Consideration of Roadside Features in the Highway Safety Manual (2022) / Chapter Skim
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From page 63... ...
63 CMFROADWAY DERIVATION Roadway characteristics that are thought to affect the probability of a vehicle leaving the roadway based on other HSM predictive models, the encroachment probability model, and the literature include: • Direction and degree of horizontal curvature (i.e., curve to the left versus curve to the right) , • Direction and percent of grade (i.e., vehicle going up a grade versus down a grade)
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64 coordination with RSAPv3. These models are shown in Table 35 and Table 36 respectively.
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65 Table 34. Negative Binomial Model for All ROR Crashes on Rural Divided Roadways.
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66 Table 35. Negative Binomial Model for Right Edge Only ROR Crashes on Rural Divided Highways.
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67 Table 36. Negative Binomial Model for Left Edge Only ROR Crashes on Rural Divided Roadways.
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68 RURAL UNDIVIDED HIGHWAY MODEL The same dataset used to develop the SPFEDGE undivided model was used here, however, it was subjected to different filtering criteria resulting in many different segments being included in the analysis. Initially, the dataset included: 2,058,268 undivided rural segment edges.
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69 Table 37. Descriptive Statistics for Rural Undivided Highway Dataset.
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70 Table 38. Negative Binomial Model for Right Edge ROR Crashes on Rural Undivided Roadways.
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71 Table 39. Negative Binomial Model for Primary Right Departure Only ROR Crashes on Rural Undivided Roadways.
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72 URBAN DIVIDED HIGHWAY MODEL The same dataset used to develop the SPFEDGE model was used here, however, it was subjected to different filtering criteria. The resulting segments, therefore, are much different.
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73 Table 40. Descriptive Statistics for Urban Divided Highway Dataset.
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74 Table 41. Negative Binomial Model for All ROR Crashes on Urban Divided Roadways.
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75 Table 42. Negative Binomial Model for Right Edge Only ROR Crashes on Urban Divided Roadways.
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76 Table 43. Negative Binomial Model for Left Edge Only ROR Crashes on Urban Divided Roadways.
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77 URBAN UNDIVIDED HIGHWAY MODEL The same dataset used to develop the SPFEDGE undivided highway model was used here, however, it was subjected to different filtering criteria resulting in many different segments being included in the analysis. Initially, the dataset included: 485,898 undivided urban segment edges.
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78 Table 44. Descriptive Statistics for Urban Undivided Highway Dataset.
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79 Table 45. Negative Binomial Model for Right Edge ROR Crashes on Urban Undivided Roadways.
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80 Table 46. Negative Binomial Model for Primary Right Departures Only on Urban Undivided Roadways.
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81 CMFROADWAY RESULTS Non-Directional CMFs The non-directionally dependent CMFs were derived from the cross-sectional models developed using the total crash frequency (i.e., not a single encroachment direction) , as shown in Table 34, Table 38, Table 41, and Table 45.
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82 Table 48. Rural Average Lane Width CMF (CMFLW)
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83 CMF for Right Shoulder Width The representation of right shoulder width within each of the databases has been repeated in Table 50 for convenience. Notice that there is a good deal of variety between divided and undivided roadways, however, the same variety is not observed by area type.
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84 Figure 27. Right Shoulder Width CMF (CMFSW)
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85 The CMFPSL generated under this research to understand the influence of posted speed limit on ROR crash frequency is shown in Table 54 for rural divided and undivided roadways and in Table 55 for urban divided and undivided roadways. These values are shown graphically in Figure 28.
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86 Figure 28. Posted Speed Limit CMF (CMFPSL)
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87 Table 57. Rural Number of Lanes CMF (CMFNL)
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88 Table 59. DOC Database Representation.
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89 Table 61. Horizontal Curve CMF for Undivided Right Edge in Direction Under Evaluation (CMFDOC)
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90 Table 62. Rural Divided Highway Horizontal Curve CMF (CMFDOC)
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91 a) Divided Left edge in direction under evaluation b)
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92 Undivided Highway CMF for Vertical Grade The Vertical Grade CMF for undivided roadways considered vehicles which exited the right roadway edge, in the direction of travel under consideration. This assessment included, therefore, vehicles traveling in the primary direction and exiting right and vehicles traveling in the opposing direction and existing left (relative to the primary direction)
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93 Divided Highway CMF for Vertical Grade The divided highway analysis for vertical grade considered cross-sectional models which included both right and left edge crashes for the urban and the rural highway types. The coefficients proposed for the rural and urban divided highway grade CMFs are shown in in Table 65.
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94 Discussion of CMFROADWAY Results Documented above are the cross-sectional models used to model the influence of onroad features on ROR crash frequency. Numerous CMFs have been developed from these models, including: • Lane width, • Right shoulder width, • Posted Speed Limit, • Number of lanes, • Percentage of heavy vehicles, • Horizontal Curvature, and • Vertical Grade.
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