collecting roadway curve radii: (1) the Rieker CARS system; (2) an automated geographic information system-based method processing a roadway centerline map; and (3) manual calculations of Google Earth measurements. Additionally, mobile LiDAR scanning collected data are also evaluated for a selected sample of roadways. The analysis showed that all three methods are comparable with regard to collecting roadway curve radii. Additionally, mobile LiDAR scanning provided excellent results with regard to collecting curve parameters including radius and superelevation.