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Safety Data and Analysis in Developing Emphasis Area Plans (2008)

Chapter: Section VII - Illegal Driver Actions

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Suggested Citation:"Section VII - Illegal Driver Actions." National Academies of Sciences, Engineering, and Medicine. 2008. Safety Data and Analysis in Developing Emphasis Area Plans. Washington, DC: The National Academies Press. doi: 10.17226/14170.
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Suggested Citation:"Section VII - Illegal Driver Actions." National Academies of Sciences, Engineering, and Medicine. 2008. Safety Data and Analysis in Developing Emphasis Area Plans. Washington, DC: The National Academies Press. doi: 10.17226/14170.
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Suggested Citation:"Section VII - Illegal Driver Actions." National Academies of Sciences, Engineering, and Medicine. 2008. Safety Data and Analysis in Developing Emphasis Area Plans. Washington, DC: The National Academies Press. doi: 10.17226/14170.
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Suggested Citation:"Section VII - Illegal Driver Actions." National Academies of Sciences, Engineering, and Medicine. 2008. Safety Data and Analysis in Developing Emphasis Area Plans. Washington, DC: The National Academies Press. doi: 10.17226/14170.
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Suggested Citation:"Section VII - Illegal Driver Actions." National Academies of Sciences, Engineering, and Medicine. 2008. Safety Data and Analysis in Developing Emphasis Area Plans. Washington, DC: The National Academies Press. doi: 10.17226/14170.
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Suggested Citation:"Section VII - Illegal Driver Actions." National Academies of Sciences, Engineering, and Medicine. 2008. Safety Data and Analysis in Developing Emphasis Area Plans. Washington, DC: The National Academies Press. doi: 10.17226/14170.
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Suggested Citation:"Section VII - Illegal Driver Actions." National Academies of Sciences, Engineering, and Medicine. 2008. Safety Data and Analysis in Developing Emphasis Area Plans. Washington, DC: The National Academies Press. doi: 10.17226/14170.
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Suggested Citation:"Section VII - Illegal Driver Actions." National Academies of Sciences, Engineering, and Medicine. 2008. Safety Data and Analysis in Developing Emphasis Area Plans. Washington, DC: The National Academies Press. doi: 10.17226/14170.
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Suggested Citation:"Section VII - Illegal Driver Actions." National Academies of Sciences, Engineering, and Medicine. 2008. Safety Data and Analysis in Developing Emphasis Area Plans. Washington, DC: The National Academies Press. doi: 10.17226/14170.
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59 Planning Programs Related to Reducing Crashes Involving Aggressive Drivers, Alcohol-Impaired Drivers, and Unlicensed or Suspended/Revoked Drivers This section of the guide presents a strategy for selecting treatment programs that offer maximum potential in reduc- ing crashes involving aggressive drivers, drinking drivers, unlicensed drivers, and drivers with a suspended or revoked driver’s license (S/R drivers). As noted earlier, it is assumed that a safety planning team has selected one or more of the above emphasis areas as part of its safety plan and has estab- lished a “stretch goal” as described in Section I. Four proce- dures for choosing treatment strategies and target groups were described in Section III of this guide. Three of these procedures require known estimates of effectiveness (crash reduction and benefit-costs) for some or all of the selected strategies – in other words, that the treatments have known CRFs or AMFs. However, none of the guides considered here identified strategies that completely met this requirement even though many of the strategies are supported by com- pelling evidence of significant crash reduction. What is generally lacking are precise estimates of the magnitude of the crash reduction that could be used in the development of an estimated B/C ratio. The latter, in turn, also requires known estimates of treatment costs and effects on crash severity, which are often lacking. Thus, we know in some cases that the treatment reduces crashes but not by how much or in terms of net cost-benefits. Procedure 3, as described in Section III, outlined an ap- proach for selecting strategies in the absence of known crash effectiveness estimates (AMFs or CRFs) and B/C ratios. This procedure is designed for use with treatments where crash reduction effectiveness has not been established. Many of the treatments related to illegal driving fall into this category, and that procedure will be presented below. Two additional treatment-choice procedures will be presented for treatments related to drinking drivers. The safety planning team is strongly urged to carefully review the material in each of the pertinent guides before beginning the planning process. These user-population- oriented guides are found within NCHRP Report 500: Guidance for Implementation of the AASHTO Strategic Highway Safety Plan. The specific volumes pertinent to this section on illegal driving acts are: • Volume 1: A Guide for Addressing Aggressive-Driving Colli- sions. (1) • Volume 2: A Guide for Addressing Collisions Involving Unlicensed Drivers and Drivers with Suspended or Revoked Li- censes. (2) • Volume 16: A Guide for Reducing Alcohol-Related Colli- sions. (16) A link to these downloadable guides can be found in http://safety.transpportation.org/guides.aspx. The planning team is also encouraged to review NCHRP Report 501 (18) for a detailed description of an integrated problem identification and safety planning process. General Strategic Considerations As noted earlier, data for estimating precise AMFs, CRFs and B/C ratios for many of the driver-oriented strategies do not exist. There are also some other differences between highway-oriented strategies and driver-oriented strategies that need to be recognized in selecting treatment programs and establishing crash-reduction goals. The first relates to the data source and “ownership” of the treatment delivery sys- tem. In contrast to many of the highway countermeasures, most of the effectiveness measures for these driver strategies do not relate to crash rates on sections or type of roads. In- stead, the safety concern usually relates more to overall crash S E C T I O N V I I Illegal Driver Actions

rates, perhaps subdivided by severity. The data on which problem driver identification and effectiveness measure- ments are based (traffic convictions and crashes) usually re- side in DMV files. These data may sometimes be added to the state crash file. It will also be noted that many of the strategies proposed in the guide could require the enactment of legislation, depend- ing on the state in question. Selection of a strategy requiring legislation entails an assessment of the likelihood that the leg- islation could be enacted in the required time-frame. Another consideration is cost. An assessment of cost for many of the proposed strategies will require subjective approx- imations. Some general information on treatment cost is presented for each treatment in each of the three guides (Vol- umes 1, 2, and 16), and that information should be reviewed by the user. Very costly strategies should be avoided unless sup- ported by proven effectiveness data and an estimated effect size that is sufficient in economic terms (dollar benefits) to be cost- beneficial or cost-effective. Strategies that are judged to have negligible or moderate operational costs (excluding start-up) will usually be cost-beneficial if they produce statistically signif- icant annual crash reductions as small as 5–10 percent over baseline. It is also possible to make statutory sanctions such as ignition interlock, vehicle impoundment, and license suspen- sion self-supporting through administrative fees and fines. The guides classify strategies into three categories: 1. Proven 2. Tried but not proven 3. Experimental – not tried, effectiveness unknown. In selecting treatment strategies, priority should be given to strategies rated as proven. However, the safety planning team is encouraged to use their own judgment and to inde- pendently review the evidence cited in the guides in selecting treatments. The tried category includes those treatments that have been used by agencies (in some cases used often), where there is little possibility of negative impacts on crash/injury frequency, and where there is an expectation (but not scien- tific proof) that the effect of the treatment on safety is likely to be a positive one. The evidence could include poorly de- signed or executed crash/injury evaluations and indirect or surrogate measures that may be related to safety (e.g., behav- ioral changes that may be related to crash/injury reduction). The following sections present three methods for choosing and targeting strategies. The first is a modified version of Pro- cedure 3 described in Section III, which is usable when treat- ment effectiveness (AMF) is unknown. This procedure could be used for any of the illegal-driving strategies found in any of the three guides. The second procedure is a modification of the economic analysis procedures found in Procedures 1, 2A and 2B. It is primarily directed to strategies in the Volume 16 guide concerning alcohol-related (AR) crashes, since ef- fectiveness levels (AMFs) are either given or can be estimated for some of the AR strategies. However, this procedure could also be used for other operator-related strategies if effective- ness is known or becomes known in the future. The third procedure is specific to AR strategies, and is based on advice given in the Volume 16 guide. Although most of the proposed treatment strategies do not have precise AMFs, a substantial number of the strategies in Volumes 2 and 16 are supported by compelling evidence concerning their efficacy and effectiveness. This is not true for aggressive driving countermeasures (Volume 1). Those who implement strategies for reducing aggressive driving must also contend with definitional ambiguity and the absence of a database for identifying such drivers and initiating appro- priate sanctions. These limitations will necessitate use of sub- jective judgment and indirect methods. Procedure 3 – Choosing Treatments and Target Subgroups Related To Illegal Driving Actions When Treatment Effectiveness in Terms of Crash/Injury Reduction Is Unknown The assumption here is that there is no known level of ef- fectiveness for the treatment strategies of interest – no defined CRFs or AMFs. Thus, economic analyses like those that are the basis for Procedures 1, 2A and 2B, and 4 are not possible for these treatments. Procedure 3 is aimed at helping the analyst make an educated choice of which treatments will be most effective in his or her jurisdiction, and to help the analyst develop a targeting strategy for the treatment in cases where it is not to be applied jurisdiction-wide or to the “total problem” (e.g., where specific illegal-driver subpopulations or jurisdictions are to be targeted). However, unlike road user populations covered in other guides (e.g., older drivers, pedestrians), the choice between alternative treatment strategies found in each of these three illegal-driving guides is much less oriented to specific crash circumstances (e.g., different crash types, times of crash, crash location types, etc.). Instead, most of the strategies are related to improvements in programs, such as impounding vehicles of repeat offenders. In addition, for both the guide related to aggressive driving and the guide related to unli- censed, suspended, or revoked drivers, the strategies are related to the full group of such illegal drivers. Thus, while targeting of a chosen strategy can occur based on jurisdiction and selected areas within a jurisdiction, it is not apparent how crash data could be used to further target the strategies. AR crash strategies presented are essentially oriented to three dif- ferent groups of drivers – young drivers in AR crashes, all drivers in AR crashes, and repeat DUI offenders in AR 60

crashes. Examination of crash data can provide the analyst with information concerning which of these subgroups are producing the largest AR problem in a given jurisdiction, but virtually none of the strategies within each of the three sub- groups are susceptible to further targeting. For these reasons, the general analysis methods presented under Procedure 3 in other sections of this manual are not as applicable here. For that reason, only a modified Procedure 3 is presented below – one which continues to use relative estimates of the program effectiveness for different alternative treatments, but one that does not include further targeting steps. Data Needs Note that Procedure 3 is a “crash-based” procedure. It assumes that the analyst wishes to choose among the alterna- tive strategies and target the treatments based on crash data. It is noted that an alternative way of making such choices is through linking crash data related to problem size to an assessment of the existing programs in a jurisdiction, and choosing to implement those strategies which are either miss- ing from the current program or have the least extensive (or least effective) degree of implementation. This program- deficiency procedure is described more fully in a later section. However, if the analyst wishes to choose treatments and targets based on crash data, the revised Procedure 3 described here basically requires crash data that will allow the analyst to (1) isolate crashes involving the specific user population of interest (e.g., drivers involved in alcohol-related crashes) and (2) define crash types or crash characteristics (e.g., AR crashes involving young drivers) for this user population which would suggest strategies and target subgroups. To isolate crashes involving the population of interest, the analyst will need to examine the data formats/coding in her/his crash files to identify variables that can be used in de- termining whether or not a given crash is a “target-population crash.” Crash databases often categorize data for a given crash into up to three subfiles – (1) general accident/crash variables (“crash”), (2) variables for each vehicle in the crash (“vehi- cle”), and (3) variables for each occupant/person in the crash (“person” or “occupant”). The variables needed to determine whether a crash is a “target-population crash” are usually found in the occupant/person subfile, but could also be found in the general crash subfile (e.g., a “flag” for all alcohol-related crashes) or “vehicle” subfile (e.g., driver information included with each vehicle record). In short, crash files differ from jurisdiction to jurisdiction. While certainly not always the case, the following variables (or similar variables) listed in Exhibit VII-1 will be used in this identification of “target populations.” Note that while such definition is possible from both drivers in AR crashes and drivers with suspended/ revoked licenses, there is no clear definition of “aggressive drivers.” Thus, the defining variables will depend on the user’s definition (e.g., speeding well above average traffic speed, multiple violations at the same time, etc.). Finally, note that identifying alcohol-related crashes involving repeat DUI offenders will be much more difficult since this group is not identified by any combination of vari- ables in the crash file. More information on defining crashes for this group using a “driver history file” is included below. As noted above, since the strategies described in these three guides are generally applicable to all aggressive or illegal driv- ers, or to subsets of drivers by age, they do not lend themselves to a great degree of additional targeting in many cases. AR strategies could be chosen based on driver age (e.g., strategies of young drivers in AR crashes vs. strategies for all AR crashes). Some of the strategies in Volume 1, the Aggressive Driving Guide (e.g., “Targeted Enforcement”), and Volume 16, the AR Guide (e.g., DUI checkpoints), could be targeted to high- priority locations or high-priority times of day based on crash occurrence. (They could also be targeted based on citation data that includes location of the offense, assuming that such enforcement is somewhat “random” across the jurisdiction.) The names of crash variables and the specific codes needed to conduct these targeting analyses will vary from jurisdiction to jurisdiction. While not all relevant crash variables are 61 Population Type Variable Crash Database Subfile Drivers Involved in Alcohol- Related Crashes Alcohol Involvement Crash Law Enforcement Suspect Alcohol Use Person/Vehicle Alcohol Test Person/Vehicle Violation Codes Person/Vehicle Drivers with Suspended/Revoked Licenses Driver License Jurisdiction Person/Vehicle Driver License Class Person/Vehicle Driver License Status Person/Vehicle Violation Codes Person/Vehicle Aggressive Drivers (Depends On User Definition of Aggressive Driving) Exhibit VII-1. Crash variables and subfile location by population type.

presented here, Exhibit VII-2 provides some guidance con- cerning where example variables related to some treatment strategies might be found. Procedure As described in Section 3, Procedure 3 has two basic steps. First, choose the best treatments for the user population of in- terest (e.g., the treatments related to AR crashes most likely to be applicable in a given jurisdiction) from among the set of all treatments presented in the applicable NCHRP Report 500 guides. Second, choose the subgroups of users (e.g., young AR or aggressive drivers), highway locations, or times of day to which the selected treatments should be applied. As described earlier in more detail, the choice of the “best treatments” from the listing of many potential user-population treatments can be based on the following factors: a) The potential treatment judged to be the most effective, even given that effectiveness is unknown b) The relative magnitude of the crash types and severity levels that the treatment will affect c) The cost of the potential treatments (either jurisdiction- wide or per-mile or per-location) d) Other technical or policy considerations These factors must be combined in some fashion to decide which treatment to choose. While there are multiple ways of making this choice, the following represents one such procedure. 1. Prioritize the specific user-population problem(s) to be addressed. An initial issue may be whether to treat one, two or all three of the groups covered in these guides – aggressive drivers, drivers involved in AR crashes, and/or unlicensed and S/R drivers. This decision can be based on the frequency and severity of the specific types of user- population crashes occurring in an analyst’s jurisdiction. Crashes specific to a given user-population were defined in Exhibit VII-1. For each user population, the analyst could begin the process by analyzing 3 to 5 years of crash data to determine the frequency of each crash popula- tion – either total crashes or some subset (e.g., fatal and serious-injury crashes). However, since the severity distri- bution may differ between some populations, and since restricting the analysis to only fatal and serious-injury crashes will severely limit the crash sample and will omit a large component of the crash problem – non-serious in- jury and no-injury crashes – a better solution is to weight each crash for a given user population by an economic cost based on its severity, and then accumulate the total crash cost for each population. Information on economic cost per crash-severity level can be found in Crash Cost Esti- mates by Maximum Police-Reported Injury Severity Within Selected Crash Geometries (22). Here, instead of using severity cost by crash type as is done in roadway-program analyses covered in earlier sections, the analyst will use the basic cost per crash categorized by police-reported crash- severity level (i.e., K,A,B,C,O). Exhibit VII-3 below presents those costs per crash. Costs for combinations of crash severity levels (e.g., K+A crashes) are presented in that report (22). This analysis of total crash cost will pro- vide the analyst with overall information on which of these three illegal driver populations is most important in his/her jurisdiction. If only one of the illegal driver popu- lations is being examined, the analysis can provide useful data for public information programs concerning the total cost of such crashes. 2. Prioritize the specific alcohol-related subpopulations to be addressed. Once one or more populations are identified, the sec- ond step involves the identification of subgroups in most need of treatment. In general, the strategies in the guides 62 Crash Type/Issue Variable Crash Database Subfile Driver Age Driver Age Person/Occupant or Vehicle Driver Date of Birth Person/Occupant or Vehicle Time of Crash Light Condition Hour of Day Crash Crash Speed-Related Crashes (for Aggressive Driving) Driver Action Prior to Crash Violation Indicated Contributing Circumstances Person (or Vehicle) Person (or Vehicle) Person (or Vehicle) Crash Location (for Targeting Treatments) County City Route Milepost Longitude/Latitude Block Address Crash Crash Crash Crash Crash Crash Speed Limit (for Use in Developing Cost per Crash) Speed Limit Crash Exhibit VII-2. Crash variables and subfile location by crash type/issue.

for aggressive and unlicensed/suspended drivers are aimed at the entire population of such drivers. However, the strategies in the AR guide are essentially oriented to three different groups of illegal drivers – young drivers in AR crashes, all drivers in AR crashes, and repeat DUI offend- ers in AR crashes. The problem size (or total crash cost) for the first two groups can be calculated using the proce- dures in the above paragraph in combination with the “Driver Age” variable in the crash file. However, the isola- tion of alcohol-related crashes involving repeat DUI offenders will be much more difficult unless this group is identified by variables in the crash file. In a limited num- ber of crash files, information will be added concerning whether a crash-related AR citation is the “first” or a “sub- sequent” offense. Those AR crashes coded as having a “subsequent” AR citation would be the target crashes. However, if this information is not available, then the an- alyst will have to rely on other data sources. If the analyst has a usable “driver history file” (see Section II) and if that file includes information on crashes (in addition to con- victions), then he/she could use those data to estimate the number of crashes related to repeat offenders. (Note that the crashes counted should occur after or at the same time as the second or subsequent DUI offense.) If that driver- history file does not contain AR crash information, then the process will be much more difficult. The analyst will have to use the driver-history file to identify the popula- tion of repeat offenders based on the number of past AR convictions. This group would then have to be matched to the crash files for the time period under examination (say, by driver license number, which is usually found on both files), and specifically to crashes that occur either after or at the same time as the second or subsequent AR offense. The identified crashes would then have to be further screened to determine which are alcohol-related before the estimate could be made. Finally, if the state has a cita- tion tracking system that includes information on crash occurrence in conjunction with an AR citation, this could provide the needed crash-related counts. If the number of repeat-offender crashes cannot be calculated, then the an- alyst could not use this modified Procedure 3 to choose between AR groups, but could use the program-deficiency procedure described following this procedure later in this section to make AR treatment choices. Note that the number of crashes involving a repeat of- fender will almost always be a very small part of all AR crashes in any jurisdiction. Thus, if the choice of AR strategies is to be based primarily on the size (or economic harm) of the crash problem, the AR strategies related to total AR crashes or AR crashes involving young drivers will always be the choice. However, calculating the num- ber of repeat-offender crashes when possible will provide the analyst (and the public) with solid information on the relative size of that part of the AR crash problem. 3. Identify possible treatments for use for each high-priority illegal driver group. The analyst will then review the pertinent NCHRP Re- port 500 series guides and list treatments that would be most appropriate for each of the high-priority illegal driver groups identified in the above step. The choice should be limited to those treatment strategies that are classified as proven or tried in the guides. 4. Rate the possible treatments based on estimated effectiveness. Since this procedure deals with treatment strategies with unknown effectiveness, this appears to be impossible. However, for a given set of possible treatments for a par- ticular user group, it may be possible to make a judgment concerning which treatment strategy would be expected to be most effective. This judgment will be most difficult for the aggressive-driver strategies, where there is essentially no information on crash-related effectiveness. The judg- ment will be somewhat easier for the strategies in the other two guides since they contain some information on esti- mated effectiveness for some of the strategies. 5. Choose best treatment(s) by considering estimated effectiveness, cost and other technical and policy considerations. The analyst will then combine the output of the steps above with at least two other factors in making a final de- cision on which treatment(s) to implement – the cost of the treatment and other technical and policy considera- tions. Unfortunately, there are no good guidelines for how to “weight” the different factors. While problem size (total crash cost) and assumed treatment effectiveness are key factors, there may be technical, policy, and cost consider- ations that will remove certain treatments from consider- ation even if they are felt to be effective. The analyst will have to choose the final treatments based on best judg- ment. The procedure outlined above will at least ensure that the major factors in the decision are clearly defined. 63 Crash Severity Speed Limit Category Comprehensive Cost/Crash* < 45 mph $3,622,200 Fatal (K) > 50 mph $4,107,600 < 45 mph $195,700 Serious injury (A) > 50 mph $222,300 < 45 mph $62,200 Moderate injury (B) > 50 mph $91,600 < 45 mph $40,100 Minor injury (C) > 50 mph $49,500 < 45 mph $7,000 No injury (O) > 50 mph $7,800 * Crash Costs in 2001 dollars Exhibit VII-3. Crash cost by crash severity level and posted speed limit (22).

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

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

5, and this step may be skipped. If the analyst has used in- dividual crash types (or crash types by severity and speed limit) in the above steps, those individual estimates within each subgroup must be summed to calculate the total economic benefit for each subgroup. 7. Define the annual cost for treating all drivers in each subgroup. This will be an estimate of total program cost for each treatment under study and for each subgroup being considered. This assessment will require subjective ap- proximations. Some general information on treatment cost is presented for each treatment in the guide, and that information should be reviewed by the user. Depending on the treatment, this cost may include start-up cost and cost per driver (i.e., all drivers that would need to be treated without knowing who will subsequently be in- volved in an AR crash). For other treatments, this may simply be an annual cost (e.g., for public information programs). Note that the total cost over the expected life of the project will need to be amortized to an “annual cost” basis, since the benefit calculations are in annual numbers [see NCHRP Report 501 (18)]. 8. Calculate “net benefits” for each treatment by subtracting cost from benefits. 9. Choose the treatments (and thus treatment subgroups) with the greatest net benefit. 10. Decide whether to use multiple treatments. After reviewing the prioritized listing of treatments and estimated costs, the analyst may decide to further de- termine whether multiple treatments would be beneficial. If the treatment combinations being considered affect dif- ferent driver subgroups (e.g., one affects young AR driv- ers while the second affects [older] multiple offenders), then the net benefit of that combination will be the sum of the individual calculations from Step 8. However, this is not usually the case. Multiple treatment combinations will often affect the same subgroup even if they are aimed at different subgroups. In this case, Steps 2–8 will need to be repeated for each combination under study. Thus the potentially affected driver groups will be specified first, then the AR crashes will be calculated, etc. Note, however, that one cannot expect that two treat- ments with estimated levels of effectiveness A% and B% will produce a reduction of A% + B% if applied to the same driver group. The combined effect would be ex- pected to be less. Unfortunately, since we do not have good data on the effectiveness of individual treatments, we have even less knowledge about the effectiveness of combined treatments. In the absence of such knowledge, it is suggested that the effectiveness level of the second treatment applied to a given driver subgroup be reduced to 50 percent of the level originally estimated for that treatment, and the effectiveness of the third treatment applied to the same driver subgroup be reduced to 25 percent of the original level. (Assume that any addi- tional treatments after the third will have no additional effect.) For example, assume that the first treatment for a given AR subgroup has an effectiveness level of 20 per- cent, the second has an effectiveness level of 15 percent, and the third has an effectiveness level of 10 percent. The estimated combined effectiveness of the three treatments applied to the same segment would be 20% + 15% (.5) + 10% (.25) = 30%. Again, this is only an estimate of the true combined effectiveness at best. Alternative Procedure – Choosing Treatments and Target Subgroups for Alcohol-Related Crash Strategies Based On Existing DWI Program Needs The above two procedures for choosing treatments and subgroups have been based on the size of the alcohol-related crash problem among different target subgroups of drivers and, in the second procedure, on estimated treatment effec- tiveness. Both are based on crash data, which make them the recommended procedures to follow. However, in the absence of crash data, a third alternative procedure that is advocated in Volume 1, the AR Guide, is to conduct a careful assessment of the nature of the jurisdiction’s drinking-driving problem and how the DWI countermeasure system is currently functioning. The choice of AR treatment strategies from those listed in the guide (and thus the choice of target subgroups) would be based primarily on “current AR program needs” – strategies that are not currently being implemented, or whose imple- mentation can be significantly improved. This assessment of current program needs requires a multidisciplinary team, since the system for dealing with alcohol-impaired driving may be the most complex and involve the greatest number of disciplines and state agencies of any traffic safety issue. States frequently use a task force that represents all the key elements of this system. Without such an approach, a fragmented and incomplete understanding of the problem is likely and progress will be difficult. The National Highway Traffic Safety Administration (NHTSA) works with highway safety offices within states to facilitate such an assessment procedure using outside experts. A brief description of NHTSA’s program assessment process can be found at http://www.nhtsa.dot.gov. A more detailed description of this process for impaired driving and recent findings from such assessments can be found at http://www. nhtsa.dot.gov/cars/rules/regrev/evaluate/809815/index.html. Finally, it is strongly recommended that the findings of an assessment of program needs be combined with crash-based information on the size of the AR problem attributable to 66

each of the three subgroups of AR drivers (i.e., young AR drivers, all AR drivers, and repeat offenders) using the analy- ses defined in Step 1 of Procedure 3 above. This would provide information on not only which program compo- nents need strengthening, but also the size of the AR crash problem that might be affected by different improvements. The above approach could also be applied to the unli- censed/suspended/revoked driver problem. A large percentage of suspended/revoked drivers have been suspended or revoked for driving under the influence and there is considerable overlap in the proposed treatment strategies. Closure Choosing treatments and targeting those treatments to the three illegal driving populations covered in this section is dif- ficult. The programs are complex, there is limited crash-based information on treatment effectiveness for the strategies cov- ered in the three guides, and there is limited information on program costs. However, choices have to be made given that available budgets will always be limited to some degree. It is hoped that the procedures presented in this section at least provide some insight into how such choices can be made. 67

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TRB's National Cooperative Highway Research Program (NCHRP) Report 500, Vol. 21: Guidance for Implementation of the AASHTO Strategic Highway Safety Plan: Safety Data and Analysis in Developing Emphasis Area Plans provides guidance on data sources and analysis techniques that may be employed to assist agencies in allocating safety funds.

In 1998, the American Association of State Highway and Transportation Officials (AASHTO) approved its Strategic Highway Safety Plan, which was developed by the AASHTO Standing Committee for Highway Traffic Safety with the assistance of the Federal Highway Administration, the National Highway Traffic Safety Administration, and the Transportation Research Board Committee on Transportation Safety Management. The plan includes strategies in 22 key emphasis areas that affect highway safety. The plan's goal is to reduce the annual number of highway deaths by 5,000 to 7,000. Each of the 22 emphasis areas includes strategies and an outline of what is needed to implement each strategy.

Over the next few years the National Cooperative Highway Research Program (NCHRP) will be developing a series of guides, several of which are already available, to assist state and local agencies in reducing injuries and fatalities in targeted areas. The guides correspond to the emphasis areas outlined in the AASHTO Strategic Highway Safety Plan. Each guide includes a brief introduction, a general description of the problem, the strategies/countermeasures to address the problem, and a model implementation process.

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