Speed Prediction Models for Trucks on Horizontal Curves of Two-Lane Rural Roads

Llopis-Castelló, David; González-Hernández, Brayan; Pérez-Zuriaga, Ana María; García, Alfredo · 2018 · Crossref

DOI: 10.1177/0361198118776111

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Summary

This study addresses the lack of speed prediction models for heavy vehicles on two-lane rural roads, a gap that compromises geometric design consistency and road safety. While passenger car operating speeds are well-documented, heavy vehicle speeds are rarely integrated into design guidelines, despite the significant safety risks posed by speed differentials between cars and trucks. The research aims to develop specific speed prediction models for trucks on horizontal curves, analyzing the influence of both horizontal and vertical alignment, as well as vehicle load status. The methodology involved collecting continuous speed profiles using 1Hz GPS tracking devices installed on heavy vehicles from three transport companies in the Valencian region of Spain. Data were gathered between May and July 2015 under dry, free-flow conditions. The study focused on 105 horizontal curves across eleven road segments, analyzing both loaded and unloaded trucks. The vertical alignment was derived from LIDAR data, and the horizontal alignment was recreated using heading direction algorithms. The researchers specifically analyzed the minimum speed and the speed at the midcurve, rejecting the common assumption that these values are equivalent. The results indicate that the radius of the horizontal curve and the grade at the point of curvature are the primary determinants of truck speeds. Distinct trends were observed for loaded versus unloaded trucks, necessitating separate regression models for the 85th and 15th percentile speeds. The study found that vertical alignment significantly affects truck speeds only on upgrades, with grades exceeding 3% adversely impacting speed. This effect was more pronounced for loaded trucks, which showed a greater sensitivity to grade increases than unloaded trucks. The calibrated models demonstrated that loaded trucks are more influenced by the radius up to 300 meters, compared to 200 meters for unloaded trucks, due to differences in the center of gravity. Additionally, the speed deviation between the 85th and 15th percentiles was larger for loaded trucks, indicating greater variability in their operating speeds. The significance of this work lies in providing validated speed prediction models tailored to Spanish two-lane rural roads, highlighting that universal models are insufficient due to regional differences in vehicle characteristics and road geometry. The findings support the integration of heavy vehicle speeds into highway design guidelines to improve geometric consistency. By demonstrating that heavy vehicle speeds depend on both horizontal and vertical alignments, the study advocates for a three-dimensional approach to road design, ultimately aiming to reduce crash likelihood by minimizing unexpected speed variations and conflicts between passenger cars and heavy vehicles.

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• road geometry