Operating Speed models for heavy vehicles on tangents of Spanish two-lane rural roads

Road safety is one of the most important public health concern in our society. In Spain, the most of the traffic accidents involving a heavy vehicle occur on two-lane rural roads. Current consistency models only rely on the analysis of the operating speed profile for passenger cars due to the few speed models available for heavy vehicles. Therefore, the main objective of this research was to analyze and model the free flow speed developed by heavy vehicles on tangents of two-lane rural roads. Thus, this research presents new speed models for estimating heavy vehicle speeds on tangents of two-lane rural roads. To do this, truck speeds were collected by means of Global Positioning System tracking devices, on 49 tangents sections that were identified from 12 road sections. Two different patterns were detected, which were associated with loaded and unloaded trucks. The combined effect of geometric and operational variables was analyzed. As a result, the most influential variables on loaded truck speeds were the speed of the preceding horizontal curve and the grade of the tangent, whereas unloaded truck speeds were significantly influenced by the length of the tangent and the speed of the preceding horizontal curve. Finally, several regression models were calibrated to predict the 85th and 15th percentile speeds for both loaded and unloaded trucks

Incorporating pavement deterioration uncertainty into pavement management optimization

This is an Accepted Manuscript of an article published by Taylor & Francis in International Journal of Pavement Engineering on 2022, available online: https://www.tandfonline.com/doi/full/10.1080/10298436.2020.1837827[EN] Pavement management systems can be used to efficiently allocate limited maintenance budgets to better align with pavement deterioration. However, pavement deterioration is subject to uncertain factors that complicate the prediction of future pavement conditions accurately, entailing differences in the optimum maintenance strategy. This paper addresses this challenge by introducing a method to aid local engineers in optimising the scheduling of maintenance activities under uncertain pavement deterioration conditions. Markov chains are used to simulate the variability of life-cycle performance. Moreover, a multi-objective optimisation of an urban network is carried out to find the maintenance programme that minimises the mean life-cycle cost, maximises the mean user benefit, and minimises the standard deviation of life-cycle cost. This third objective enables the optimisation routine to minimise the possibility of unintentionally increasing the life-cycle cost due to system variability. This approach results in a reduction of the life-cycle cost variability by up to 62%, provides pavement strategies that benefit road users as a result of better pavement conditions, and reduces the risk of resorting to costly future maintenance activities.This work was supported by the Spanish Ministry of Science and Innovation with the European Regional Development Fund (grants BIA2017-85098-R and RTC-2017-6148-7).García-Segura, T.; Montalbán-Domingo, L.; Llopis-Castelló, D.; Lepech, MD.; Sanz-Benlloch, MA.; Pellicer, E. (2022). Incorporating pavement deterioration uncertainty into pavement management optimization. International Journal of Pavement Engineering. 23(6):2062-2073. https://doi.org/10.1080/10298436.2020.18378272062207323

Speed prediction models for trucks on horizontal curves of Spanish two-lane rural roads

Road safety is closely related to geometric design consistency, which is usually assessed by examining operating speed. Most of consistency models only consider passenger car speeds, even though the interaction between passenger cars and heavy vehicles plays a pivotal role on road safety. This is due to the 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 eleven road sections. As a result, 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 great influence on heavy vehicle speeds. To this regard, vertical alignment only has a significant effect on truck speeds developed along upgrades. In addition, different trends were identified for loaded and unloaded trucks. Several speed models were calibrated for both loaded and unloaded trucks. 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