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

Chapter: Section VIII - Unsafe Driver Actions

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Suggested Citation:"Section VIII - Unsafe 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 VIII - Unsafe 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 VIII - Unsafe 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 VIII - Unsafe 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 VIII - Unsafe 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 VIII - Unsafe 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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68 Planning Programs Related to Reducing Crashes Involving Distracted and Fatigued Drivers and Unbelted Vehicle Occupants This section of the guide presents a strategy for selecting treatments to reduce crashes involving distracted and fa- tigued drivers and unbelted vehicle occupants. As noted ear- lier, 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 established a “stretch goal” as described in Section I. Four procedures 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 se- lected strategies – in other words, that the treatments have known CRFs or AMFs. However, in general, the two guides considered here identified strategies that do not completely meet this requirement even though many of the strategies are supported by compelling evidence of significant crash reduc- tion. The major exceptions to this situation are a subset of proposed strategies related to distracted and fatigued drivers, strategies related to improving the roadway to prevent lane departure, and intersection crashes involving these drivers. Some of these strategies could be analyzed using procedures 1, 2, and 2A since AMFs are known. The user is referred to Sections IV and V if analyzing those strategies with known ef- fectiveness. What is generally lacking for other strategies in these two guides 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. It should be noted that some strategies aimed at drowsy drivers are also beneficial for impaired drivers. For example, edgeline and centerline rumblestrips may help alert the drowsy driver and also may help keep impaired drivers from leaving their travel lane. The traffic engineer should use his or her judgment to determine which subset of crashes or driver population may be affected by each treatment application being considered. The benefits of a given treatment may be greater, and therefore worth more investment, when other target populations or crash types are also positively impacted. 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 re- duction effectiveness has not been established. Many of the treatments related to unsafe driver actions fall into this cate- gory, and that procedure will be presented below. 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: Guid- ance for Implementation of the AASHTO Strategic Highway Safety Plan. The specific volumes pertinent to this section on illegal driving acts are: • Volume 11: A Guide for Increasing Seatbelt Use (11) • Volume 14: A Guide for Reducing Crashes Involving Drowsy and Distracted Drivers (14) A link to these downloadable guides can be found in http://safety.transportation.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 and vehicle- S E C T I O N V I I I Unsafe Driver Actions

69 occupant-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 se- lecting treatment programs and establishing crash-reduction goals. The first relates to the data source and “ownership” of the treatment delivery system. In contrast to many of the highway countermeasures, most of the effectiveness measures for these driver and vehicle occupant strategies do not relate to crash rates on sections or type of roads. Instead, the safety concern usually relates more to overall crash rates, perhaps subdivided by severity. The data on which problem driver identification and effectiveness measurements are based (traffic convictions and crashes) usually reside in DMV files. The information on previous convictions may sometimes be added to crash files. It will also be noted that some of the strategies proposed in the guides could require the enactment of legislation, de- pending on the state in question. For example, increasing seat belt usage may require upgrading from secondary to primary enforcement legislation. Selection of a strategy requiring leg- islation entails an assessment of the likelihood that the legis- lation 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 approximations. Some general information on treatment cost is presented for each treatment in both of the guides, and that information should be reviewed by the user. Very costly strategies should be avoided unless supported 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 statisti- cally significant annual crash reductions as small as 5–10 percent over baseline. 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 designed 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). As noted earlier, if the user is considering roadway-related strategies for drowsy and distracted drivers described in the re- lated guide, and if the considered strategies have known effectiveness measures, then Procedures 1, 2A, and 2B in Sections IV and V should be used. The issue here will be defin- ing the proportion of all drivers involved in lane-departure crashes or intersection crashes who are drowsy and distracted. Some guidance on defining such drivers will be given under “Data Needs” below. For the remaining strategies which do not have known effectiveness (AMF) measures, the recom- mended method for choosing and targeting strategies is a modified version of Procedure 3 described in Section III. This procedure could be used for any of the unsafe driving strate- gies found in either of the two guides. Procedure 3 – Choosing Treatments and Target Subgroups Related To Unsafe Driving Actions When Treatment Effectiveness in Terms of Crash/Injury Reduction Is Unknown The assumption here is that, for the majority of the strate- gies, there is no known level of effectiveness – 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 an- alyst make an educated choice of which treatments will be most effective in his or her jurisdiction, and to help the ana- lyst 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 unsafe-driver subpopulations or jurisdictions are to be targeted). However, unlike road user populations covered in other guides (e.g., older drivers or pedestrians), the choice between alternative treatment strategies found in each of these two unsafe-driving guides is much less oriented to specific crash circumstances such as different crash types, crash location (except for the roadway-based strategies), and times of crash (except perhaps for drowsy drivers). Instead, most of the strategies are related to improvements in programs, such as increasing seatbelt usage. In addition, for both the guide re- lated to drowsy and distracted driving and the guide related to increasing seatbelt usage, the strategies are related to the full group of such drivers and vehicle occupants who under- take such unsafe actions. Some limited subpopulation- targeting is possible for the occupant restraint strategies (children vs. other occupants) and for the drowsy and dis- tracted driver strategies (i.e., teen drivers, adult drivers, and heavy truck drivers). Some additional targeting of a chosen strategy can occur based on jurisdiction and selected areas

within a jurisdiction. However, additional targeting based on crash types and other crash data are not generally applicable with these strategies. 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 esti- mates of the program effectiveness for different alternative treatments, but one that does not include further targeting steps based on crash circumstances. Data Needs Note that Procedure 3 is a “crash-based” procedure. It as- sumes that the analyst wishes to choose among the alternative 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 as- sessment of the existing programs in a jurisdiction, and choos- ing to implement those strategies which are either missing 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 and target treat- ments 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 fatigue-related crashes or crashes involving unbelted vehicle occupants), and (2) define crash types or crash characteristics (e.g., crashes involving unbelted occupants in specific age ranges) for this user pop- ulation 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 their crash file to identify variables that can be used in determining 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 (“vehicle”), and (3) variables for each occupant/person in the crash (“person” or “occupant”). The variables needed to de- termine 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 head- on and run-off-road crashes in general) 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 variables (or similar variables) listed in Exhibit VIII-1 will be used in this iden- tification of “target-populations.” Thus, the defining variables will depend on the user’s definition of fatigue-related crashes (e.g., late-night crash involvement with no indication of DUI, especially head-on or run-off-road crashes). Drivers involved in nighttime crashes, especially those who are not under the influence of alcohol, are a logical subpopulation to consider for fatigue involvement, although fatigue involvement can also clearly occur during other time periods as well, and treat- ments that help drowsy drivers may also help drivers who are under the influence of alcohol. Research on human circadian rhythms indicates that early afternoon is also a period when drowsiness is likely. Since there is no broadly accepted defi- nition of distracted driving crashes, defining specific crash types related to distracted driving may be difficult or impos- sible. Some crash files may include a variable on “distrac- tion.” Indeed, the MMUCC guidelines for crash variables include such variables (i.e., P16. “Driver Distracted By”). Narratives written by the investigating officer may include driver and witness reports and the officer’s own impressions about possible distractions or fatigue. While reading narra- tives on every crash report can be much more time-consum- ing than simply scanning for a coded “distraction” variable, these statements can provide a wealth of information on the 70 Population Type Variable Crash Database Subfile Drivers Involved in Fatigue- Related Crashes Fatigue Involvement Captured under “Driver Condition” (If Available) Person/Vehicle Alcohol Involvement Person/Vehicle/Crash Time of Day Crash Violation Codes Person/Vehicle Driver Action Prior to Crash Violation Indicated Contributing Circumstances Person (or Vehicle) Person (or Vehicle) Person (or Vehicle) Distracted Drivers Driver Distracted By Person Driver Condition Person/Vehicle Driver Action Prior to Crash Contributing Circumstances Person (or Vehicle) Person (or Vehicle) Unbelted Vehicle Occupants Seatbelt Usage Person Injury Severity Person/Vehicle Crash Type Crash Exhibit VIII-1. Crash variables and subfile location by population type.

71 circumstances surrounding the crash. It must be noted that “distraction” variables are very likely less reliable than other police collected variables since they must be based either on information provided by the driver (which can be self-serving) and/or on very difficult conclusions drawn by the investigat- ing police officer who was not on the scene or in the vehicle at the time of the crash. However, this may be the only data available, unless the user can define distraction/inattention in some alternative manner. Seatbelt usage for vehicle occu- pants can be based on data from the officer’s investigation of a crash. However, like distraction/inattention data, such data will not always be as accurate as we would hope because the officer has to base his/her judgments on after-crash observa- tions and occupant/witness statements. Some occupant state- ments may be untrue, particularly in states with mandatory belt usage laws. As noted above, some of the strategies described in these two guides are directed to specific driver/occupant ages and types of drivers. The roadway-related strategies noted for fatigued and distracted drivers can be targeted to specific roadway location if Procedures 1, 2A, and 2B are used, but are difficult to target under this modified Procedure 3. For this limited additional targeting, the names of crash variables and the specific codes needed to conduct these targeting analyses will vary from jurisdiction to jurisdiction. While not all rele- vant crash variables are presented here, Exhibit VIII-2 provides some guidance concerning where example variables related to some treatment strategies might be found. Procedure As described in Section III, Procedure 3 has two basic steps. First, choose the “best treatments” for the user population of interest (e.g., the treatments related to fatigue-related crashes or crashes involving unbelted vehicle occupants 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, where appropriate, choose the subgroups of users (e.g., young drivers or older drivers), highway loca- tions, 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 deter- mine 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 – drowsy driv- ers, distracted drivers, and unbelted vehicle occupants. 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 the table above. For each user population, the analyst could begin the process by Crash Type/Issue Variable Crash Database Subfile Driver Age Driver Age Person/Occupant or Vehicle Driver Date of Birth Person/Occupant or Vehicle Occupant Age (for Child Restraint Strategies) Occupant Age Person/Occupant Time of Crash Light Condition Hour of Day Crash Crash Vehicle Type (to Identify Large Truck Drivers) Vehicle Type Motor Vehicle Body Type Category Commercial Motor Vehicle Configuration Vehicle Vehicle 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 VIII-2. Crash variables and subfile location by crash type/issue.

analyzing 3 to 5 years of crash data to determine the fre- quency of each crash population – either total crashes or some subset (e.g., fatal and serious-injury crashes). How- ever, since the severity distribution 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 injury and no-injury crashes – a better solution is to weight each crash for a given user pop- ulation by an economic cost based on its severity, and then accumulate the total cost of crashes for each population. Information on economic cost per crash severity level can be found in Crash Cost Estimates by Maximum Police-Re- ported 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 sec- tions, the analyst will use the basic cost per crash catego- rized by police-reported severity level (i.e., K,A,B,C,O). Exhibit VIII-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 provide the analyst with overall infor- mation on which of these three unsafe driver/occupant populations is most important in his/her jurisdiction. If only one of the unsafe driver/occupant populations is being examined, the analysis can provide useful data for public information programs concerning the economic cost of such crashes. 2. Prioritize the specific 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. Some strategies in each of the two guides can be applied to all drivers or occupants, and thus all crashes involving the population of illegal drivers are treatable. However, certain strategies in each of these two guides are only applicable to certain user subgroups (e.g., child vs. adult restraint strategies or fatigue strategies for passenger car drivers vs. heavy truck drivers). In order to analyze the possible benefit of these strategies, crashes in- volving only the applicable subpopulations must be iden- tified and analyzed. Here, just as in Step 1, the prioritiza- tion of subpopulations can be based on the frequency and severity of the specific types of user-subpopulation crashes occurring in an analyst’s jurisdiction. Crashes specific to a given user-subpopulation can be defined using variables in the table above (e.g., occupant age for child restraint programs or vehicle type for heavy-truck driver pro- grams). For each user subpopulation, the analyst could analyze 3 to 5 years of crash data to determine the fre- quency of each crash population. Again, either total crashes or some subset (e.g., fatal and serious-injury crashes) could be used, but the economic cost of crashes is a better measure since crash severity may differ. The same cost figures presented above could be used. Note that using these crash costs to develop the eco- nomic harm of crashes involving unbelted children will likely result in conservative estimates of that economic cost. These cost-per-crash estimates in Council, et al. (22) were based on standardized populations of vehicle occu- pants by age and belt usage. Components of these costs re- lated to lost wages and other factors would be greater for fatally injured children than for older populations. How- ever, it is felt that even though perhaps conservative, they are suitable for this use. 3. Identify possible treatments for use for each high-priority unsafe driver group. The analyst will then review the pertinent NCHRP Re- port 500 guides and list treatments that would be most ap- propriate for each of the high-priority unsafe 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. The judgment will be somewhat easier for the strategies in these two guides since there is some information available on estimated 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 deci- sion on which treatment(s) to implement – the cost of the treatment and other technical and policy considerations. Unfortunately, there are no good guidelines for how to 72 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 Cost in 2001 dollars Exhibit VIII-3. Crash cost by crash severity and posted speed limit (22).

73 “weight” the different factors. While problem size (total crash cost) and assumed treatment effectiveness are key fac- tors, there may be technical, policy, and cost considerations that will remove certain treatments from consideration even if they are felt to be effective. The analyst will have to choose the final treatments based on best judgment. The procedure outlined above will at least ensure that the major factors in the decision are clearly defined. The output of this step will be one or more chosen treatments, with the nature of the treatment defining the specific crash types more likely to be affected. The roadway-oriented treatments for drowsy and distracted drivers (e.g., shoulder and centerline rumble strips) are also included in the NCHRP Report 500 guides discussed in Section IV of this guide and are best addressed with the procedures presented there. 6. Target the chosen treatments to the user populations where the problem is found. 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. Mileposted crash data could be used as discussed in Section III for Procedure 2A to target specific roadways for enforcement related to fatigued drivers. However, for enforcement re- lated to unbelted occupants, targeting of communities identified from crash data as having the most crashes involving unbelted occupants (per person, per road mile, or per vehicle-mile of travel) may provide the best targeting method. Crash data may also be useful in targeting specific age groups that are being injured as unbelted occupants. Targeting information might also be extracted from obser- vational seatbelt use studies done within specific states. 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 if a sound eval- uation is conducted after its implementation. Where quantitative estimates or approximations of effec- tiveness can be made for treatments aimed at distracted or fatigued drivers, it may be possible to provide estimates of net impact (number of crashes prevented) by multiplying the unit treatment effects by the number of drivers or roadway segments treated. Since passenger restraint strategies will not prevent crashes, and because it is difficult to estimate the increase in belt use as a result of any specific program or to translate that increase into a well-defined reduction in injury severity, providing estimates of net impacts for these treat- ments is more difficult. Seatbelt strategies are most effective in communities and among populations where usage rates are the lowest and there is the greatest room for improve- ment. And because the proper use of restraint systems is so effective at reducing injury level in crashes, it is important to continue to develop and implement effective programs aimed at increasing restraint use in these communities and among these populations. Closure Choosing treatments and targeting those treatments to the unsafe driving populations covered in this section are difficult. The programs are complex, there is limited crash-based infor- mation on treatment effectiveness for the strategies covered in the two 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. Because programs aimed at these targeted populations are much more focused on driver behavior, they often deal with educational and enforcement-related programs more than traditional engi- neering treatments. The application of these types of programs is usually more flexible in nature and costs for implementation can be more easily adapted to a budget of any size. It is hoped that the procedures presented in this section at least provide some insight into how budgetary choices can be made.

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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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