No abstract

No abstract

The Highway Safety Manual (HSM) provides an algorithm, and associated knowledge, for predicting crashes for different facility types. This algorithm requires calibration to current local conditions to enhance transferability, using a procedure that is prescribed in the HSM. However, there is no procedure for assessing transferability. To fill this void, this paper is focused on the methodology for assessing the transferability of the key HSM algorithm components, the baseline Safety Performance Function (SPF) and the Crash Modification Factors (CMFs), using the Italian road network for an illustrative case study. The calibration of the HSM crash prediction model is investigated with a dataset for two-lane two-way rural highways, to demonstrate tools that could be used by jurisdictions around the world for assessing the validity and compatibility of the CMFs and base models, as well as the performance of the complete algorithm. A comparison with the results from a similar study carried out in Canada is provided in supplementing the conclusions on the transferability of the HSM algorithm outside the United States.* factor not applied when AADT is in [millions of vehicle per year; ** conversion factor from km to mi *** HSM default proportion of F+I crashes for rural 2U segments

No abstract

Driver behavior is influenced by environmental lighting conditions on roads; in the literature, many studies report a reduced night–day accident ratio following improvements to lighting on different types of roads, with the results classified by severity and type of accident. Few studies, however, report the influence of lighting conditions on driver speed. This study investigates the principal factors that influence driver speed on arterial roads in Turin, Italy. The aim of this study was to analyze driver speed under different daylight and nighttime lighting conditions. Six arterial roads were selected for observation and the measurement of speeds and illuminance on the pavement surface. The results showed that illuminance, in addition to factors such as lane position, lane width, and the relevant speed limit, should be considered a variable that can influence driver speed. The study used a regression equation to predict operating speeds (V85) on urban arterials; the corresponding sensitivity analysis has made it possible to quantify the effects of the aforementioned variables on operating speed under different environmental lighting conditions.