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OCR for page 64
64 The output of this step will be one or more chosen treat- target subgroups, times or locations until the available budget ments, with the nature of the treatment defining the for safety improvement has been fully committed. The total specific crash types more likely to be affected. benefit of the selected program will not be forecastable, but 6. Target the chosen treatments to the user populations the success of the program can be determined by conducting where the problem is found. a sound evaluation after its implementation. In some cases, treatment strategies related to illegal Where quantitative estimates or approximations of treat- drivers will be implemented jurisdiction-wide. In other ment effectiveness can be made, it may be possible to provide cases, it may be desirable to target the treatment to either estimates of net impact (number of crashes prevented) by a subgroup (e.g., young AR drivers), to specific locations multiplying the unit treatment effects by the number of driv- (e.g., specific counties, route sections, or intersections), or ers or roadway segments treated. This should be possible for to specific time periods (e.g., DUI checkpoints at night). many of the alcohol and unlicensed/suspended/revoked However, unlike most strategies in other guides, the driver treatments but would appear unfeasible for aggressive strategies described in these three guides do not lend driver treatments due to lack of treatment effect estimates and themselves to a great degree of additional targeting in absence of data on the population volume of such drivers. many cases. Some of the strategies in Volume 1, the Aggressive Driving Guide (e.g., "Targeted Enforcement"), Alternative Economic Analysis Procedure and Volume 16, the AR Guide (e.g., DUI checkpoints), Choosing Treatments and Target Subgroups could be targeted to high-priority locations or high- for Alcohol-Related Crash Strategies When priority times of day based on crash occurrence. (They Treatment Effectiveness in Terms could also be targeted based on citation data that include of Alcohol-Related Crash/Injury Reduction the location of the offense, assuming that such enforce- Can Be Estimated ment is somewhat "random" across the jurisdiction.) If targeting is to be done by location, the treatment This second procedure for AR crash strategies is a modifi- could be targeted to counties, city areas, or routes/streets cation of the economic analysis procedures found in Proce- showing the highest total crash cost or frequency, coupled dures 1, 2a and 2b. However, the emphasis here is not on with the analyst's judgment of potential differences in cost mileposted vs. un-mileposted crashes, or on the presence or between locations and technical and political issues. If the absence of roadway inventory data. While programs related crash data are mileposted, the analyst could (1) link illegal to illegal driving could be targeted based on crash location driving crashes to routes and search for the locations of (e.g., to roadways around alcohol outlets which might gener- "clusters" of target crashes for possible treatment, or (2) ate increased AR crashes), the more likely targeting is to sub- use a network screening program similar to that described populations of drivers (e.g., young drinking drivers or repeat under Procedure 2A to identify 1-mile sections with the offenders). The procedure here assumes that effectiveness highest crash frequency or total crash cost. The windows factors for the strategies are known or can be estimated. Close identified by the network screening program could then review of the "Effectiveness" sections for strategies in Volume be ranked by crash frequency or total crash cost to identify 16: A Guide for Reducing Alcohol-Related Collisions indicates priority locations. The analyst would then correct for that estimates of AR crash reductions are possible for some of "treatment gaps" using the same logic provided in Proce- these treatments. (Indeed, it may also be possible to estimate dure 2A (see Section IV). If the crashes are not mileposted, the crash-related effectiveness of some of the strategies found but there is information available on jurisdiction and in Volume 2: A Guide for Addressing Collisions Involving Un- route, the analyst could link crashes to routes within the licensed Drivers and Drivers with Suspended or Revoked Li- jurisdiction and calculate the total crash cost or number of censes.) If those treatments for which effectiveness can be es- target crashes per mile by dividing the sum of the crash timated are being analyzed, the following procedure can be costs or the sum of the number of target crashes on that used. Additional estimates of reductions may result from fu- route by route length. Then rank the potential routes for ture research efforts. treatment based on this rate per mile. The analyst could then choose the routes to be treated based on the highest Data Needs rankings plus other technical and policy factors. The data needed for this procedure will be the same as de- Note again that the lack of treatment effectiveness data scribed in the modified Procedure 3 above data that will means that the analyst will not be able to verify whether or allow the analyst to (1) isolate crashes involving the specific not a specific set of implemented strategies can be expected to user population of interest (e.g., young drivers involved in al- meet the established crash-reduction goal. In these cases, the cohol-related crashes) and (2) define the specific crash types best that can be done is to proceed in selecting strategies and involving drivers in each subgroup of interest (Exhibit VII-4).

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65 Population Type Variable Crash Database Subfile Drivers Involved in Alcohol- Alcohol Involvement Crash Related Crashes Law Enforcement Suspect Person/Vehicle Alcohol Use Alcohol Test Person/Vehicle Violation Codes Person/Vehicle Young Drivers Involved in Driver Age Person/Occupant or Vehicle Alcohol-Related Crashes Driver Date of Birth Use "Driver Age" Repeat DUI Offenders The isolation of alcohol-related crashes involving repeat DUI Involved in Alcohol-Related offenders might require a usable "driver history file." See Crashes discussion above under Procedure 3 concerning how this might be accomplished. Exhibit VII-4. Crash variable and subfile location by population type for alcohol-related crashes. Additional data related to economic cost associated with dif- will be gained by this crash-type categorization. Here, the ferent crash types and program costs will be described below. crashes should be categorized using the 22 crash types shown in Crash Cost Estimates by Maximum Police- Reported Injury Severity Within Selected Crash Geometries Procedure (22). This categorization will allow calculation of the eco- 1. Specify the AR target groups of interest young nomic cost of these crashes in the steps below. Note that drivers, all drivers, repeat offenders. even greater precision can be gained by further catego- Note that some of the strategies in Volume 16 are only rizing each crash type by speed limit (i.e., 45 mph and appropriate for certain subgroups. It is suggested that lower vs. 50 mph and greater) and by crash severity (i.e., the analyst consider all three subgroups in the initial K+A, B+C, no injury), since crash cost estimates are analysis. provided for those breakdowns in the same reference. 2. Estimate the annual number of affectable AR crashes 4. Estimate the number of AR crashes that can be reduced for the target group or groups of interest. annually by each potential treatment. This can be done by defining group-specific crashes This will be done by multiplying the annual number of (e.g., AR crashes involving young drivers or all drivers) AR crashes for each subgroup by the estimated percent using the crash variables in the table above and analyzing reduction due to the treatment. These effectiveness esti- 3 to 5 years of crash data. Averaging over this longer time mates will be made by the user based on information period will provide a more stable estimate of annual found under the "Expected Effectiveness" section of the crashes. As noted in the discussion under Procedure 3 guide. If the crashes for each subgroup were further above, the difficulty will be in isolating AR crashes in- categorized by crash type (or crash type within speed volving repeat DUI offenders unless the crash file con- limit and injury categories), calculate the reductions for tains information on prior violations. Once identified, a each crash type in the same manner. crash-based file should be developed for each subgroup Care must be exercised in maintaining consistency in of interest (i.e., one analysis record per AR crash). the unit of analysis. If the effectiveness data and treat- As indicated in the Procedure 3 discussion above, an ments are in terms of drivers treated, the crash reduc- alternative to using the crash file might be an analysis of tions represent number of crashes per, say, 100 drivers DUI violation and crash data in the driver history file. treated. If the effectiveness data are in terms of percent- This would be particularly true if one is estimating ef- age of crashes reduced over some prior period or histor- fectible AR crashes for repeat offenders. As noted there, ical crash time series baseline, the net number of crashes this would only be possible if the driver history file (or a reduced can be computed directly. citation-tracking system) contains information on 5. Convert the crash reductions to "economic benefits." crashes that can be linked to specific DUI violations. If so, This will be done by multiplying each calculated crash multiple years of the driver history file could be used in frequency reduction from the previous step by the this analysis. appropriate crash cost from Council, et al. (22) 3. Categorize the AR crashes for each target group of 6. Calculate the total "economic benefit" for each interest into specific crash types. subgroup. This step can be omitted, using only total counts of If the analyst used only total counts of crashes for each crashes for each subgroup of AR drivers. However, much subgroup of AR drivers in Step 2 (and skipped Step 3), more precision in the economic estimates of crash costs then the total economic benefit will be calculated in Step