Rafael Jurado-Piña

Empirical calibration of a roadside hazardousness index for Spanish two-lane rural roads

Crash records and roadside data from Spanish two-lane rural roads were analyzed to study the effect of roadside configuration on safety. Four indicators were used to characterize the main roadside features that have an influence on the consequences of roadway departures: roadside slope, non-traversable obstacles distance from the roadway edge, safety barrier installation, and alignment. Based on the analysis of the effect of roadside configuration on the frequency and severity of run-off-road injury crashes, a categorical roadside hazardousness scale was defined. Cluster analysis was applied to group the combinations of the four indicators into categories with homogeneous effects on run-off-road injury crashes frequency and severity. As a result a 5-level Roadside Hazardousness Index (RHI) was defined. RHI can be used as reference to normalize the collection of roadside safety related information. The index can also be used as variable for inclusion of roadside condition information in multivariate crash prediction models.

Methodology to Predict Driver Vision Impairment Situations Caused by Sun Glare

This paper presents a methodology to determine the days and times of the year when sun glare may impair drivers’ vision on a particular road section, depending on the geographic location, the geometric design of the road, and the physical characteristics of the environment. The methodology is based on applying cylindrical charts to represent the entire set of variables involved in the problem. The results may be used to study in detail the problem at critical sections of existing or newly designed roads such as intersections, freeway ramps, and tunnel exits. The methodology may also support the use of variable message signs to warn drivers of the risk of vision impairment at the exact times and locations where high-glare conditions occur.

A genetic algorithm for slope stability analyses with concave slip surfaces using custom operators

Heuristic methods are popular tools to find critical slip surfaces in slope stability analyses. A new genetic algorithm (GA) is proposed in this work that has a standard structure but a novel encoding and generation of individuals with custom-designed operators for mutation and crossover that produce kinematically feasible slip surfaces with a high probability. In addition, new indices to assess the efficiency of operators in their search for the minimum factor of safety (FS) are proposed. The proposed GA is applied to traditional benchmark examples from the literature, as well as to a new practical example. Results show that the proposed GA is reliable, flexible and robust: it provides good minimum FS estimates that are not very sensitive to the number of nodes and that are very similar for different replications.