Safety Prediction Models for Six-Lane and One-Way Urban and Suburban Arterials (2022) / Chapter Skim
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Pages 110-124
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110 CHAPTER 6. PREDICTIVE MODELS FOR INTERSECTIONS OF URBAN AND SUBURBAN ARTERIALS WITH SIX OR MORE LANES This chapter describes the activities undertaken to calibrate safety predictive models for both signalized and stop-controlled intersections of urban and suburban roadway arterials with six or more lanes.
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111 Table 57. Supplemental data collected for intersections as a whole.
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112 conditions. The CMFs were used to adjust the SPF estimate when the attributes of the subject site were not consistent with the base conditions.
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113 πΆππΉ = U-turn prohibition CMF. πΆππΉ = right-turn channelization CMF.
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114 Table 59. Calibrated coefficients for FI crashes at two-way street intersections.
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115 Table 60. Calibrated coefficients for PDO crashes at two-way street intersections.
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116 Figure 27. Graphical form of the intersection SPF for crashes on three-leg stop-controlled intersections (3ST)
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117 The relationship between crash frequency (FI and PDO crashes) and traffic demand for base conditions, as obtained from the calibrated models, is illustrated in Figure 29 for four-leg stopcontrolled intersections.
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118 The proportions in Table 61 are used to separate total crashes into components by crash type for intersections with six-or-more-lane streets. Table 61.
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119 Chapter 12)
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120 where, π = predicted average crash frequency of an individual intersection (excluding vehicle-pedestrian and vehicle-bicycle collisions)
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121 The bicycle crash adjustment factor is estimated by dividing the vehicle-bicycle crashes by the sum of single-vehicle and multiple-vehicle crashes for each intersection type. Table 63 presents the values of π .
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122 Table 64. Nighttime crash proportions for unlighted intersections.
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124 The base condition for the number of lanes CMF is six lanes on the major street and two lanes on the minor street (excluding left-turn and right-turn lanes added at the intersection)
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