Safety Prediction Models for Six-Lane and One-Way Urban and Suburban Arterials (2022) / Chapter Skim
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7 CHAPTER 2. LITERATURE REVIEW This chapter summarizes the review of the literature relevant for this project.
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8 where, Nx = predicted number of crashes per year (excluding vehiclepedestrian and vehicle-bicycle crashes) for site type x (roadway segment or intersection)
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9 interest. In applying the algorithm to a jurisdiction or time period different from that for which the base model is estimated, a multiplicative calibration factor is applied to the model, calculated as the ratio of the observed number of crashes at a sample of sites to the predicted number of crashes at the sample sites using the safety prediction model prior to calibration.
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10 CMFs Five CMFs in HSM Chapter 12 apply to the predicted average crash frequency for roadway segments. The CMFs are applicable to multiple-vehicle and single-vehicle collisions, but not to vehicle-pedestrian and vehicle-bicycle collisions.
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11 • Right-turn-on-red CMF: applies to signalized intersections and depends on the number of approaches with right-turn-on-red prohibition. The base condition is RTOR permitted at all approaches.
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12 Table 1. Input variables of the safety prediction models for six-lane arterial segments and the HSM Chapter 12 methodology.
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13 • Cross-sectional attributes -- lane width, outside shoulder width, inside shoulder width, median width, surface width, curb presence, and on-street parking presence. • Alignment -- horizontal curve radius or degree of curve.
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14 ( ) llmsissigdwc NWWWWLNLND PDO eAADTLC 0682.00063.00234.00196.0/0492.0/0017.00521.04675.761065.3 −−−−++−−×= (6)
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15 LN PDOdw dweCMF /0017.0, = (15) LN KAsig sigeCMF /0286.0, = (16)
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16 curvature (i.e., greater frequency of more severe crashes)
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17 Cmv,N = multiple-vehicle FI crash frequency for segments with nonrestrictive medians, crash/year. Csv,N = single-vehicle FI crash frequency for segments with nonrestrictive medians, crash/year.
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18 CKABCO = expected crash frequency with severity levels KABCO (all crashes) , crash/year.
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19 where, Cr,KABCO = expected crash frequency (all crash severity levels) for segments with raised-curb medians, crash/year.
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20 Table 2. CMF values for land use and parking presence (based on Bonneson and McCoy, 1997)
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21 ABCtotKtottot CCC ,, += ( 61) KABCOmbcKABCOmbmwKABCOmbsi KABCOmbvslKABCOmb CMFCMFCMF CMFAADTLC ,,,,,,/ ,, 072.18223.06 , 109.5 −×= ( 62)
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22 The most appropriate method to compare the models developed by Hadi et al.
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23 Table 5. Crash rates and input variables for six-lane roadway segment models in the literature.
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24 It can be seen that the model predictions consistently show lower crash rates for restrictive medians compared to nonrestrictive medians, and likewise for nonrestrictive medians compared to undivided segments. A comparison of models that apply to undivided six-lane urban arterials is provided in Figure 1.
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25 Figure 2. Models for six-lane urban or suburban arterials with nonrestrictive medians.
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26 A comparison of models that apply to divided six-lane urban arterials with no specification of median type (nonrestrictive versus restrictive) is provided in Figure 4.
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27 Table 6. Land use CMF values.
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28 Figure 5. Lane width CMFs.
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29 Figure 6. Outside shoulder width CMFs.
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30 Median Width. CMFs for median width were developed by Petritsch et al.
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31 where, CMFhc = horizontal curvature CMF. R = curve radius, ft.
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32 indicates that a 0.2 percent increase in BC crashes would occur due to the presence of one driveway on a 1-mi urban street segment. If three driveways were present, the predicted increase in crashes would be 0.6 percent (= (1.002)
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33 More recent efforts have yielded separate SPFs and CMFs for intersections, such that intersection geometric and traffic control characteristics could be directly modeled. This approach is represented in HSM Chapter 12 and was applied by Bonneson and Pratt (2009)
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34 Table 10. Input variable values for intersection model comparisons.
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35 AADTmajor = major-street traffic volume, veh/day. AADTminor = minor-street traffic volume, veh/day.
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36 Figure 10. Models for urban four-leg signalized intersections.
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37 provided on all four approaches. To facilitate comparison between this CMF and the signal phasing CMF developed by Bauer and Harwood (1998)
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38 conducted by Harwood et al.
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39 Table 14. Right-turn channelization CMFs for signalized intersections (based on Bonneson and Pratt, 2009)
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40 orminmajor ormin ormin AADTAADT AADTP + = ( 105) where, C3U = KABC crash frequency at a three-leg unsignalized urban intersection, crash/year.
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41 Figure 11. Models for urban four-leg stop-controlled intersections.
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42 As was listed in Table 9, several CMFs are included in the preceding models. The trends of these CMFs are compared in the following paragraphs.
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43 The right-turn lane CMF documented by Bonneson and Pratt (2009) is sensitive to traffic volumes on each approach.
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44 Other CMFs. The models developed by Bonneson and Pratt (2009)
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45 district)
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46 Table 19. Conflict points at four-leg intersections (based on Smith and Hart, 1949)
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48 Figure 13. Models for four-leg diamond interchange ramp terminals (Bonneson et al., 2012)
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