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Publication Number:  FHWA-HRT-14-057    Date:  February 2018
Publication Number: FHWA-HRT-14-057
Date: February 2018

 

Safety Evaluation of Access Management Policies and Techniques

CHAPTER 8. GUIDANCE FOR PRACTICAL APPLICATION OF THE MODELS

This chapter is intended to guide a user through the steps required to select and apply the most appropriate model(s) for estimating the safety impacts of a contemplated AM strategy or combination of strategies for a corridor. The model selection and application process involves the following four steps.

  1. Select land use and region.
  2. Select crash types and variables of interest.
  3. Select analysis type of interest.
  4. Select applicable model(s) and perform analysis.

The remainder of this chapter provides a detailed discussion of the four-step process. Chapter 9 provides numerical sample problems to illustrate the steps presented here.

STEP 1: SELECT LAND USE AND REGION

Select the applicable land use and region based on the application context. The land use categories include mixed-use, commercial, or residential as defined in chapter 2. Regions include North Carolina, Minnesota, Northern California, or Southern California. One consideration in selecting an applicable region is a comparison of local values with the mean values of the variables in each region (see appendix D). It is recommended that users select an applicable region based on the summary statistics that best match their study corridor rather than selecting the region based on geographic proximity. The result of this step is the identification of the most applicable land use type and region.

STEP 2: SELECT CRASH TYPES AND VARIABLES OF INTEREST

Select the crash types and variables of interest. The selection of crash types and variables determines which model(s) will be needed. The potential crash types include total, injury, turning, rear-end, and right-angle as defined in table 8. The potential variables of interest include AADT, corridor length, and the following access-related characteristics:

STEP 3: SELECT ANALYSIS TYPE OF INTEREST

Select the analysis type of interest from the following two choices:

STEP 4: SELECT APPLICABLE MODEL(S) AND PERFORM ANALYSIS

Select the applicable model(s) based on table 24 through table 26. Note the following factors, in priority order, were considered when populating table 24 through table 26 when more than one option was available in appendix C for the land use and crash type of interest:

  1. Statistical significance of the coefficients for the variables of interest as indicated by the size of the p-value; a lower p-value indicates a higher level of significance.

  2. A smaller value of k indicates a better fitting model.

Continue to algorithm 1 or algorithm 2 based on the analysis type selected in step 3 and the applicable models identified in table 24 through table 26. Recall that algorithm 1 applies to analysis option 1, and algorithm 2 applies to analysis option 2. Sample problems are presented in chapter 9 to illustrate various scenarios, and the following guiding principles are common to all scenarios:

Table 24. Relevant models by crash type of interest—mixed land use.

Crash Type Variables Available for Specified Land Use Applicable Model (Table No.) Variables Available Through Extrapolation Applicable Model for Extrapolation of Variables (Table No.) Applicable Base Model for Extrapolation and EB Method (Table No.)
Total ACCDENS Table 34 Table 35
Total PROPLANE1 Table 35 Table 35
Total PROPNODEV Table 36 Table 35
Total SIGDENS Table 35 Table 35
Total UNSIGDENS Table 35 Table 35
Total PROPFULLDEV Table 59 Table 35
Injury PROPLANE1 Table 38 Table 38
Injury PROPNODEV Table 38 Table 38
Injury SIGDENS Table 37 Table 38
Injury ACCDENS Table 49 Table 38
Injury PROPVC Table 51 Table 38
Injury PROPFULLDEV Table 64 Table 38
Turning ACCDENS Table 39 Table 40
Turning PROPNODEV Table 41 Table 40
Turning SIGDENS Table 39 Table 40
Turning UNSIGDENS Table 40 Table 40
Turning PROPLANE1 Table 54 Table 40
Rear-end PROPLANE1 Table 43 Table 43
Rear-end SIGDENS Table 43 Table 43
Rear-end PROPTWLTL Table 70 Table 43
Right-angle ACCDENS Table 44 Table 44
Right-angle MEDOPDENS Table 45 Table 44
Right-angle PROPDIV Table 45 Table 44
Right-angle PROPFULLDEV Table 46 Table 44
Right-angle SIGDENS Table 44 Table 44
Right-angle PROPLANE1 Table 73 Table 44
—Not applicable.

 

Table 25. Relevant models by crash type of interest—commercial land use.

Crash Type Variables Available for Specified Land Use Applicable Model (Table No.) Variables Available Through Extrapolation Applicable Model for Extrapolation of Variables (Table No.) Applicable Base Model for Extrapolation and EB Method (Table No.)
Total ACCDENS Table 47 Table 47
Total SIGDENS Table 47 Table 47
Total PROPNODEV Table 48 Table 47
Total UNSIGDENS Table 35 Table 47
Total PROPLANE1 Table 34 Table 47
Total PROPFULLDEV Table 59 Table 47
Injury ACCDENS Table 49 Table 52
Injury SIGDENS Table 52 Table 52
Injury PROPNODEV Table 50 Table 52
Injury PROPLANE1 Table 52 Table 52
Injury PROPVC Table 51 Table 52
Injury PROPFULLDEV Table 64 Table 52
Turning ACCDENS Table 53 Table 53
Turning SIGDENS Table 53 Table 53
Turning PROPNODEV Table 54 Table 53
Turning PROPLANE1 Table 54 Table 53
Turning UNSIGDENS Table 40 Table 53
Rear-end SIGDENS Table 56 Table 56
Rear-end PROPLANE1 Table 56 Table 56
Rear-end PROPTWLTL Table 70 Table 56
Right-angle ACCDENS Table 57 Table 57
Right-angle SIGDENS Table 57 Table 57
Right-angle PROPFULLDEV Table 58 Table 57
Right-angle MEDOPDENS Table 45 Table 57
Right-angle PROPDIV Table 45 Table 57
Right- angle PROPLANE1 Table 73 Table 57
—Not applicable.

 

Table 26. Relevant models by crash type of interest—residential land use.

Crash Type Variables Available for Specified Land Use Applicable Model (Table No.) Variables Available Through Extrapolation Applicable Model for Extrapolation of Variables (Table No.) Applicable Base Model for Extrapolation and EB Method (Table No.)
Total PROPLANE1 Table 59 Table 59
Total SIGDENS Table 59 Table 59
Total PROPFULLDEV Table 59 Table 59
Total ACCDENS Table 61 Table 59
Total PROPNODEV Table 62 Table 59
Injury PROPLANE1 Table 64 Table 63
Injury SIGDENS Table 63 Table 63
Injury PROPFULLDEV Table 64 Table 63
Injury ACCDENS Table 49 Table 63
Injury PROPNODEV Table 38 Table 63
Injury PROPVC Table 51 Table 63
Turning UNSIGDENS Table 66 Table 66
Turning SIGDENS Table 67 Table 66
Turning ACCDENS Table 67 Table 66
Turning PROPNODEV Table 68 Table 66
Turning PROPLANE1 Table 54 Table 66
Rear-end SIGDENS Table 69 Table 70
Rear-end PROPLANE1 Table 70 Table 70
Rear-end PROPTWLTL Table 70 Table 70
Right-angle SIGDENS Table 73 Table 73
Right-angle PROPLANE1 Table 73 Table 73
Right-angle PROPFULLDEV Table 73 Table 73
Right-angle ACCDENS Table 74 Table 73
—Not applicable.

 

ALGORITHM 1

Algorithm 1 pertains to analysis option 1, comparing the relative safety impact of two alternatives, alternative A and alternative B, one of which can be a do-nothing alternative.

Step 4.1.1: Data for Conditions of Interest

The user identifies values for alternative A and alternative B, including corridor length, AADT, and all variables of interest for all models to be used in the analysis. A value must be provided for corridor length and AADT. For all other variables, a default value may be used if a value cannot be entered (default values are given in appendix D). The default value is the mean value for the variable of interest and is determined by the land use and region selected.

Step 4.1.2: Calculations for Nonextrapolated Variables

Using the model(s) from column 3 in table 24 through table 26, compute the predicted crashes for existing conditions based on the values identified for alternative A. The next calculation only changes the variable(s) of interest, and the following two cases may be distinguished:

Step 4.1.3: Calculations for Extrapolated Variables

Variables available through extrapolation of another land use model are identified in column 4 of table 24 through table 26. The extrapolation method first requires the use of a base model from the land use and crash type of interest to predict crashes for existing conditions. Then, a model is selected from another land use to estimate the impacts of the variables of interest. For each variable to be considered through extrapolation, take following steps.

Step 4.1.3a Baseline Predicted Crashes for Existing Condition

Use the applicable base model from table 24 through table 26 with the values from the existing condition (alternative A) to estimate the baseline predicted crashes for the existing condition.

Step 4.1.3b Estimate the Impacts of the Variables of Interest for Existing Conditions

The effects of the variables of interest for the existing conditions are estimated using the equation in figure 20:

Figure 20. Equation. Formula to estimate effects of variables of interest for existing conditions. Multiplier equals exp to the open parenthesis coefficient close parenthesis times open parenthesis Variable Actual Value minus Variable Default Value close parenthesis power.

Figure 20. Equation. Formula to estimate effects of variables of interest for existing conditions.

 

The coefficient is obtained for the variable of interest from the extrapolation model identified in column 5 of table 24 through table 26. The Variable Actual Value is obtained from the existing condition (alternative A). The Variable Default Value is the mean value of the variable of interest for the region and land use type from which that model was developed. Default values can be found in appendix D.

Step 4.1.3c Adjusted Predicted Crashes for Existing Condition

The estimate from step 4.1.3b is then multiplied by the estimate from step 4.1.3a to compute the adjusted predicted crashes for existing conditions.

Step 4.1.3d Baseline Predicted Crashes for Proposed Condition

Use the applicable base model from table 24 through table 26 with the values from the proposed condition (alternative B) to estimate the baseline predicted crashes for the proposed condition.

Step 4.1.3e Estimate the Impacts of the Variables of Interest for Proposed Conditions

The effects of the variables of interest for the proposed conditions are estimated using the equation in figure 20.

The coefficient is obtained for the variable of interest from the extrapolation model identified in column 5 of table 24 through table 26. The Variable Proposed Value is obtained from the proposed condition (alternative B). The Variable Default Value is the mean value of the variable of interest for the region and land use type from which that model was developed. Default values can be found in appendix D.

Step 4.1.3f Adjusted Predicted Crashes for Proposed Condition

The estimate from step 4.1.3e is then multiplied by the estimate from step 4.1.3d to compute the adjusted predicted crashes for proposed conditions.

Step 4.1.4: Estimated Safety Impacts

The results from steps 4.1.2 and 4.1.3 can be used to compare the predicted crashes per year for alternative A and alternative B. The results may be presented as the difference or the percent change in predicted crashes per year.

ALGORITHM 2

Algorithm 2 pertains to analysis option 2, comparing expected crashes for existing and proposed conditions. Recall that one of the conditions is the existing condition because a crash history is required to apply algorithm 2. In this context, alternative A is the existing condition, and alternative B is the proposed condition.

Step 4.2.1: Data for Conditions of Interest

The user identifies values for alternative A and alternative B, including corridor length, AADT, and all variables of interest for all models to be used in the analysis. A value must be provided for corridor length and AADT. For all other variables, a default value may be used if a value cannot be entered (default values are given in appendix D). The default value is the mean value for the variable of interest and is determined by the land use and region selected. The observed crash history for the existing condition is also identified, including the number of years of crash data and crash totals for each crash type selected. Finally, the user must identify a calibration factor for all crash types selected. The default value is 1.0, but a user may compute a local calibration factor based on the procedure described in chapter 10.

Step 4.2.2: Prediction for Existing Condition

Steps 4.2.2a through 4.2.2d are completed for each crash type selected. The baseline predicted crashes for the existing condition are modified using the EB method, which uses the crash history of the corridor. The EB method is used to compute the expected crashes.(19)

Step 4.2.2a Baseline Predicted Crashes for Existing Conditions

Use the applicable base model from column 6 of table 24 through table 26 with the values from alternative A to estimate the baseline predicted crashes for the existing condition.

Step 4.2.2b Estimated EB Weight

The EB weight (w) is estimated using the formula in figure 21.

Figure 21. Equation. Formula to estimate w. w equals 1 divided by open bracket 1 plus open parenthesis k times years times step 4.2.2a estimate close parenthesis close bracket.

Figure 21. Equation. Formula to estimate w.

 

Note that k is given for each specific model in appendix C.

Step 4.2.2c Expected Crashes for Existing Condition

The annual expected crash frequency (EB estimate) for existing conditions is calculated using the formula in figure 22.

Figure 22. Equation. Formula to estimate the annual expected crash frequency (EB estimate). EB estimate equals open bracket w times step 4.2.2a estimate close bracket plus open bracket open parenthesis 1 minus w close parenthesis times open parenthesis observed crashes divided by years of data close parenthesis close bracket.

Figure 22. Equation. Formula to estimate the annual expected crash frequency (EB estimate).

 

Step 4.2.2d Estimated EB Correction Factor

The EB correction factor is calculated as the expected crashes for existing conditions (step4.2.2c) divided by the baseline predicted crashes for existing conditions (step 4.2.2a).

Step 4.2.3: Prediction for Proposed Condition

Step 4.2.3a Difference in Predicted Crashes for Existing and Proposed Condition

Apply steps 4.1.2 through 4.1.4 from algorithm 1 using the existing and proposed conditions as inputs. The result is an estimate of the difference in predicted crash frequency for the existing and proposed conditions.

Step 4.2.3b Adjusted Predicted Crashes for Existing Condition

Add the difference in predicted crashes from step 4.2.3a to the baseline predicted crashes for existing conditions from step 4.2.2a.

Step 4.2.3c Expected Crashes for Proposed Condition

Multiply the adjusted predicted crashes for the existing condition from step 4.2.3b by the EB correction factor from step 4.2.2d.

Step 4.2.4: Estimated Safety Impacts

The results from algorithm 2 can be used to compare the expected crashes per year for alternative A and alternative B. The expected crashes for the existing condition are estimated from step 4.2.2c. The expected crashes for the proposed condition are estimated from step 4.2.3c. The results may be presented as the difference or the percent change in expected crashes per year.

 

 

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