Safety Prediction Models for Six-Lane and One-Way Urban and Suburban Arterials (2022) / Chapter Skim
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Pages 138-148
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138 CHAPTER 8. PREDICTIVE MODELS FOR INTERSECTIONS OF URBAN AND SUBURBAN ONE-WAY ARTERIALS This chapter describes the activities undertaken to calibrate safety predictive models for both signalized and stop-controlled intersections of urban and suburban one-way arterials.
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139 vehicle crashes, and a model was developed for total crashes. The following regression model form was used to predict the average crash frequency at an individual one-way street intersection.
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140 Variables with corresponding p-values less than 0.05 can be considered statistically significant (at the significance level α = 0.05)
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141 Table 78. Calibrated coefficients for PDO crashes at one-way street intersections.
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142 Figure 38. Graphical form of the intersection SPF for crashes on one-way street three-leg stop-controlled intersections (3ST)
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143 Figure 40. Graphical form of the intersection SPF for crashes on one-way street four-leg stop-controlled intersections (4ST)
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144 Figure 42. Comparison of the SPF by intersection category for crashes on one-way street four-leg signalized intersections (4SG)
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145 A sample of 10 intersections in California and 24 intersections in San Antonio, Texas, were selected for data collection. All the intersections involved one-way streets.
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146 The third task was to perform a goodness-of-fit evaluation to assess the applicability of the HSM model to signalized intersections of one-way streets. The Pearson's chi-squared test was used for this purpose.
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147 frequency. This section shows figures of the CMFs developed from the regression models described above for one-way street intersections.
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148 increase the size of the intersection conflict area, which could increase the exposure of vehicles to conflict with crossing movements. Table 83.
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