Understanding and Communicating Reliability of Crash Prediction Models (2021) / Chapter Skim
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3 Chapter 1. Introduction and Background Highway Safety Manual and the Crash Prediction Methodology The 1st edition of the Highway Safety Manual (AASHTO, 2010)
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4 ο· Repeatability describes the extent to which multiple analysts using the same CPM with the same training, data sources, and site of interest obtain the same results (as measured by the number of significant figures showing agreement among results)
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5 be used to predict effect of design alternatives on fatal crashes, but the reliability of these estimates needs to be communicated because many of the CPMs in the HSM were estimated based on limited samples of fatal crashes. ο· Application to sites with characteristics that are not represented by CPM.
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6 become less reliable over the same time period. In recognition of this issue, the HSM recommends the recalibration of CPMs every two to three years (AASHTO, 2010)
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7 Table 2. Application-Related Factors Influencing the Reliability of an Estimated Value Using a CPM.
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8 This was a two-phase effort. Phase I included a kickoff call, reviewing and assimilating literature and state of the art, analysis of relevant resource data and identify gaps, develop work plan, develop an annotated outline of the guidance document, develop an annotated outline of the communications plan, develop an interim report, and a face to face interim meeting.
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9 For linear regression models, the R2 statistic, the proportion of the total variation in the dependent variable explained by the model, is the GOF measure typically reported. For Generalized Linear Models (GLMs)
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10 where Bias = percent bias in reported value; Np = predicted crash frequency from CPM, crashes/yr; and Np,true = predicted true crash frequency, crashes/yr; Root mean squared difference (RMSD)
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11 Equation 7 π‘βππ‘π π
πππ‘ ππππ πππ’ππππ π·πππππππππππππ π΄ππ πππ’π‘π π·πππππππππ The value of the absolute difference at the desired percentile level can be determined using online calculators such as https://homepage.divms.uiowa.edu/~mbognar/applets/gamma.html, or using statistical textbooks. For example, using the 85th percentile and estimated Gamma distribution parameters, the analyst estimates the value of Absolute Deviation that 85% of sites would be expected to be less than or equal to, or conversely, the value that 15% of sites may exceed.
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12 f(k) = estimate of the dispersion parameter.
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13 Figure 1. Example CURE Plot (Source: Hauer and Bamfo, 1997)
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14 Figure 2. CURE Plot with Confidence Limits (Source: Hauer and Bamfo, 1997)
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