Bermúdez-Arbona, Alex M.

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    Velocidad y diseño geométrico: Factores para identificar curvas potencialmente peligrosas en carreteras rurales de dos carriles en Puerto Rico
    (2018-05) Bermúdez-Arbona, Alex M.; Cruzado-Vélez, Ivette; College of Engineering; Valdés Díaz, Didier; González Vélez, Enrique; Torres Saavedra, Pedro; Pagán Trinidad, Ismael; Department of Civil Engineering; Colón, Omar
    Two-lane rural highways network is relevant in the movement of vehicles, freight and socioeconomic development of the cities, towns and municipalities that are served. Furthermore, these types of highways provide access and links to principal arterials within the network. The Federal Highway Administration (FHWA) states that rural highways move the 40% of the total volume of traffic in the United States (2013). However, 57% of traffic fatalities every year occur along this type of highways. Horizontal curves along highways are considered one of the most dangerous elements in the design of the road since 25% of the fatalities are associated with this geometric characteristic. Another factor that has a great effect in the frequency and severity of the crashes is the operational speed along highways, especially when these exceed both the posted and the design speeds. This research focused in collecting speed data of free flow vehicles, geometric characteristics and crash data in two lane rural highways in the west area of Puerto Rico in order to identify high risk horizontal curves and predict the high severity crash rates and probabilities. The purpose of this research required three different types of data in the selected horizontal curves. The first was speed data along the horizontal curve; speed sensors were located in five points in the horizontal curve (entry tangent, point of curvature, midpoint, tangent point and exit tangent). Vehicles captured in all five points in the curve section were used in the analysis and model development. The second data collected are geometric characteristic of road segment; this data include all measures of cross section, horizontal curve geometric design and qualitative features of highway section. The final type of data was the crash history; in this research were analyzed all high severity crashes related to horizontal curves in two lane rural highways in Puerto Rico. Four regression technics were used in the analysis in order to correlate the speed variables and highway characteristics with high severity crash rates: Poisson, Zero Inflated Poisson, Negative Binomial, and Zero Inflated Negative Binomial. Negative binomial model were selected as the best model for high severity crash rates; the independent variables found to be significantly influence the response variable and therefore included in the model were percentage of reckless drivers, curve radii, type of horizontal curve (Isolated, inverted and consecutive), and highway functional classification (arterial, collector, local). Another two regression models were used for the response variable associated with high severity crash probability. The model that best fitted the crash data was the logistic model; the independent variables found to be significant were annual average daily traffic (AADT), operational speed differentials, kurtosis at point of curvature, curve radii, driveway density, and functional classification (arterial, collector, local). Additional to the geometric characteristics, the selected models include several speed variables that reflect the drivers’ behavior along the horizontal curves (speed differentials between MC and entry tangent, Speed differential between exit tangent and PT and kurtosis at PC). This information is an important focus in safety evaluation and can assist the decision making process in roadway design and direct efforts to improve the safety level for drivers in high risk curves.