Road safety is closely related to geometric design consistency, which is usually assessed by examining operating speed. Most consistency models only consider passenger car speeds, even though the interaction between passenger cars and heavy vehicles plays a pivotal role in road safety. This is due to the fact that there are too few models to estimate heavy vehicle speeds. This study aims to develop speed prediction models for heavy vehicles on horizontal curves of two-lane rural roads. To do this, continuous speed profiles were collected by using Global Positioning System (GPS) tracking devices on 11 road sections. Truck speeds were analyzed on 105 horizontal curves. The results showed that the radius of the horizontal curve and the grade at the point of curvature have a significant influence on heavy vehicle speeds. In this regard, vertical alignment only has a significant effect on truck speeds along upgrades. In addition, different trends were identified for loaded and unloaded trucks, so different speed models were calibrated for each of them. As a result, heavy vehicle speeds were adversely affected by grades greater than 3%. This phenomenon was larger for loaded trucks than for unloaded ones. Finally, the calibrated 85th and 15th percentile speed models were compared with those developed previously. As a conclusion, the use of the proposed models in this study was recommended on Spanish two-lane rural roads due mainly to the different characteristics of heavy vehicles around the world.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.