Segmentation effect on developing safety performance functions for rural arterial roads in Egypt

Abstract

This paper presents the development of safety performance functions (SPFs) for major rural arterial roads in Egypt. Four segmentation methods were used for the SPFs development: (1) constant section length of one kilometer (S1), because crash data are reported for every kilometer; (2) homogenous sections (S2), following the highway safety manual (HSM) recommendation; (3) variable sections with respect to the presence of curvatures (S3); and (4) variable sections with respect to the presence of both curvatures and U-turns (S4). The generalized linear modeling technique was used for SPFs development using the stepwise procedure, with/without considering time effect (i.e. year-to-year variation). The Akaike information criterion, Pearson product-moment correlation coefficient, and mean prediction bias along with the cumulative residual (CURE) plots are used to evaluate the prediction accuracy of the proposed models. The segmentation method was found to affect the prediction accuracy of the calibrated SPFs. For total crashes, the calibrated SPF model based on the S3 segmentation method with the time-trend model form is superior to SPFs calibrated based on other segmentation methods. While S1 and S4 segmentation methods without the time-trend model form produced the best SPFs for “fatal and injury” crashes and property damage only crashes, respectively. In addition, the results showed that by increasing each of the pavement, shoulder, and median widths, the probability of crash occurrence is likely to decrease. In addition, the presences of either horizontal curves and/or accesses are most likely to reduce the probability of crash occurrence.