Examining vehicle operating speeds on rural two-lane curves using naturalistic driving data

Abstract

Horizontal curves have been shown to exhibit crash rates significantly higher than comparable tangent segments. Extensive research has investigated the causes of crashes on horizontal curves, particularly the curve navigation process and driver speed selection. Research in this area has generally been limited by the nature of the data, which is often inhibited by practical constraints as to the number of locations and drivers that can be observed. This study overcomes these hurdles through the use of naturalistic driving data, providing insights on how drivers navigate and react to curves on rural two-lane highways. Nearly 10,000 vehicle traces were collected from 202 drivers on 219 horizontal curves as a part of this study. All driving traces were collected on rural two-lane highways with prevailing posted speed limits of 45 mph or 55 mph, as well as a diverse range of curve advisory speeds. Regression models are estimated via generalized estimating equations to discern those factors affecting mean speeds on curves. A log-linear relationship was found between curve radius and mean vehicle speed, with speeds relatively stable on radii of 900–1000 ft. or more, decreasing more rapidly as radii decreased below this range. Drivers were found to reduce speeds when curve advisories were present, but the magnitude of these reductions was much less than suggested by the advisory signs. Speeds were significantly lower when a W1-6 curve arrow sign was present adjusting for the curve radius. There were also some differences in speeds based on driver age and gender. Ultimately, this paper provides insights into driver curve navigation and demonstrates the potential of high-fidelity naturalistic driving data to assess speed management and geometric design on horizontal curves.