Abstract

Two-lane roadways constitute the largest proportion of road networks. Their operational characteristics are significantly different from other road classifications. Allowing passing maneuvers is considered as one of the effective measures to improve mobility levels along two-lane highways, while crash records show that head-on collisions, which usually are attributed to passing maneuvers, are among the most common and most severe types of crashes on two-lane roadways. Therefore, rational and realistic estimation of the needed passing sight distance (PSD) considering driver behavior is essential for the safe design of passing zones along two-lane highways. Several random variables help to determine the minimum length required for safe passing maneuvers. Current PSD models are based on single deterministic values of the input variables to determine PSD values. This paper presents a reliability model PSD that accounts for the variability of the input random variables to offer a better representation of real-life conditions. The objectives of this paper are: (1) to design driving simulator and field experiments for data collection, (2) to develop a PSD model using the mechanics of passing maneuvers, (3) to develop a reliability model based on the first-order second-moment (FOSM) method, and (4) to validate the model using Monte Carlo simulation. In this study, driving simulator experiments were conducted to determine the passing behavior of drivers, and field data were used to validate the proposed PSD model. The proposed model accounts for the variability in the parameters by using the mean and standard deviation in a closed form estimation method. The analysis was performed for a design speed of 80 km/h, and the corresponding PSD distribution was established. A comparison of the results of the proposed model, which reflects driver behavior, and those of existing models was presented. Using the reliability-based design method, transportation engineers can adjust the PSD to fulfill a desired probability of non-compliance.

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