Emphasis Areas specify significant safety concerns identified using data about vehicles, persons and infrastructure associated with crash data and other relevant information. An Emphasis Area may also be thought of as a targeted crash type that the jurisdiction seeks to reduce through some program or strategy. Emphasis Areas are typically crash types that occur in larger numbers, result in serious injuries and deaths, and show potential for reductions. Identifying Emphasis Areas is an important part of developing and monitoring a Vision Zero or similar plan. Examples of Emphasis Areas are:
Single-vehicle run-off-road crashes on rural roads
Vehicle-pedestrian crashes at signalized intersections
Crashes involving an alcohol-impaired driver
Crashes involving novice drivers
Defining Emphasis Areas leads to the formulation of objectives, strategies and specific activities to achieve crash reductions. As the first step in this process, defining Emphasis Areas is critical to successful outcomes and maximizing safety improvements for dollars spent in the community.
Without a formal process based on data, Emphasis Areas may be selected based on incorrect perceptions or personal biases and select target crash types for which achieving reductions may prove difficult. Without a factual basis, decisions can be expected to be based on political or other considerations. For example, red-light running crashes in a community may be in the news following a high-profile incident but the reality may be that these crashes are rare and the potential for achieving crash reductions is very small. Selecting this crash type as an Emphasis Area would divert attention and funding from other crash types where the potential for reductions is much greater.
Defining Emphasis Areas using a data driven, evidence-based approach also allows for subsequent monitoring and evaluation to determine whether implemented strategies and activities are successful in reducing crashes and are cost effective.
Emphasis Areas can be defined using simple or more sophisticated methods. In simple terms, defining Emphasis Areas involves categorizing relevant data, primarily crash data, into different subsets and looking for crash characteristics that are over-represented. For example, fatal and serious injury crashes could be grouped by type of crash (i.e., single-vehicle run-off-road, vehicle-pedestrian), and analyzed to identify which group has the largest number of crashes.
One way to do this visually is by creating graphs showing the frequency of variables of interest. A group that appears overrepresented can then be further subcategorized to more specifically define the Emphasis Area. For example, vehicle-pedestrian crashes may be identified as an Emphasis Area based on a high number of such crashes. As a next step, vehicle-pedestrian crashes may be further grouped by type of roadway (i.e., two-lane undivided, four-lane undivided, six-lane undivided) and the number of crashes in these subgroups examined. This may reveal that four-lane undivided roads appear over-represented compared to other roadway types. As a further step, vehicle-pedestrian crashes on four-lane undivided roads could be grouped by whether they occurred mid-block, at signalized intersections or at unsignalized intersections, and so on. At each step an analyst refines potential Emphasis Area until it is defined.
Another visual method is a crash tree diagram. Crash tree diagrams present the number and percentage of crashes by the characteristics of interest. As an illustration, consider the fictional crash tree diagram below. The analyst is looking at crashes on rural two-lane roads and there are 5,000 such crashes. At the second level of the diagram crashes are grouped by crash type. We can see that run-off-road crashes dominate, making up 60% of the total and no other crash type is greater than 20%. At this point the analyst decides that run-off-road crashes are the crash type that needs attention. In the next step, all run-off-road crashes are grouped by whether the vehicle left the roadway on the left or right-hand side. The numbers show that 80% of such crashes left the roadway on the right side. Since most are leaving on the right-hand side, shoulder rumble strips could be an appropriate countermeasure. At the next level, run-off-road right crashes are grouped by whether they occurred on a tangent or horizontal curve. Naturally, there are more of these crashes occurring on tangents because curves make up a small proportion of the roadway. For illustration, assume there is 10,000 km of rural two-lane roadways and 1000 km are curves. The crash rates would then be 1,800/9.000= 0.2 for tangents and 600/1,000=0.6 for curves. When accounting for exposure, horizontal curves should clearly be prioritized over tangents. At the next step, the analyst sees if horizontal curves can be prioritized for treatment based on the sharpness of the curves. The 600 run-off-road right crashes on horizontal curves are grouped based on three categories of degree of curvature (<5, 5-10, >10 degrees). It is seen that most crashes are occurring on curves with a degree of curvature over 10 degrees. The analyst decides that run-off-road crashes on horizontal curves are an emphasis area and treatments should be prioritized for curves with a degree of curvature over 10 degrees.
A more comprehensive approach is outlined in NCHRP Report 501. The approach is comprised of two main steps.
Step 1: Frequency distributions are run over all crashes for every variable in the crash records database and the results are examined for peaks. This is essentially the frequency graph or crash tree diagram approach.
Step 2: Evaluate potential emphasis areas and formulate objectives. This step compares the characteristics of the potential Emphasis Areas from the list in Step 1 against those of their complementary subsets on a percentage or rate basis (e.g., time-of-day of alcohol crashes would be compared against time-of-day crashes that were not alcohol-involved to determine the optimum time-of-day for enforcement). This comparison includes the application of a statistical test of the observed differences to ensure the differences are significant. The number of crashes that could be reduced, or Maximum Gain, for a given Emphasis Area is estimated by assuming that the subset of crashes can be reduced to the expected value of its complementary subset of crashes.
The table below presents fictitious results of analyzing head-on crashes with respect to roadway curvature, which has been described as none, slight or sharp. The second column presents the number of head-on collisions for each curvature category and the third column the percentage by category. Columns four and five present the same information for the complementary subset (i.e., non-head-on collisions). Comparing the subset percentages, it is obvious that head-on collisions are overrepresented in the slight and sharp curvature categories compared to the complementary subset. The sixth column calculates the degree of overrepresentation by dividing the subset percentage by that of its complementary subset (e.g., for the sharp category, 11.8/5.0 = 2.36). The degree of overrepresentation is highest for the sharp curvature category. The maximum gain for each category is calculated as:
If the maximum gain is negative then a value of 0 is assigned.
Analysis of Head-On vs Non-Head-On Collisions Considering Roadway Curvature
Developing Emphasis Areas should be a collaborative exercise including agencies with a stake in road safety. These would typically include agencies addressing the components within a Safe System Approach: transport planning, road engineering, enforcement, education, and emergency services. Any other agencies that collect and maintain relevant data should also be included. The data used in the selection of Emphasis Areas includes data on vehicles, drivers and other road users, and infrastructure elements associated with crash data.
Examples of agencies at the local level that may be represented include:
Transportation or highway agencies: operations, planning, design, road construction, maintenance.
Law enforcement agencies: driver and vehicle safety surveillance.
Health agencies: injury prevention, emergency medical care, alcohol and drug safety programs.
Education agencies: driver education and through high school safety education.
One agency may take the lead on data analysis. Alternatively, multiple agencies can provide staff to work collaboratively.
Defining Emphasis Areas requires police-reported and/or self-reported crash data at a minimum. The availability of additional related data will allow a deeper exploration, potentially enabling more precise definitions of Emphasis Areas. Examples of other types of data include:
Roadway data
Number of signalized intersections in jurisdiction
Length of roadway by road type
Length of bicycle lanes
Traffic volume data
Average annual daily traffic by road segment
Commercial vehicle volumes
Bicycle volumes
Pedestrian volumes
Driver data
Number of licensed drivers by age
Number of licensed motorcyclists
Citation data
Hospital and emergency medical services data
Community surveys/feedback
Note that police-reported crash data may not capture a substantial number of crashes, particularly those involving pedestrians and bicyclists. Use of hospital and emergency medical services data can help fill this gap as well as provide more detailed information on injury severity. In some jurisdictions, data from insurance companies can also be a useful source of crash data.
Feedback from members of the community should also be considered. Observations, based on the experiences of community members can provide important insights into road safety issues that may not be readily apparent from other data.
Equity is related to road safety because lower income communities and communities of colour often carry a disproportionate burden of traffic-related injuries and fatalities. This concentration of safety problems is the result of patterns of disinvestment and under-investment in certain communities.
An equitable approach should be adopted when defining Emphasis Areas by prioritizing engagement and investments in traditionally under-served communities. Some cities overlay injury data with areas of economic hardship. In doing so, socioeconomic factors can be used as additional considerations in defining Emphasis Areas.
Defining Emphasis Areas requires people with a knowledge about collection practices for relevant data and their limitations. When various datasets are being merged and/or queried, people with this skillset are needed, such as data scientists or other professionals with relevant experience. People with knowledge of statistical analysis of data should be involved as well.
Additionally, as Emphasis Areas are also subject to pragmatic and political considerations, people with an understanding of how the safety program fits into the jurisdiction’s overall goals and policies should also be included.
While specific tools for defining Emphasis Areas are not necessarily needed, there are some available.
1. NCHRP Report 501 – Integrated Safety Management Process
NCHRP Report 501 provides detailed guidance on how to develop an integrated safety management process. The process assists agencies in integrating safety-related actions by proposing a method for bringing together agencies responsible for highway safety. Specifically related to the identification of Emphasis Areas, Appendix D of the report describes in detail a sophisticated methodology applying statistics for identifying Emphasis Areas using data, and effective strategies to reduce those crashes.
2. FHWA Crash Tree Diagram Tool
The Federal Highway Administration provides a free spreadsheet-based tool for constructing crash tree diagrams. A description of the tool is available at https://www.youtube.com/watch?v=QNUZ5b-J3Dw and the tool is available at https://ruralsafetycenter.org/resources/safety-data-analysis/.
Term | Definition |
Countermeasures | Interventions applied to reduce crashes, e.g. rumble strips |
Facility | Infrastructure provided for road user movements, e.g. roads, bicycle lanes, sidewalks |
Hotspots | Locations identified as having a high number of crashes compared to other locations |
Rumble strips | Textured strips installed on the road to alert drivers through tactile vibrations if they unintentionally veer off the roadway or across the centerline |
Cable median barrier | A safety barrier installed in the median of a divided highway composed of high-tension cables supported by posts |
High friction surface treatments | Applications of specialized materials or coatings on the road surface in increase friction between vehicle tires and the pavement |
Curve warning signs | Traffic signs used to warn drivers in advance of upcoming curves in the road |
Signal backplates | Panels mounted behind traffic signal heads to enhance the visibility of traffic signals |
Countdown pedestrian signals | Pedestrian crossing signals that display a numerical countdown indicating the time remaining for the pedestrian walk signal |
Educational campaigns | Public awareness initiatives designed to inform, educate and change behaviour related to road safety |
Crash tree diagram | A visual representation or chart that illustrates the frequency of crashes by crash types and other involved factors |
Road diets | A reallocation of road space by reducing the number of through lanes and adding a two-way left-turn lane, often with the addition of bicycle lanes or other facility |
Optical speed bars | Visual speed indicators painted on the road in the form of bars that provide optical cues to encourage motorists to reduce their speed |
Speed tables | A traffic calming device similar to a speed bump but that is longer and with a flat top |
Centreline hardening | A form of traffic calming that reduces the turning radius for vehicles using physical measures on the roadway to encourage slower speeds |
Gateway treatments | Physical measures taken where a rural road meets a more urban area to increase driver awareness that posted speed limits are changing, such as landscaping, signage or road markings |
