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                        Systemic Safety Project Selection Tool


            
            In This Section
        Safety Data Analysis & Tools
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                Element 1: The Systemic Safety Planning Process
Graphic – This image displays the continuous cycle among three elements, each of which contain specific processes, with Element 1 highlighted. Element 1 begins with Identity Focus Crash Types & Risk Factors, which feeds into Screen & Prioritize Candidate Locations, followed by Select Countermeasures, and Prioritize Projects.  The last process of Element 1 feeds into the one process within Element 2, Identify Funding for Systemic Program & Implement, which feeds into the sole process for Element 3, Perform Systemic Program Evaluation, which in turn feeds back into the first process of Element 1.

Overview of the Systemic Safety Planning Process

The systemic safety planning process (Element 1 of the Systemic Safety Project Selection Tool) consists of the four steps shown in Figure 3. Each step can be scaled based on the availability of technical resources and the quality or quantity of data available to support different analytical approaches. The systemic safety planning process is similar to most common safety management processes. The systemic safety planning process involves identifying the problem, screening and prioritizing candidate locations, selecting countermeasures, and prioritizing projects.

The premise that makes systemic safety planning different from traditional network screening techniques is that it looks for similar issues across the roadway system rather than focusing on select locations with high crash histories or densities. The systemic safety planning process begins by looking at systemwide data to analyze and identify focus crash types (those representing the greatest number of severe crashes) and potential risk factors. As the downward arrows indicate, the approach then moves to a micro-level risk assessment of locations across the network, which then leads to selecting relevant mitigating countermeasures most appropriate for broad implementation across those locations, and prioritizing projects for implementation. The upward arrows indicate that the results of one step might suggest the need to return to a previous step and make adjustments before continuing the process.

**FIGURE 3. Systemic Safety Planning Process**

Figure 3 – Graphic – Figure 3 presents the cyclic four-step systemic safety planning process. The four steps are Identify Focus Crash Types & Risk Factors, Screen & Prioritize Candidate Locations, Select Countermeasures, and Prioritize Projects.

The following chapters (Identify Focus Crash Types and Risk Factors, Screen and Prioritize Candidate Locations, Select Countermeasures, and Prioritize Projects) further describe the four steps of the systemic safety planning process. Each chapter includes a discussion of the objective, data needs, tasks, and outcomes, along with examples illustrating the fundamental process for each step.

Data Needs

The systemic safety planning process builds on the Federal Highway Administration (FHWA) guidance to develop SHSPs and structure an HSIP using data-driven processes. The four-step process uses basic types of crash, roadway, and traffic volume data that are recommended by the FHWA for use in safety analysis efforts. Several agencies actively applying the systemic approach to safety and conducting research relative to systemic safety improvement also use these types of data. The following chapters describe in detail the specific types of data associated with each step in the systemic safety planning process. These data are recommended for each step because they represent elements that can impact safety performance of a facility. Although agencies might not currently maintain all these data elements, more detailed data provide the opportunity to more specifically identify facility types and risk factors.

The systemic approach emphasizes a data-driven decision-making process. However, the Tool is intended to be flexible to support varying degrees of data availability.

The basic objective of the systemic safety planning process is to identify candidates for safety investment. Candidate identification results from comparing the actual conditions of segments, curves, and intersections with a set of observed characteristics associated with the locations where the focus crash types actually occurred. The data-driven process identifies the observed characteristics (risk factors) associated with the focus crash type. The systemic safety planning process uses selected risk factors to differentiate one segment from another, one curve from another, and one intersection from another in order to prioritize these facilities and give higher priority to locations where there is greater potential for future severe focus crashes. The data suggested to support the systemic approach are not intended to be prescriptive; some agencies currently use these types of data to successfully advance a systemic approach to safety. The systemic safety planning process can be adapted to meet agency-specific needs or crash reduction goals, consistent with the data available. The systemic planning process produces results with minimal levels of data; greater levels of data, however, support a more refined prioritization.

Identify Focus Crash Types and Risk Factors

Objective

The objective of the first step in the systemic safety planning process is to identify risk factors commonly associated with each focus crash type experienced across a system. This step involves reviewing systemwide (i.e., macro-level) crash data and identifying potential risk factors for further analysis. Identification of potential risk factors does not necessarily imply the observed characteristics "caused" the crashes; rather, the characteristics are useful to identify the situations in which the crashes occurred, so that similar "looking" locations can be identified and prioritized.

Data Needs

The identification of focus crash types and risk factors results from using a range of data elements. Following are the minimum recommended crash data elements:

System type
	Crash type
	Facility type
	Crash location type
	Location characteristicsThe FHWA's Model Inventory of Roadway Elements Fundamental Data Elements (MIRE FDE) identified for the HSIP is a good starting point for determining which roadway data to collect for a systemic analysis because it includes many of the roadway and traffic volume data elements recommended for use in this first step (FHWA, 2012). However, other road characteristics, such as shoulder width and type or roadway curvature, should be investigated when possible. The road and intersection data inventory is typically available in a geographic information system (GIS) or database, which should be linked with the crash records system. Ideally, the various data sets would incorporate the same time period. When volume data are from an earlier time period than crash data, first consider if changes have occurred that make the volumes no longer relevant (i.e., economic growth). If little change has occurred, agencies can consider using older traffic volumes. To compensate for greater change, agencies can estimate current traffic volumes by applying a growth factor appropriate for the region or jurisdiction.

The systemic safety planning process focuses on severe crashes (defined as fatal plus serious injury crashes) to be consistent with national safety programs. Furthermore, focusing on severe crashes reduces the scale of the effort and resources required to gather supplemental data if needed.

The data-gathering effort is an iterative process; as such, all data do not need to be collected at the beginning of the process. For example, the focus facility types selected will determine the necessary roadway and volume data to be collected to identify potential risk factors.

Process

The first step of the systemic safety planning process—identifying and understanding the risk factors commonly associated with the focus crash types—includes a series of analyses involving three tasks (Figure 4). The first task refines the problem identification from all crashes to a few focus crash types for an entire system or subregion. Further investigation through additional analyses attains a more comprehensive understanding of the facility type and risk factors (i.e., roadway characteristics) commonly linked with the severe focus crash types.

Data for Identifying Target Crash Types and Location Characteristics

Recommended Minimum Data

System type (e.g., state, local)
	Crash type (e.g., road departure, right angle, head-on, rear end, turning)
	Facility type (e.g., freeway, expressway, arterial, or collector)
	Crash location type (e.g., urban vs. rural, intersection vs. segment, tangent vs. curve)
	Location characteristics (e.g., topography, intersection elements, segment elements)Additional Data for Identifying Risk Factors

Traffic volumes for segments and intersections
	Roadway features (e.g., number of lanes, shoulder type and width, road edge features and quality, number and type of access, radius and superelevation of horizontal curves, density of horizontal curves, speed limit, speed differential between curves and tangents, medians, pavement condition and friction)
	Intersection features (e.g., number of approaches, skew, proximity to horizontal and vertical curves, number of approach lanes, signal timing, proximity to railroad crossing, traffic control devices, presence of street lighting, presence of commercial development)**FIGURE 4. Systemic Safety Planning Process: Tasks to Identify Focus Crash Types and Risk Factors**

Figure 4 – Diagram – Figure 4 presents the cyclic four-step systemic safety planning process. The four steps are Identify Focus Crash Types & Risk Factors, Screen & Prioritize Candidate Locations, Select Countermeasures, and Prioritize Projects. The first step, Identify Focus Crash Types & Risk Factors, is expanded to include three tasks. Task 1 is, "Select Focus Crash Type(s)". Task 2 is, "Select Focus Facilities". Task 3 is, "Identify and Evaluate Risk Factors".

Task 1: Select Focus Crash Types

Task 1 in the step to identify focus crash types and risk factors involves conducting a systemwide analysis of crash types to select those representing the greatest potential to reduce fatalities and severe injuries. This effort typically results in identifying the crash types that represent the greatest number of severe crashes across the system being analyzed.

A good starting point for identifying focus crash types is a state or regional SHSP, which documents emphasis areas (i.e., focus crash types) for the state or region's safety program. These emphasis areas were likely identified through a data-driven process, which is a primary principle of the systemic safety planning process. State agencies with completed Roadway Departure and Intersection Safety Implementation Plans can identify these as focus crash types for their systemic safety programs. As such, the analysis summaries contained in the plans are useful for the subsequent tasks that identify focus facilities and risk factors. Agencies can also refer to safety plans in which emphasis areas specific to their jurisdiction have been identified through a similar data-driven approach.

The Kentucky Transportation Cabinet developed a Roadway Departure Safety Implementation Plan in 2010 to detail the key steps and actions necessary to implement the broad initiatives outlined in the roadway departure emphasis area of the state's SHSP. The agency chose their focus facility and crash type for the pilot effort based on this plan. The data analysis had already been performed as part of the planning efforts for the SHSP and Roadway Departure Safety Implementation Plan, so the agency was able to begin the systemic analysis process at Task 3 of Step 1.

If the state or regional SHSP does not cover the roadway type or region of interest, then referencing the emphasis areas identified in the American Association of State Highway and Transportation Officials (AASHTO) SHSP is useful to determine what types of crashes require further investigation. Depending upon their needs, an agency can add additional emphasis areas to the list of 22 emphasis areas in the AASHTO SHSP (AASHTO, 2005). Some common additions include winter weather crashes, animal crashes, and driveway/access crashes. If a state SHSP added emphasis areas to AASHTO's list, then, at a minimum, those same emphasis areas should be included in this task. In addition to a systemwide assignment of crashes into the emphasis areas, subregional and jurisdictional analyses are an important consideration. The systemwide analysis can mask important localized issues—for example, differences between rural and urban locations or between state and local highway systems. Following are some typical sublevel summaries for severe crashes by emphasis area:

State-maintained highways compared with local agency roads
	Jurisdictional subdivisions (e.g., county, city)
	Rural areas or districts compared to urban/suburban areas or districts
	Areas with unique geography, such as mountainous areas
	Areas with strong seasonal travel patterns, such as tourist destinationsAASHTO's 22 Emphasis Areas

Part 1: Drivers

Instituting graduated licensing for young drivers
	Ensuring drivers are fully licensed and competent
	Sustaining proficiency in older drivers
	Curbing aggressive driving
	Reducing impaired driving
	Keeping drivers alert
	Increasing driver safety awarenessPart 2: Special Users

Making walking and street crossing safer
	Ensuring safer bicycle travelPart 3: Vehicles

Improving motorcycle safety and increasing motorcycle awareness
	Making truck travel safer
	Increasing safety enhancements in vehiclesPart 4: Highways

Reducing vehicle-train crashes
	Keeping vehicles on the roadway
	Minimizing the consequences of leaving the road
	Improving the design and operation of highway intersections
	Reducing head-on and across-median crashes
	Designing safer work zonesPart 5: Emergency Medical

Services
	Enhancing emergency medical capabilities to increase survivabilityPart 6: Management

Improving information and decision support systems
	Creating more effective processes and safety management systemsSince the systemwide analysis identifies crash types for an aggregate crash data set, the results are not as sensitive to specific locations as are the results of a subregion analysis in which the crash data set is more focused on a specific geographical area. Comparing the results of the systemwide analysis to subregion analyses highlights those crash types and contributing factors that may be substantial only in a localized area. For example, intersection crashes could be the top crash type in all districts within the state, while pedestrian and bicycle crashes represent a sizable portion of severe crashes only in the urbanized district. In this case, the safety program manager will not identify pedestrian and bicycle crashes as a top emphasis for the state; however, the crash data justifies encouraging the urban district manager to develop a pedestrian and bicycle safety program.

Example 1 illustrates the data-driven selection of focus crash types by the New York State Department of Transportation (NYSDOT). Using crash data from the state's Safety Information Management System (SIMS) database, NYSDOT identified focus crash types by disaggregating the crash data by emphasis area and facility type. This example highlights how roadway systems in different jurisdictions or subregions require different priorities.

Thurston County disaggregated data according to attributes recorded on crash reports (e.g., crash type, road geometry, lighting, and contributing circumstances), to identify their focus crash type.



EXAMPLE 1. New York State Department of Transportation Data Analysis to Select Focus Crash Type

NYSDOT identified focus crash types by disaggregating the crash data by emphasis area and facility type. The emphasis areas are from the 2010 New York State Strategic Highway Safety Plan. As the bold text highlights, intersection crashes are the most frequent severe crash type statewide (41 percent), followed by roadway departure crashes (26 percent). Since roadway departure crashes are the most predominant crash type on the state-owned system (30 percent), NYSDOT chose to focus their systemic planning efforts on this severe crash type. The data disaggregation also shows that the most predominant crash type on the county roadway system is road departure and is intersection-related for the city street systems.

**Fatal and Severe Injury Crashes from Safety Information Management System (2007-2011) Percent by Jurisdiction**
	Emphasis Area
			Statewide Total 114,592 mi
			Statewide Percentage
			State (01) Percentage 15,486 miles
			State (01) Total 15,486 miles
			County (02) Percentage 19,938 miles
			County (02) Total 19,938 miles
			City, Township, Village (03, 04, 12, 13) Percentage 76,735 miles
			City, Township, Village (03, 04, 12, 13) Total 76,735 miles
			Parkway (05) Percentage 511 miles
			Parkway (05) Total 511 miles
			Interstate (06, 07, 11) Percentage 575 miles
			Interstate (06, 07, 11) Total 575 miles
			Other Percentage 1,347 miles
			Other Total 1,347 milesTotal Fatal/Serious Injury
			63,443
			–
			31%
			19,819
			10%
			6,572
			45%
			28,597
			1%
			407
			2%
			1,540
			10%
			6.508Young drivers (under 21)
			9,686
			15%
			17%
			3,394
			22%
			1,441
			13%
			3,747
			12%
			48
			13%
			201
			13%
			855Older drivers (over 64)
			8,805
			14%
			17%
			3,405
			15%
			978
			11%
			3,270
			8%
			34
			10%
			149
			15%
			969Aggressive driving and speeding-related
			15,378
			24%
			30%
			5,905
			33%
			2,152
			17%
			4,979
			45%
			182
			56%
			866
			20%
			1,294Drug and alcohol-related
			6,175
			10%
			11%
			2,227
			16%
			1,039
			9%
			2,581
			9%
			35
			10%
			147
			9%
			599Inattentive, distracted, asleep drivers
			13,258
			21%
			23%
			4,631
			20%
			1,291
			20%
			5,598
			15%
			63
			20%
			302
			21%
			1,373Pedestrian crashes
			11,786
			19%
			9%
			1,860
			6%
			421
			28%
			8,122
			5%
			19
			4%
			54
			20%
			1,310Bicycle crashes
			3,390
			5%
			3%
			518
			3%
			187
			8%
			2,414
			0%
			2
			0%
			1
			4%
			268Motorcycle crashes
			852
			1%
			2%
			360
			2%
			141
			1%
			283
			1%
			4
			1%
			20
			1%
			44Heavy vehicle crashes
			3,123
			5%
			6%
			1,266
			4%
			234
			4%
			1,051
			1%
			6
			19%
			288
			4%
			278Train-vehicle crashes
			17
			0%
			0%
			0
			0%
			6
			0%
			7
			0%
			0
			0%
			0
			0%
			4Road departure crashes
			16,668
			26%
			30%
			5,985
			44%
			2,892
			18%
			5,128
			44%
			179
			47%
			722
			27%
			1,762Intersection crashes
			25,791
			41%
			25%
			5,033
			30%
			1,957
			64%
			18,270
			16%
			65
			4%
			64
			6%
			402Head-on and sideswipe crashes
			3,071
			5%
			7%
			1,439
			7%
			490
			3%
			887
			2%
			7
			2%
			37
			3%
			211Workzone crashes
			214
			0%
			1%
			104
			0%
			16
			0%
			32
			0%
			1
			2%
			37
			0%
			24Depending on the focus crash type, further data disaggregation may be necessary to more specifically define a systemic safety problem. For example, Thurston County began their systemic planning effort with a focus on lane departure crashes that had been formulated from previous safety-related studies. Example 2 illustrates the disaggregation of the County's lane departure crash data into various data elements available from the crash reports.

Helpful Hints and Other Considerations

**How many crash types should I select?**

How you disaggregate crash data depends on the data type, system capabilities, and agency past practices. Disaggregating crash data is about identifying statewide and regional trends regarding a focus for subsequent analytical efforts. Screening those trends to a manageable list of target crash types is very important because if the list is too long, then the associated level of effort could be a burden. If the systemic safety program is new, you might consider limiting your analysis to one or two crash types, which limits the scope while the methodology is developed and refined.

**Should crashes be assigned to a single category or is double counting acceptable?**

When completing the analysis, a single crash could involve more than one emphasis area. For example, a fatal intersection crash involving a drinking teen-driver covers three AASHTO emphasis areas. One approach is to identify the leading contributing factor, thereby assigning each crash to only one emphasis area. Another approach is to include the crash in each related emphasis area to determine the total number of crashes in each category. Regardless of the decision made, the process needs to be documented so that consistency is maintained across regional analyses and jurisdictions, and when the analysis is updated.

**What criteria do I use to identify crashes in each emphasis area?**

Crash record systems vary greatly by jurisdiction, so there are no guidelines or criteria that can be used to identify crashes in each emphasis area. Instead, the process to analyze crash data when developing the state SHSP might provide an answer or general guidance for local agency crash record systems. Also, FHWA and National Highway Traffic Safety Administration (NHTSA) provide guidance on how Fatality Analysis Reporting System (FARS) data can be used to identify various crash types, such as road departure or speeding-related crashes (NHTSA). These resources might provide insights on how local crash record systems can be used to identify crashes within each emphasis area.

**As a local jurisdiction, can I select focus crash types different from statewide focus areas?**

A Department of Transportation (DOT) district, county, or city should consider crash types that represent the greatest potential for crash reduction in their jurisdiction. For example, an urban DOT district might select pedestrian crashes for a district program because they represent a sizeable problem locally, even though pedestrian safety may not be a priority focus area statewide. Focus crash types for local jurisdictions should ideally be selected in consultation with the state DOT, particularly if the state agency establishes priorities for allocating funding.

**Should the focus be on infrastructure-related crash types only or also include other factors, such as driver behavior?**

Highway agencies should not be reluctant to select crash types that are related to driver behavior, such as unbelted vehicle occupants, speeding, or alcohol-related. Selecting these crash types as the focus of systemic safety planning efforts creates opportunities for coordinating with enforcement and driver education programs.

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EXAMPLE 2. Thurston County Public Works Data Analysis to Select Focus Facilities

**2006 – 2010 Collision History**
	2006 – 2010 Collision History
			Fatal and Serious Crashes – Thurston County Percentage
			Fatal and Serious Crashes – All Counties Percentage
			Fatal and Serious Crashes – Statewide PercentageOverall Numbers
			Total number of collisions
			3
			4
			2By Collision Type
			Hit fixed object
			48
			41
			27By Collision Type
			Overturn
			10
			14
			11By Collision Type
			Angle (left turn)
			9
			13
			16By Collision Type
			Head on
			7
			5
			5By Light Condition
			Daylight
			52
			54
			58By Light Condition
			Dark – no street lights
			33
			29
			16By Junction Relationship
			Intersection-related
			19
			22
			33By Junction Relationship
			Driveway-related
			5
			6
			7By Junction Relationship
			Non-Intersection
			77
			72
			60Hit Fixed Object Crashes Only – By Fixed Object Hit
			Tree/stump (stationary)
			14
			10
			5Hit Fixed Object Crashes Only – By Fixed Object Hit
			Roadway ditch
			7
			6
			3Hit Fixed Object Crashes Only – By Fixed Object Hit
			Utility pole
			7
			5
			3By Roadway Curvature
			Straight and level
			42
			42
			54By Roadway Curvature
			Horizontal curve (all)
			45
			39
			26By Speed Limit (Number of Drivers)
			35 mph
			28
			48
			35By Speed Limit (Number of Drivers)
			50 mph
			69
			33
			16By Contributing Circumstance Number of Drivers)
			Exceeding safe/stated speed
			48
			41
			31By Contributing Circumstance Number of Drivers)
			Under influence of alcohol/drugs
			42
			31
			25By Contributing Circumstance Number of Drivers)
			Over centerline
			16
			12
			10By Contributing Circumstance Number of Drivers)
			Inattention/distraction
			11
			13
			13By Driver Age Group
			Ages 16-20
			26
			26
			20By Driver Age Group
			Ages 41-50
			28
			23
			26By Seat Belt/Car Seat Use (Number of Occupants)
			No restraint
			33
			35
			25Source: Thurston County, Washington, Department of Public Works

Between 2006 and 2010, 177 fatal and serious injury crashes occurred in Thurston County, Washington. A spreadsheet program was used to disaggregate the lane departure crash data into various data elements available from crash reports. This dataset shows that the horizontal curve crashes are overrepresented in the County. Also, the proportion of roadway departure crashes in horizontal curves is greater in Thurston County than for either the combined County roadway system in Washington or the statewide roadway system. As a result, Thurston County selected lane departure crashes on horizontal curves as their focus crash type.

Task 2: Select Focus Facilities

After selecting the focus crash types, Task 2 answers the question Where are the crashes occurring? A "crash tree" diagram is the recommended approach to answer this question. The crash tree can have a number of different formats, depending on agency capabilities and data availability. One such example is to begin the crash tree with the total number of severe crashes at the highest level. Each subsequent level separates the severe crashes by facility type.

At a minimum, the crash tree analysis should include separation by urban and rural, ownership (state and local), segment and intersection, segment type, and intersection control type. This minimum level of detail allows for the refinement of facility types, which is useful to focus the identification of risk factors (i.e., characteristics associated with the locations where the focus crash types are occurring) and select relevant countermeasures.

Depending on the data set and the scope of the analysis, examples of potential combinations include the following:

Segment versus intersection
	Segment type, including freeway, multilane, two-lane, and one-way (typical segment divisions)
	Intersection control type, including signalized, unsignalized, and uncontrolled (typical intersection divisions)
	On tangent versus on curve
	High-speed versus low-speed
	Presence of street lighting
	District or regionExamining the crash tree leads to the identification and selection of the facility types where the focus crash types most frequently occur. States with a Roadway Departure or Intersection Safety Implementation Plan may already have crash trees and could use these plans to identify focus facility types for either their roadway departure or intersection crashes. Example 3 shows a crash tree diagram for the New York state roadway system.

Systemic approach: Deploy countermeasures at locations with greatest risk. Systematic approach: Deploy countermeasures at all locations.

If data or resources are not available to complete the remaining tasks and steps of the four-step systemic safety planning process, then an agency can still move forward with selecting and implementing countermeasures to address the focus crash types on the focus facility type. After identifying the focus crash type and facility type, a systematic deployment (deploy everywhere), instead of systemic (deploy at locations with greatest risk), of cost-effective countermeasures is a possibility. While a systematic deployment requires no further analysis to prioritize locations, the approach requires more funding since all locations are improved.

Helpful Hints and Other Considerations

**How many levels will my crash tree include?**

That will depend on the data and your starting point. For example, you might choose to begin the crash tree with only data for your jurisdiction or subregion instead of statewide, thereby eliminating one or more levels from the diagram.

Typically, most information used at this step will be reported by the officer on the crash report. Therefore, use whatever data are considered reliable and relevant for the focus crash type, but be careful not to create too many levels or the number of crashes will become small and the patterns difficult to identify.

**Does the crash tree include all severe crashes or just severe crashes for one focus crash type?**

Either option is considered acceptable. If there are relatively few severe crashes, then it might be best to begin the crash tree with all crash types. However, if there are instead many severe crashes for a particular crash type, the crash tree might focus on just the one.

**How many facility types should I select?**

Selecting fewer facility types is generally advised because it will streamline the process of identifying candidates for investment, reduce effort to conduct follow-up evaluations, and simplify the identification process if changes in crash numbers are a direct result of the projects implemented. However, the selection does not have to be a single type of facility for each focus crash type: an intersection systemic safety program might choose both urban signalized and rural thru-stop intersections. There is no set rule on exactly how many or what proportion of the severe crashes must occur at the facility type to be selected. An important consideration is selecting facilities that have crash histories that permit the identification of patterns and risk factors.

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EXAMPLE 3. New York State Department of Transportation Crash Tree Diagram to Select Focus Facility

Example 3 – Tree Diagram ndash; After selecting lane departure as their focus crash type based on an analysis of crash data for the years 2007 through 2011, NYSDOT created a crash tree diagram for the state roadway system to identify the focus facility type for their systemic planning effort.

Source: New York State Department of Transportation Office of Traffic Safety and Mobility

After selecting lane departure as their focus crash type based on an analysis of crash data for the years 2007 through 2011, NYSDOT created a crash tree diagram for the state roadway system to identify the focus facility type for their systemic planning effort. The first level separates the severe roadway departure crashes into rural, urban, and New York City areas. Separating the data into three more levels (divided versus undivided, number of lanes, and speed limit) identifies the appropriate focus facility as those that are rural, undivided, and two lanes with a posted speed limit of 55 miles per hour (represented by the highlighted boxes in the diagram).

Task 3: Identify and Evaluate Risk Factors

Task 3 further defines the facility types selected in the previous task by documenting the most common characteristics of the locations where crashes occurred. For example, if the previous tasks suggested a focus on road departure crashes on rural two-lane segments, then this task might indicate that these crashes were over-represented on roads with poor edges, curvilinear alignment, and volume within a specific Average Annual Daily Traffic (AADT) range. Tasks 1 and 2 relied on data typically available in the crash records system. Task 3 is the first point where road and intersection inventories are likely needed to provide additional levels of detail to support the data analysis.

The first decision to be made for this task is determining which characteristics will be evaluated—in other words, the potential risk factors for the systemic network screening. The initial characteristics are further evaluated before selecting the final characteristics that represent the risk factors. Selecting characteristics for evaluation might be based on several considerations, but it is important that they can indicate greater potential for severe focus crashes to occur. For example, the shoulder surface type might be a risk factor for roadway departure crashes in a curve but not for right angle crashes at intersections. If not certain whether a characteristic might be a suitable risk factor, then first reference safety research before evaluating that risk factor for a specific jurisdiction. Example 4 summarizes the research process the Kentucky Transportation Cabinet (KYTC) conducted to identify potential risk factors.

Potential Risk Factors

**Roadway and Intersection Features**

Number of lanes
	Lane width
	Shoulder surface width and type
	Median width and type
	Horizontal curvature, superelevation, delineation, or advance warning devices
	Horizontal curve density
	Horizontal curve and tangent speed differential
	Presence of a visual trap at a curve or combinations of vertical grade and horizontal curvature
	Roadway gradient
	Pavement condition and friction
	Roadside or edge hazard rating (potentially including sideslope design)
	Driveway presence, design, and density
	Presence of shoulder or centerline rumble strips
	Presence of lighting
	Presence of on-street parking
	Intersection skew angle
	Intersection traffic control device
	Number of signal heads vs. number of lanes
	Presence of backplates
	Presence of advanced warning signs
	Intersection located in or near horizontal curve
	Presence of left-turn or right-turn lanes
	Left-turn phasing
	Allowance of right-turn-on-red
	Overhead versus pedestal-mounted signal heads
	Pedestrian crosswalk presence, crossing distance, signal head type**Traffic Volume**

Average daily traffic volumes
	Average daily entering vehicles
	Proportion of commercial vehicles in traffic stream**Other Features**

Posted speed limit or operating speed
	Presence of nearby railroad crossing
	Presence of automated enforcement
	Adjacent land use type (e.g., schools, commercial, or alcohol-sales establishments)
	Location and presence of bus stopsReturn to top

EXAMPLE 4. Summation of Kentucky Transportation Cabinet Research Process to Identify Potential Risk Factors

**Risk Factors with Potential Applicability for Run-Off-Road and/or On-Curve Crash Type**
	Risk Factors (Highway Safety Manual)
			Compatible Highway Performance Monitoring System Attributes
			Data Available
			HSM – SPF Base Condition for Rural 2-Lane RoadFrom HSM Chapter 6 (run-off-road)
			From HSM Chapter 6 (run-off-road)
			From HSM Chapter 6 (run-off-road)
			From HSM Chapter 6 (run-off-road)Inadequate Lane Width (risk factor selected by KYTC for the systemic risk assessment)
			Item 34 – lane width
			Yes
			12 feetSlippery Pavement
			16 attributes that are “pavement-related” Item 61 – climate zone
			No
			–Inadequate median width
			Items 35, 36 – median type, median width
			Yes
			–Inadequate Maintenance
			Item 54 – year roadway was last improved
			No
			–Inadequate Roadway Shoulders (risk factor selected by KYTC for the systemic risk assessment)
			Items 37, 38, 39 – shoulder type and width
			Yes
			6 feet, pavedPoor Delineation (pavement markings, RPMs, chevron signs, object markers, PMDs)
			None
			No
			Centerline Rumble Strips – NonePoor Visibility
			None
			No
			Lighting – NoneExcessive Speed (risk factor selected by KYTC for the systemic risk assessment)
			None
			No
			Automated Speed Enforcement – NoneFrom HSM Chapter 6 (vehicle rollover)
			From HSM Chapter 6 (vehicle rollover)
			From HSM Chapter 6 (vehicle rollover)
			From HSM Chapter 6 (vehicle rollover)Roadside Design (e.g. non-traversable side slopes, pavement edge dropoff)
			None
			Yes
			Roadside Hazard Rating (RHR) = 3Pavement Design
			16 attributes that are “pavement-related”
			No
			–From HSM Chapter 6 (fixed object)
			From HSM Chapter 6 (fixed object)
			From HSM Chapter 6 (fixed object)
			From HSM Chapter 6 (fixed object)Obstruction In or Near Roadway
			None
			Yes
			Roadside Hazard Rating (RHR) = 3Inadequate Lighting
			None
			No
			Lighting – NoneInadequate Roadway Geometry (risk factor selected by KYTC for the systemic risk assessment)
			Item 43 – curves
			Item 45 – grades
			Item 46 – percent passing sight distance
			Yes
			(Curves)
			Horizontal curvature – None
			Vertical curvature – None
			Passing Lanes – NoneFrom HSM Chapter 13
			From HSM Chapter 13
			From HSM Chapter 13
			From HSM Chapter 13Roadway Signs (a CMF)
			None
			Yes
			–Source: Kentucky Transportation Cabinet

The four risk factors selected by KYTC for the systemic risk assessment are: Horizontal curve density, lane width, shoulder type, and speed limit. These are denoted by an asterisk (*) in the table.

The Kentucky Transportation Cabinet (KYTC) consulted a variety of references to assist with identifying potential risk factors. A list of potential risk factors for the focus crash type (lane departure crashes on 2-lane rural roads) was generated based on risk factors presented in Chapters 6 and 13 of the Highway Safety Manual. The table shows the potential risk factors, of which four were selected for the systemic risk assessment.

The Highway Pavement Management System (HPMS) was then reviewed to determine if their database contained an attribute related to each risk factor. The table summarizes those potential risk factors for which data were either available or collected for this systemic planning effort.

Availability of data or the ability to collect data should be part of the decision process for selecting a risk factor so candidate locations can be identified based on their characteristics. KYTC also included the base conditions for the focus facility type from the Highway Safety Manual as another source of information to assist with evaluating and selecting risk factors.

Additionally, the availability of the data element in existing databases, the ability to quickly gather data if not already available, and the applicability to the focus crash type and facility type (e.g., intersection characteristics do not need to be investigated for a systemic lane departure program) influence the selection of characteristics to review as potential risk factors. For data elements in an existing database, concerns about quality or the amount of time since the last update also may influence the decision of whether to evaluate that data element as a potential risk factor. Data that do not reflect current conditions could lead to implementing a countermeasure that is no longer appropriate or the best choice for addressing the focus crash type.

The list of potential risk factors suggests characteristics to be examined for curves, segments, and intersections. These characteristics are based on a review of published research and professional experience, many of which are inputs used by the predictive methods in the AASHTO Highway Safety Manual (HSM), and the degree to which many of these attributes might affect crash frequency is available within the HSM (AASHTO, 2010). The FHWA's Crash Modification Factor (CMF) Clearinghouse is another source for information on the relationship between location characteristics and their potential to contribute to a severe focus crash type (refer to the Appendix for more information about the CMF Clearinghouse). Table 1 shows examples of potential risk factors based on focus crash types.

**TABLE 1. Potential Risk Factors for Example Focus Crash Types**
	Example Focus Crash Type
			Potential Risk FactorsRural Crashes
			Rural CrashesRoad Departure
			Road edge condition
			Access density
			Curve density
			Traffic volumeRoad Departure in Horizontal Curve
			Curve radius
			Speed differential (from tangent approach)
			Visual trap
			Intersection in the curve
			Traffic volumeIntersection
			Skewed approach
			Proximity to horizontal and/or vertical curve
			Presence of commercial development
			Proximity to at-grade railroad crossing
			Traffic volume
			Distance from previous controlled intersectionUrban Crashes
			Urban CrashesPedestrian
			Intersection control type
			Major road characteristics (e.g., number of lanes, divided or undivided)
			Traffic volume
			Traffic speed
			Presence or proximity of pedestrian generator
			Presence or proximity of transit stop
			Presence of sidewalkIntersection
			Left or right turn lanes
			Left-turn signal phasing
			Right-turn-on-red
			Red-light enforcement
			Intersection control
			Number of lanes on major approach
			Divided or undivided
			Lighting
			Traffic volume
			SpeedAfter potential risk factors have been identified, they are evaluated to determine whether the characteristics exhibit a relationship to future crash potential. Only those that positively demonstrate a relationship should be selected as risk factors. Two approaches to evaluate these relationships are using descriptive statistics and reviewing characteristics using CMFs from published research.

Descriptive statistics. Descriptive statistics are used to compare the proportion of locations where the location characteristics exist with the percentage of severe crashes. For example, consider a scenario where an analysis of an intersection database identifies only 10 percent of rural unsignalized intersections are skewed, yet more than 40 percent of the severe rural unsignalized crashes occurred at skewed intersections. This indicates skew is overrepresented at rural unsignalized locations experiencing a severe crash. By extension, skew would be a good choice for one risk factor when prioritizing locations. Another option is to compare the crash density of locations exhibiting the characteristic with locations without the characteristic. Where the crash density differs between locations with and without the characteristic, then that characteristic could be used to differentiate between locations for prioritization.

Reviewing characteristics using CMFs from published research. The safety effectiveness of design features and traffic characteristics can be used instead of descriptive statistics to select risk factors. For example, intersection skew has been shown to increase crash frequency (CMF greater than 1.0) while intersection lighting has been proven to reduce crashes (CMF less than 1.0). By applying CMFs documented in safety research results, an agency could select intersection skew and the absence of intersection lighting as risk factors in lieu of local crash analysis. Furthermore, combining the findings and CMFs from research with the results of the local descriptive statistics might increase confidence in the final selection of risk factors. For example, if a county agency has a relatively small data set to evaluate risk factors for severe intersection crashes, then the descriptive statistics might not be conclusive for skew and lighting. However, CMFs for skew and lighting might reinforce or confirm the patterns seen in the local descriptive statistics, providing greater confidence that these characteristics are risk factors for a future severe crash.

Example 5 depicts the descriptive statistics application used by NYSDOT to identify curve radii as a risk factor.

EXAMPLE 5. New York State Department of Transportation Evaluation of Curve Radii as a Potential Risk Factor

Example 5 - Graph - Example 5 shows the results of analyzing curve radius as a risk factor.

Source: New York State Department of Transportation Office of Traffic Safety and Mobility

NYSDOT chose curve radii as a potential risk factor because of the typical geometry of their focus facility – rural, undivided, two-lane roadways. When compared with all curves along the focus facility type, those segments with curve radii between 100 and 500 feet are overrepresented when compared with the proportion these curves represent of the focus facility segments. NYSDOT selected a curve radius less than 300 feet as a risk factor because the data show that 12 percent of severe crashes occurred in curves with radii less than 300 feet, while only 7 percent of all reviewed curves have radii less than 300 feet.

As illustrated in Example 6, Thurston County also used descriptive statistics to compare the proportion of severe curve-related roadway departure crashes on various functional classifications of roadways to the proportion of those functional classifications represented on the entire county roadway system.

Helpful Hints and Other Considerations

**How can I test a characteristic even if it is not part of an existing data set or if my data set cannot be merged with the crash data?**

You could either review published CMFs or consider sampling locations for evaluation. Instead of a systemwide comparison, sample locations that have severe crashes and compare them with sampled locations without severe crashes. Video logs, online aerial imagery, or windshield surveys can be used to cost-effectively collect information on the characteristics. This also allows you to understand the magnitude of effort needed to collect the information for an entire system before choosing the characteristic as a risk factor. Does the crash tree include all severe crashes or just severe crashes for one focus crash type?

Either option is considered acceptable. If there are relatively few severe crashes, then it might be best to begin the crash tree with all crash types. However, if there are instead many severe crashes for a particular crash type, the crash tree might focus on just the one.

**How many risk factors should I select?**

There is no rule on how many risk factors must be selected. At a minimum, you would need two to three risk factors to differentiate between sites. Of these, the presence of one or more fatal or serious injury crashes can be viewed as a risk factor. Selecting more—up to seven to ten—requires more time to perform the screening but also helps to determine the likelihood of future crashes.

**Should potential risk factors be combined during the evaluation process?**

There might be occasions in which individual risk factors do not appear to be overrepresented in the crash data set. In these cases, you can perform the descriptive statistics analysis for combinations of risk factors to determine whether the related crashes are overrepresented. For example, one agency's crash data indicated that neither shoulder width nor shoulder surface type were risk factors for road departure crashes in horizontal curves. Engineering judgment suggested further analysis was required. Combining the data associated with these two risk factors revealed that severe crashes were found to be overrepresented in curves that had either narrow gravel shoulders or wide paved shoulders (which were also high volume corridors).

**Can you still identify risk factors if you do not have local Average Annual Daily Traffic (AADT) information?**

Unless the range of volumes across the network being evaluated is very narrow, it is generally desirable to consider AADT as a risk factor. Since higher volume may not always relate to higher risk, agencies should conduct a descriptive statistics analysis to identify the range of volumes with the highest risk for potential crashes. If traffic volume data are not available to perform a descriptive statistics analysis for AADT, then agencies are strongly encouraged to do a qualitative assessment (e.g., categorizing AADT as high, medium, or low to evaluate if AADT is indeed an important risk factor).

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EXAMPLE 6. Thurston County Public Works Evaluation of Roadway Functional Class as a Potential Risk Factor

Example 6 - Graph - Example 6 shows the proportion of crashes for three categories among six functional roadway classes: Rural Minor Arterial, Rural Major Collector, Rural Minor Collector, Urban Principal Arterial, Urban Minor Arterial, and Urban Major Collector. The three categories represent crash severity: Fatal/serious, Injury, and Property Damage. Rural Major Collector is the predominant risk factor among each of the three categories, with 76%, 76%, and 65% of crashes for Fatal/serious, Injury, and Property Damage, respectively. Injury and Fatal/serious are similarly represented, with a maximum difference of only 3% in any of the functional roadway classes. Property Damage is represented at 22% in Rural Minor Collector, which represents only 11% and 8% of Fatal/serious and Injury crashes, respectively.

Source: Thurston County, Washington, Department of Public Works

Thurston County compared the proportion of severe curve-related roadway departure crashes on various functional classifications of roadways to the proportion those functional classifications represent of the entire County roadway system. The data show that the focus crash type occurs on roadways with a Rural Major Collector functional classification in a greater proportion than this roadway type represents for the County system. Based on this descriptive statistics analysis, Thurston County chose Rural Major Collector functional classification as a risk factor.

Outcome

Completing the first step of the systemic safety planning process provides an understanding of the focus crash types, focus facilities, and risk factors that represent the core of the developing systemic safety program. This information informs the risk assessment process in the next step of the systemic safety planning process.

Answering Some Common Concerns

**Q: Is there a minimum number of crashes on a system that is considered necessary to provide credible results?**

A: That will depend on the data and your starting point. For example, you might choose to begin the crash tree with only data for your jurisdiction or subregion instead of statewide, thereby eliminating one or more levels from the diagram.

Typically, most information used at this step will be reported by the officer on the crash report. Therefore, use whatever data are considered reliable and relevant for the focus crash type, but be careful not to create too many levels or the number of crashes will become small and the patterns difficult to identify.

**Q: What if my data system cannot provide the ideal level of data?**

A: The process can be modified to work with the data that are available, but the analysis outcomes might not be as detailed as desired. If existing road and intersection data are limited, then video logs, aerial imagery, or field visits might supply useful information. However, these data collection efforts would require additional investment to synthesize the data into a usable format.

**Q: What if my jurisdiction has developing areas for which land use patterns are changing and traffic volumes are growing?**

A: The process ideally relies on the most recent crash, volume, and roadway data available. If these data do not reflect current conditions, then the process might still be applicable, depending upon the crash type and countermeasure selection. For example, if traffic volumes are increasing on a facility but access is not changing, then the risk rating and the countermeasure selection might still be appropriate. A possible exception is when the type of countermeasure assigned for very low-volume facilities is different than moderate- and high-volume facilities. In this case, you should consider the countermeasures identified for moderate- and high-volume areas based on the volume growth rate. On the other hand, if the growth in the area is resulting in modified land use patterns, access density, and roadway cross-section, then the countermeasures derived from the process might not be as useful for preventing crashes given the current volumes and roadway configurations. In these situations, you should critically review the analysis to determine whether the risk rating and selected countermeasure will apply to conditions in the near future.

Screen and Prioritize Candidate Locations

Objective

The objective of the second step in the systemic safety planning process is to develop a prioritized list of potential locations on the roadway system (e.g., segments, curves, intersections) that could benefit from systemic safety improvement projects. The results of this step answers the question Are all elements of my system equally at risk for the focus crash types or are some more at risk than others?

The process to screen and prioritize candidate locations evaluates specific sites (i.e., individual segments, curves, and intersections) at the micro-level. The tasks in this step involve reviewing all elements from the focus facility types and assigning a level of risk to each element. Risk is inferred from the presence of crashes and risk factors, which are roadway and traffic features commonly associated with the locations where the focus crash types occur.

Data Needs

The screening and prioritization process requires two primary types of data. The first type is site-specific crash information, including severity, type, and any contributing factors relevant to the focus crash types and facility types. The second data type is the basic features of the road system, especially geometric or traffic elements selected as risk factors in the previous step of the systemic safety planning process. This information is available in from variety of sources, including electronic databases of roadway features and traffic characteristics, archives of as-built plans, aerial photography and street views, video logs, traffic control device inventories, and traffic flow maps.

Process

As Figure 5 illustrates, screening and prioritizing candidate locations involves three tasks: selecting the locations or elements of the roadway system to review, verifying selected crash risk factors, and prioritizing these elements based on the presence of the risk factors at each location. In this process, the more risk factors present infers a higher priority as a candidate for safety investment.

**FIGURE 5. Systemic Safety Planning Process: Tasks to Screen and Prioritize Candidate Locations**

Figure 5 - Diagram - Figure 5 presents the cyclic four-step systemic safety planning process. The four steps are Identify Focus Crash Types & Risk Factors, Screen & Prioritize Candidate Locations, Select Countermeasures, and Prioritize Projects. The second step, Screen & Prioritize Candidate Locations, is expanded to include three tasks. Task 1 is, "Identify Network Elements to Analyze". Task 2 is, "Conduct Risk Assessment". Task 3 is, "Prioritize Focus Facility Elements".

Task 1: Identify Network Elements to Analyze

Task 1 identifies the elements from the focus facility types, which represent the locations where the focus crash types tend to occur. For spot-based applications such as curves and intersections, all relevant locations are identified first. For segment applications, corridors are split into elements with consistent design (i.e., cross-section) to establish homogeneous segments. Additionally, the segment elements should have uniform traffic and design characteristics whenever possible, especially with respect to the selected risk factors. Homogeneous segments allow for consistent application of risk assessment and the same countermeasure to be selected for the entire element. For example, a rural two-lane corridor might be divided into segments extending from the limits of one small rural community to the limits of the next community. The Highway Safety Improvement Program Manual provides additional guidance for identifying network elements (FHWA, 2010).

After identifying the network elements to analyze, assemble the information in a format useful for conducting the risk assessment and documenting the results. Refer to the Minnesota Department of Transportation Case Study for an illustration of how to document identified network elements.

Helpful Hints and Other Considerations

**What other data should I collect when reviewing locations for risk factors?**

When examining specific locations, in addition to collecting information about the risk factors, you should also collect information that might impact countermeasure selection. For example, if the focus crash type is lane departure on rural two-lane highways, data related to shoulder width, shoulder surface type, and lane width can help select countermeasures, such as shoulder rumble strips, edgeline rumble strips, or enhanced edgeline markings.

You might not be able to gather every possible piece of data that impacts the project type selection, especially the first time going through a systemic analysis. However, the point is to think this through to prevent (or at least minimize) having to scan the part of the system selected for treatment a second time.

Task 2: Conduct Risk Assessment

In Task 2, agencies assess the risk of the systems and specific locations selected for analysis. The purpose of this assessment is to identify and document roadway and traffic characteristics pertaining to the selected risk factors, as well as total crash history, if applicable, for each location. For purposes of the Systemic Tool, the term "risk assessment" means the effort to collect the roadway/traffic data and to characterize the potential for a severe focus crash to occur at a given location or along a given segment of roadway based on certain characteristics present at these network elements.

The roadway and traffic characteristics could be available in a database format or can be collected as part of a field review of the road system. Roadway and traffic characteristics might also be collected in a virtual environment with field confirmation, as appropriate. Agencies with experience developing systemic approaches have found that roadway features can be documented in the office using video logs, aerial photography, and traffic volume data bases. Also, local agencies can provide some basic information about design features and traffic control devices.

The process to document the presence of a risk factor at a given network element involves recording if the risk factor is present or not. Presence can be indicated with a "1" or an asterisk or some other identifier that can be tabulated. Summing the number of risk factors present provides the ability to compare and prioritize network elements. The MnDOT Case Study at the end of this section provides an example of the documentation produced for a risk assessment.

After identifying and documenting the network elements for the prioritization process, consider if the selected risk factors are feasible for a systemwide analysis. A risk factor is not useful to prioritize locations if it is present at every location on the focus facility. For example, speed limit may need to be removed as a risk factor if it is the same for all roadway segments identified for the screening process. Also, curve radii may not be an appropriate risk factor if every curve on the focus facility type has the same radius. After considering, remove or add risk factors if necessary. This revision may be necessary if risk factors were selected using CMFs or a sample of locations on the focus facility. The MnDOT Case Study contains an example of the determination of risk factor feasibility.

Task 3: Prioritize Focus Facility Elements

Task 3 generates the prioritized lists of segments, horizontal curves, and intersections based on the presence of the selected risk factors—the more risk factors present, the greater the potential for the focus crash type and the higher the priority as a candidate for safety investment. Systemic analysis approaches might weigh risk factors equally, which simply means the more risk factors present, the higher the location's priority. However, risk factors also can be given relative weights. In this case, particular risk factors—if found to have a stronger association with locations where severe focus crashes occurred—can be given larger weights. The values for relative weights may be high/medium/low or based on integers that infer a higher level of confidence in the weights. Example 7 illustrates how Thurston County weighted their selected risk factors based on their level of confidence in the data representing that risk factor.

Agencies can adjust the thresholds (the number of risk factors present or a weighted value) used to identify high-priority candidates based on the level of funding anticipated for implementation. To set the threshold, agencies should identify more candidate locations than can be implemented in a given year. There are two reasons for this. First, the effort creates a backlog or shelf life for the analysis so that it does not have to be completed annually. Second, locations might drop off the list as a result of field conditions or where additional time or funding is needed to implement the selected countermeasure. Having identified more candidates than can be implemented in one year provides flexibility to ensure all available funding can be allocated to priority projects. The MnDOT Case Study contains an example illustration of how risk assessment results are useful to establish a threshold for candidate locations.

EXAMPLE 7. Thurston County Public Works Risk Factor Prioritization

**Risk Factor Weights (Served as a guide, not a standard.)**
	Category
			Higher Confidence
			Lower ConfidenceCrash Over-representation
			> 10%
			≤10%Crash Total
			≥ 30%
			< 30%Weight
			1 point
			0.5 pointReturn to top

**Risk Factor Prioritization Results**
	ID
			Risk Factor
			1 Point Range
			1⁄2 Point Range01
			Federal/Functional Classification
			Major Rural Collector
			Urban Minor Arterial02
			Intersection
			Yes
			–03
			Vertical Curves
			–
			Yes04
			Visual Trap
			–
			Yes05
			Edge Risk Assessment Rating = 3
			Yes
			–06
			Paved Shoulder Width
			> 4 feet
			–07
			Average Daily Traffic
			3,000-7,500
			0-1,50008
			Speed Differential (native shoulders)
			–
			0 to 5 mph
			Width < 4 feet at 25 mph09
			Speed Differential (paved shoulders)
			–
			20 mph10
			Type of Advance Warning Sign
			–
			W1-5In a systemic review of road departure crashes on horizontal curves, Thurston County prioritized their selected risk factors by weighting them based on their level of confidence in the data representing that risk factor. Using the results of the descriptive statistics analysis performed on the potential risk factors, those factors present in at least 30 percent of the severe crashes and overrepresented by at least 10 percentage points (when comparing the proportion of all locations with the proportion of severe crash locations) were considered to have a high confidence and were assigned a weighted value of one point in the risk assessment process. Of the risk factors that were selected but did not meet these criteria, Thurston County had a lower confidence in them and each was assigned a relative weight of one-half point. The Risk Factor Weights table summarizes these criteria. This prioritization was used as a guideline, not a strict standard, for assigning weights to risk factors. The Risk Factor Prioritization Results table summarizes the results of the weighting process for the ten risk factors selected by Thurston County.

The final result of Task 3 is a prioritized list of focus facility elements that represents the locations with the greatest potential for the focus crash type to occur. At a minimum, the list includes information about the element location and the risk assessment score. Example 8 shows the eight horizontal curves on the Thurston County Rural Major Collector system that have the highest risk scores and, therefore, represent the highest priority locations for systemic safety improvements. This list shows the value of systemic safety planning—more than half of these locations with risk factors present do not have a documented severe crash. However, the risk assessment indicates these locations have common characteristics with locations where severe crashes have occurred and, therefore, have the potential for a future severe crash.

Outcome

The outcome of this step is a risk assessment and ranking of the focus facility elements. The elements of the focus facilities carried forward to the next phase represent the locations with greatest potential for safety improvement.

Answering Some Common Concerns

**Q: What if I do not have enough data to either document the characteristics of locations with crashes or to conduct the risk assessment of focus facilities?**

A: The key objective of this step is to determine whether one part of a system is more at risk than another, which might require only one or two risk factors which could be based on data readily available, such as number of lanes or roadway curvature.

**Q: How do I know if the characteristics I select really represent an increased level of risk?**

A: Three keys to improve the success of your program include (1) be evidence driven [descriptive statistics and CMFs] in your selection of risk factors and consistent in their application, (2) exercise your judgment and conduct annual follow-up evaluations to see how the process is working, and (3) make adjustments if and when necessary.

**Q: How many locations should I select in my initial prioritized list?**

A: You can determine exactly how many locations to select for your initial prioritized list using factors such as anticipated funding amount and implementation goals. If your initial threshold identifies too few locations, then add locations in their established priority order until the target funding level is reached.

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EXAMPLE 8. Thurston County Public Works Results of Segment Prioritization for Focus Facility Type Based on Risk Factor Scoring

These eight horizontal curves on the Thurston County Rural Major Collector system have the highest risk scores and, therefore, represent the highest priority locations for systemic safety improvements. This list shows the value of systemic safety planning – more than half of these locations with risk factors present do not have a documented severe crash.

**Horizontal Curves of Highest Priority Locations for Systemic Safety Improvements**
	Curve ID
			Road Name
			Scoring
			5-year Crash Rate
			Fatal or Serious Crash182
			Hawks Prairie Road NE
			6.5
			1.2
			Yes194
			Boston Harbor Road NE
			6.0
			1.1
			No143
			Delphi Road NW
			6.0
			0.9
			No203
			Johnson Point Road NE
			5.5
			0.4
			No202
			South Bay Road NE
			5.5
			0.2
			No136
			Waddell Creek Road SW
			5.5
			10.3
			Yes238
			Morris Road SE
			5.5
			2.6
			Yes58
			Bald Hill Road SE
			5.5
			7.2
			NoSource: Thurston County, Washington, Department of Public Works

Select Countermeasures

Objective

The objective of the third step in the systemic safety planning process is to assemble a small number of low-cost, highly effective countermeasures to be considered for project development at candidate locations. The countermeasures are selected based on research related to the systemwide data analysis results from the first step (Identify Focus Crash Types and Risk Factors), and specific jurisdictional experience, policies, and practices regarding potential countermeasures.

Data Needs

The National Cooperative Highway Research Program (NCHRP) Report 500 series is a suggested source of information for assembling the initial list of safety countermeasures (TRB, Various). These 24 volumes provide an extensive list of countermeasures for each of AASHTO's safety emphasis areas plus they provide insight about implementation costs. Recent countermeasure effectiveness information is available in the HSM and the CMF Clearinghouse. The National Highway Safety Traffic Administration's (NHTSA's) Countermeasures That Work report provides effectiveness information about behavioral countermeasures (NHTSA, 2013). These resources provide information about the expected effectiveness of the countermeasures, and documentation of implementation and maintenance costs. Other information needed to support countermeasure selection is gathered from the crash, roadway, and traffic data assembled in the previous two steps.

The information documented for the countermeasures might indicate whether the countermeasure is proven or tried, the expected safety effectiveness of the countermeasure, estimated implementation and maintenance costs, and consistency with agency policies and practices. In addition to assisting with countermeasure selection, this information is useful to the safety planning process because it provides:

Documentation of proven, effective, or tried countermeasures which support a level of confidence about forecasted crash reductions.
	Effectiveness measures which assist in computing an expected crash reduction associated with deployment across a system.
	Implementation costs which are critical in the safety investment decision-making process.
	A final check of deployment feasibility in relation to agency policies and practices.**FIGURE 6. Systemic Safety Planning Process: Tasks to Select Countermeasures**

Figure 6 - Diagram - Figure 6 presents the cyclic four-step systemic safety planning process. The four steps are Identify Focus Crash Types & Risk Factors, Screen & Prioritize Candidate Locations, Select Countermeasures, and Prioritize Projects. The third step, Select Countermeasures, is expanded to include three tasks. Task 1 is, "Assemble Comprehensive List of Countermeasures". Task 2 is, "Evaluate/Screen Countermeasures". Task 3 is, "Select Countermeasures for Deployment".

Process

Countermeasure selection involves assembling a comprehensive list of potential countermeasures and evaluating each countermeasure to determine a select few most appropriate for systemic deployment. Figure 6 shows the three primary tasks conducted to define the safety countermeasures for implementation at the candidate locations.

Task 1: Assemble Comprehensive List of Countermeasures

Task 1 involves assembling a comprehensive list of the safety countermeasures associated with each focus crash type. The list is assembled after reviewing the latest research and other available information (e.g., agency experience or engineering judgment) to identify those countermeasures with the greatest potential to address the focus crash types. As previously mentioned, the NCHRP Report 500 series, HSM, and CMF Clearinghouse are suggested starting points for the research effort. A state SHSP or other local safety plans also might include countermeasures already defined for particular focus crash types. Other resources, such as FHWA's illustrated guide sheets for 77 intersection countermeasures, may be used for developing the initial list of countermeasures (FHWA, Office of Safety). An agency's existing maintenance program could also be a source for identifying potential countermeasures. For example, a countermeasure could be to replace missing or damaged traffic signs with signs that meet current retroreflectivity standards. The MnDOT Case Study provides an illustration of the process to assemble a comprehensive list of countermeasures.

Task 2: Evaluate and Screen Countermeasures

The second task in the countermeasure selection process is to evaluate and screen the initial list of countermeasures based on documented safety effectiveness at reducing the focus crashes, implementation and maintenance costs, and consistency with the agency's policies, practices, and experiences. Implementing countermeasures that are proven to be effective at reducing crashes provides agencies the highest possible level of confidence that their investment will have a positive outcome—a reduction in the focus crashes. The HSM and the CMF Clearinghouse provide the most current information about countermeasure effectiveness. Evaluation results from previous countermeasure implementation efforts (discussed in Element 3 of the Systemic Safety Project Selection Tool) offer additional critical information for evaluating and selecting future countermeasures. The key is to follow the evidence and select the countermeasures with the greatest potential to address the focus crash type not just at a single location, but across the prioritized focus facility elements.

Helpful Hints and Other Considerations

**Should I seek input from others when screening countermeasures?**

To generate awareness of the systemic safety planning process and support among safety partners, you may conduct safety workshops during this task. Agency staff representing Engineering, Enforcement, Emergency Medical Services, and Driver Education could participate in a day-long workshop focused on sharing information about the process to select target crash types, and then discussing and prioritizing safety countermeasures. Also, within the engineering group, experts beyond just traffic and safety (e.g., construction, maintenance, public affairs representatives) should be involved.

**Is safety effectiveness the only issue to consider when evaluating countermeasures?**

An equally important consideration in the process of screening the countermeasures is the implementation and maintenance cost. The systemic approach is focused on mitigating types of crashes that are widely scattered across a roadway system. The key to addressing low crash densities is implementing low-cost countermeasures, so that resources are adequate to widely deploy them across a system. Furthermore, policies and practices might limit the ability to use some countermeasures such as automated enforcement. The practical ability to implement a countermeasure equally influences the screening process.

**Is there an optimum number of countermeasures for my agency's short list?**

Not really—too few countermeasures can limit flexibility to address the various conditions and constraints that are typical across a roadway system. Too many countermeasures can make project development more challenging and follow-up evaluations more difficult (too few samples of any one countermeasure to provide statistical reliability).

**Why would I want to remove countermeasures from the list?**

In many cases, there are simply too many potential countermeasures to discuss in any meaningful way at a stakeholder meeting or workshop. There are going to be some countermeasures that are just not consistent with an agency's practices and should be removed before investing time and energy to discuss further.

**Are the CMFs developed for specific high-crash locations applicable to a systemic implementation?**

While CMFs in the CMF Clearinghouse present the best information available to date, it is important to recognize that most CMFs were developed from before-after studies conducted when the countermeasure was implemented at a high-crash location. However, it is unknown whether the same results will be achieved when implementing these countermeasures on a systemic basis. Because systemic countermeasures are deployed at some locations with no crash history, it is possible that a systemic application of a countermeasure may not achieve as high of an average percentage reduction in crashes as a high-crash location. Therefore, you are encouraged to conduct follow-up evaluations as described in Element 3 to determine the true effect of implementing safety countermeasures.

The screening process should consider maintenance requirements for the countermeasures because a countermeasure cannot perpetually provide the potential for crash reduction if it is not maintained or replaced when necessary. Thus, agencies should consider their ability to perform and fund routine maintenance of countermeasures implemented through a systemic deployment program. A countermeasure is likely not going to be a viable improvement and should be removed during the screening process if it will not be maintained. The MnDOT Case Study provides an illustration of how to evaluate and screen countermeasures.

Agencies can also screen potential countermeasures by performing a benefit-cost analysis of various countermeasures applicable for a typical section that represents the focus facility type. A spreadsheet tool is useful to automate the benefit-cost ratio calculations. Example 9 illustrates the benefit-cost analysis used to identify countermeasures for roadway departure crashes on bridges in Salem County, New Jersey. When performed in this manner, a benefit-cost analysis can help to determine the most cost-effective way to spend the funding allocated to systemic improvements.

Task 3: Select Countermeasures for Deployment

The result of the countermeasure screening process is the selection of one or more countermeasures for each focus crash type. This short list would include primarily low-cost countermeasures, along with a few higher-cost countermeasures. Agencies use this list of countermeasures to develop safety projects at specific locations across their roadway system. Although an agency might choose to deploy one particular countermeasure, there might also be locations where that countermeasure is not an ideal choice. As a result, having alternatives to choose from provides flexibility and acknowledges that all candidate locations in a system are not the same. Additionally, including alternative countermeasures offers an opportunity to incorporate a few higher-cost countermeasures proven to significantly reduce crashes. Agencies should use these higher-cost countermeasures in a limited number of circumstances and only in situations that might not be effectively addressed by the low-cost countermeasures in the short list. The high-priority locations identified in the second step (Screen and Prioritize Candidate Locations) also might influence the final countermeasure selection, which is why it is important to identify a range of countermeasures appropriate for the range of high-priority sites selected for project development. The final selection represents the highest-priority countermeasures that agencies will maintain for safety investment, based on expected crash reductions and estimated implementation costs. The MnDOT Case Study provides an illustration of how to select countermeasures for deployment.

Outcomes

An outcome of this step is documentation of the countermeasures, which will be used in future program evaluation. The primary outcome of this step is a short list composed mainly of effective, low-cost countermeasures and a few higher-cost countermeasures for each focus crash type. These countermeasures then become the focus of the safety project development efforts that are described in the next step of the systemic safety planning process.

EXAMPLE 9. Rutgers Center for Advanced Infrastructure and Transportation Benefit Cost Analysis to Evaluate and Screen Countermeasures

**Countermeasure 2: Rumble Strips – Service Life: 3 years**
	Step
			Year – 2012 (Years in Service Life – 0)/Annual Average Daily Traffic – 1,400
			Year – 2013 (Years in Service Life – 1)/Annual Average Daily Traffic – 1,428
			Year – 2014 (Years in Service Life – 2)/Annual Average Daily Traffic – 1,457
			Year – 2015 (Years in Service Life – 3)/Annual Average Daily Traffic – 1,486
			Total Number of Crashes
			Total BenefitStep 1 WITHOUT Countermeasure Number of Crashes (Expected Before)
			Total
			0.0090
			0.0092
			0.0094
			0.0097
			0.0283
			–Step 1 WITHOUT Countermeasure Number of Crashes (Expected Before)
			Fatal and Injury
			0.0029
			0.0030
			0.0030
			0.0031
			0.0091
			–Step 1 WITHOUT Countermeasure Number of Crashes (Expected Before)
			Property Damage Only
			0.0061
			0.0063
			0.0064
			0.0066
			0.0092
			–Step 2 WITH Countermeasure Number of Crashes (Expected After)
			Total
			–
			0.0073
			0.0075
			0.0076
			0.0224
			–Step 2 WITH Countermeasure Number of Crashes (Expected After)
			Fatal and Injury
			–
			0.0016
			0.0016
			0.0016
			0.0048
			–Step 2 WITH Countermeasure Number of Crashes (Expected After)
			Property Damage Only
			–
			0.0063
			0.0064
			0.0066
			0.0192
			–Step 3 Change in Number of Crashes (Expected)
			Total
			–
			0.0019
			0.0020
			0.0020
			0.0059
			–Step 3 Change in Number of Crashes (Expected)
			Fatal and Injury
			–
			0.0014
			0.0014
			0.0015
			0.0043
			–Step 3 Change in Number of Crashes (Expected)
			Property Damage Only
			–
			0.0
			0.0
			0.0
			0.0
			–Step 4 Benefit and Maintenance Calculations
			Change in Number of Crashes (Fatal and Injury)
			–
			0.001391
			0.0
			0.0
			–
			–Step 4 Benefit and Maintenance Calculations
			Fatal and Injury Crash Cost
			–
			$158,200
			$158,200
			$158,200
			–
			–Step 4 Benefit and Maintenance Calculations
			Annual Maintenance Cost (Fatal and Injury)
			–
			$220
			$220
			$230
			–
			–Step 4 Benefit and Maintenance Calculations
			Change in Number of Crashes (Property Damage Only)
			–
			0.0
			0.0
			0.0
			–
			–Step 4 Benefit and Maintenance Calculations
			Property Damage Only Crash Cost
			–
			$7,400
			$7,400
			$7,400
			–
			–Step 4 Benefit and Maintenance Calculations
			Annual Maintenance Cost (Property Damage Only)
			–
			$0
			$0
			$0
			–
			–Step 4 Benefit and Maintenance Calculations
			Annual Maintenance Cost (Total)
			–
			$220
			$220
			$230
			–
			–Step 5 Present Value Calculation
			Present Value
			–
			$212
			$203
			$204
			–
			$619

**Cost/Benefit Ratio**
	Category
			Benefit
			(Net Present Value)
			Cost
			Benefit/
			Cost RatioGuiderail
			$1,685.55
			$4,200
			0.401Rumble Strips
			$619.41
			$126
			4.915Rumble Stripes
			$0.00
			$268
			0.0000Pavement Markings
			$813.67
			$284
			2.865Pavement Resurfacing
			$162.22
			$3,675
			0.044High-Friction Surfacing
			$1,171.71
			$1,386
			1.278Source: Rutgers CAIT Transportation Safety Resource Center

The Rutgers Center for Advanced Infrastructure and Transportation (CAIT) Transportation Safety Resource Center performed a systemic safety analysis for Salem County, New Jersey, to develop a prioritized list of HSIP-eligible projects. CAIT conducted a cost-benefit analysis of potential countermeasures selected based on identified risk factors. CAIT used safety performance functions (from the HSM predictive method procedures) and crash modification factors (from the CMF Clearinghouse) to estimate the difference between the expected number of crashes with and without the countermeasure (the benefit of implementing the countermeasure). After calculating the net present value of the implementation and maintenance costs, the automated process estimated the benefit-cost ratio of each countermeasure. The resultant prioritization of the countermeasures was used to create safety projects for sites with particular combinations of lane width and traffic volume.

Prioritize Projects

Objective

The objective of the fourth and final step in the systemic safety planning process is to identify and develop a list of high-priority safety improvement projects for implementation. This process considers the prioritized at-risk locations identified in the second step (Screen and Prioritize Candidate Locations) and applies the most appropriate countermeasures from the list developed in the third step (Select Countermeasures) to develop a list of high-priority safety improvement projects. For the purposes of the Systemic Tool, the term projects includes dedicated safety projects as well as safety improvements implemented as one component of a traditional construction or maintenance project (e.g., resurfacing) or as part of routine maintenance efforts.

Data Needs

The information needed to support the project prioritization process includes a basic understanding of an agency's priorities, practices, and policies as they relate to project and program development. This understanding is especially important to ensure the countermeasures identified in this step are only included in projects for areas where they fit with local practices for installation and maintenance. In addition, defining specific safety projects requires current information about countermeasure implementation costs and estimated effectiveness.

Process

Prioritizing projects involves developing a decision process so that selected countermeasures can be consistently assigned to projects for the prioritized focus facility elements identified in the second step. This fourth and final step results in a prioritized implementation order for safety projects. Figure 7 shows the three basic tasks conducted to prioritize systemic safety projects.

**FIGURE 7. Systemic Safety Planning Process: Tasks to Prioritize Projects**

Figure 7 - Diagram - Figure 7 presents the cyclic four-step systemic safety planning process. The four steps are Identify Focus Crash Types & Risk Factors, Screen & Prioritize Candidate Locations, Select Countermeasures, and Prioritize Projects. The fourth step, Prioritize Projects, is expanded to include three tasks. Task 1 is, "Create Decision Process for Countermeasure Selection". Task 2 is, "Develop Safety Projects". Task 3 is, "Prioritize Safety Project Implementation".

Task 1: Create Decision Process for Countermeasure Selection

Creating a decision process for each focus crash type provides a means to consistently assign countermeasures to focus facility locations. A decision process is simply a set of criteria that considers issues such as volume, environment, adjacent land use, or cross-section, and uses them to identify the appropriate countermeasure for high-priority locations. An important distinction of the systemic safety planning process is that the decision-making process does not just identify the most appropriate countermeasure for each location (like when addressing hot spots), it also considers multiple locations with similar crash and risk characteristics to select preferred one or more countermeasures suitable and affordable for widespread implementation. Alternative countermeasures, and the criteria for deploying each countermeasure, might consider typical variations in site conditions.

For example, urban intersection and rural road departure systemic safety programs address uniquely different problems. Therefore, each program needs countermeasures specific to the problem and different decision processes for selecting the final countermeasure. Additionally, programs addressing similar issues on different facility types (e.g., road departure on rural divided expressways versus two-lane highways) might have some of the same countermeasures, but the criteria and thresholds for selecting the countermeasures might be completely different. An agency can develop a process recognizing that no single countermeasure is likely to be best for every location due to the variety of features and characteristics that are encountered along a roadway system. The MnDOT Case Study illustrates a decision tree created to select countermeasures.

A Quick Illustration: Addressing Road Departure Crashes on Rural Two-Lane Highways

Shoulder rumble strips may be the preferred countermeasure for addressing rural road departure crashes that happen due to driver inattention. Factors that might influence the actual decision to implement shoulder rumble strips at any given location include the shoulder surface type and width, lane width, and the presence of adjacent residential development. These factors could point to selecting an alternative countermeasure, such as edge-line rumble strips (also known as rumble stripes), if there is no paved shoulder and no noise concerns. An enhanced edgeline using a wider edgeline or wet-reflective material might be considered in the case of either really low-volume, narrow lanes with no paved shoulder or due to noise concerns in areas with residential development.

Criteria should also consider when any higher-cost alternatives are selected. In this same scenario, a higher-cost alternative could be paving shoulders with adding rumble strips. Criteria might suggest this as the preferred project if the gravel shoulder is sufficiently wide and the countermeasure is appropriate for the site conditions and agency practices. Other criteria for choosing a higher-cost countermeasure could include high volumes, a relative high frequency of severe road departure crashes, or a curvilinear alignment where recovery area outside the edgeline is viewed as important.

Task 2: Develop Safety Projects

The next task in the project prioritization process is to apply the decision process to identify one or more specific countermeasure for each candidate locations selected for safety investment. Safety projects are developed by providing a detailed site description (e.g., route number, mile point, intersecting roadway, and segment termini), identifying the specific countermeasure selected, estimating the implementation cost, and summarizing how the site scored with the risk factors. After the countermeasures for safety investments are selected, agencies can then decide how to most efficiently bundle projects into a design package for contract letting. The MnDOT Case Study shows an example of the documentation produced during the process to develop a safety project.

Task 3: Prioritize Safety Project Implementation

Lastly, projects are prioritized for implementation by considering factors such as funding, other programmed projects, time to develop project plans, expected crash reduction, amount of public outreach needed, and environmental and right-of-way constraints. The prioritized list of locations infers a particular order based on the number of risk factors present at a given location. However, other factors often influence the ability to let a specific project. For example, a project might need to be included in an established capital improvement program or coordinated with other projects/programs. The next chapter presents a case study that illustrates how MnDOT applied the systemic safety planning process to develop prioritized projects for deployment on the county roadway network throughout the state.

Outcome

The outcome for this step is development of a safety project for each identified at-risk candidate location along a roadway system. The roll-up of the prioritized projects produces the systemic safety program for the city, county, district, region, or state. This final step completes the systemic safety planning process, which is Element 1 of the Systemic Safety Project Selection Tool.

Answering Some Common Concerns

**Q: I have selected a preferred countermeasure to mitigate the focus crash type and now I find that I cannot implement this countermeasure at a particular location (e.g., due to a lack of support by maintenance crews, complaints by residents, lack of support by local politicians, geometric constraints). What do I do?**

A: You should have multiple countermeasures identified, which will provide flexibility to adapt to the many constraints and/or features that are typical across roadway systems. The decision process should account for such issues by providing alternative countermeasures.

**Q: If I have a list of suggested safety projects in my possession and I choose not to implement some, either immediately or ever, am I at risk from a tort liability perspective?**

A: This question comes up regularly in conversations with local agencies. Agencies should have clear documentation of the process used to identify and prioritize safety investments. Tort law in a number of states provides agencies with discretionary immunity related to decisions about the allocation of resources. In addition, federal law (23 U.S.C. 409) and a U.S. Supreme Court case (Pierce County, Washington v. Guillen) protects agencies participating in statewide safety planning efforts that support the HSIP by shielding the outcomes of those efforts from plaintiff's attorneys; the information generated (e.g., data, lists of at-risk facilities, lists of suggested projects) is not discoverable and cannot be used against an agency in tort cases. Agencies should seek legal counsel to determine the extent of protection provided by these Federal statutes.

**Q: The process has identified more projects than there are funds available—is this a problem?**

A: No, systemic safety planning is not expected to be fiscally constrained. It is desirable to identify more projects than could be implemented in a single year because funding agencies will have a multiyear backlog of high-priority projects (and will not need to perform annual analysis updates). A good target would be to assume a of 3- to 5-year shelf life for the results of the analytical process, after which the process would be updated.

**Q: Can I use HSIP funds to supplement regular funding sources for reconstruction?**

A: Federal regulation (23 CFR 924.5) states that improvements to safety features that are routinely provided as part of a broader federal-aid project should be funded from the same source as the broader project. States should address the full scope of their safety needs and opportunities on all roadway categories by using all available funding sources. For example, if an improvement project identified through the HSIP planning and programming process encompasses an area identified through the systemic planning process a location for safety improvements, it makes logical sense to combine the two efforts to reduce the cost of two projects (less administration, only one mobilization cost, etc.).

**Q: My high-priority segments, curves, and intersections are listed in a very specific rank order. Do the suggested safety projects need to be implemented in that exact order?**

A: No, the prioritization process results in a rank ordering of the system based on a comparison to the adopted risk factors. However, a variety of factors (i.e. cost effectiveness) likely will enter into an agency's decision as to how projects will fit into their capital improvement program. Agencies would benefit from a systemic prioritization process that considers these other factors to the extent feasible.

Case Study: Minnesota Department of Transportation's Application of the Systemic Safety Planning Process

The following case study illustrates how the Minnesota DOT applied the systemic safety planning process as part of a statewide effort to develop county road safety plans for each of their 87 counties. The focus crash types were severe lane departure crashes on rural segments and curves, severe right-angle crashes at rural thru-stop and urban signalized intersections, and severe pedestrian crashes in urban areas. The FHWA's HSIP Noteworthy Practice Series provides information about this effort (FHWA, Office of Safety). The FHWA's Developing Safety Plans: A Manual for Local Rural Road Owners provides guidance for developing local road safety plans (FHWA, 2012). The case study provides illustrations of each successive task of the systemic safety planning process, using the same data set throughout. Each illustration describes the purpose, provides a description, and typically shows example data and analysis results.

Identify Focus Crash Types and Risk Factors – Task 1: Select Focus Crash Types – Crash Data for All Public Roads

**Crash Data**
	Emphasis Area
			Statewide Percentage
			Statewide – State System (Percentage)
			Statewide – State System
			Statewide – County System (Percentage)
			Statewide – County System
			Statewide – City, Township, & Other System (Percentage)
			Statewide – City, Township, & Other SystemTotal Fatal and Serious Injury Crashes
			8,300
			–
			2,998
			–
			3,379
			–
			1,923Drivers – Young drivers (under 21)
			24% (Top 5 Emphasis Area by Jurisdiction)
			21%
			638
			25% (Top 5 Emphasis Area by Jurisdiction)
			839 (Top 5 Emphasis Area by Jurisdiction)
			28% (Top 5 Emphasis Area by Jurisdiction)
			539 (Top 5 Emphasis Area by Jurisdiction)Drivers – Unlicensed drivers
			8%
			8%
			251
			7%
			237
			9%
			164Drivers – Older drivers (over 64)
			14%
			18%
			527
			13%
			429
			11%
			206Drivers – Aggressive driving and speeding-related
			20%
			20%
			606
			20%
			661
			22% (Top 5 Emphasis Area by Jurisdiction)
			432 (Top 5 Emphasis Area by Jurisdiction)Drivers – Drug and alcohol-related
			26% (Top 5 Emphasis Area by Jurisdiction)
			23% (Top 5 Emphasis Area by Jurisdiction)
			680 (Top 5 Emphasis Area by Jurisdiction)
			26% (Top 5 Emphasis Area by Jurisdiction)
			949 (Top 5 Emphasis Area by Jurisdiction)
			26% (Top 5 Emphasis Area by Jurisdiction)
			497 (Top 5 Emphasis Area by Jurisdiction)Drivers – Inattentive, distracted, asleep drivers
			20%
			23% (Top 5 Emphasis Area by Jurisdiction)
			693 (Top 5 Emphasis Area by Jurisdiction)
			19%
			638
			16%
			300Occupants – Unbelted vehicle occupants
			25% (Top 5 Emphasis Area by Jurisdiction)
			26% (Top 5 Emphasis Area by Jurisdiction)
			782 (Top 5 Emphasis Area by Jurisdiction)
			26% (Top 5 Emphasis Area by Jurisdiction)
			872 (Top 5 Emphasis Area by Jurisdiction)
			21%
			400Special Users – Pedestrian crashes
			8%
			6%
			180
			7%
			222
			15%
			291Special Users – Bicycle crashes
			4%
			2%
			54
			3%
			113
			8%
			157Vehicles – Motorcycle crashes
			16%
			14%
			416
			17%
			591
			15%
			293Vehicles – Heavy vehicle crashes
			10%
			15%
			456
			7%
			249
			6%
			114Highways – Train-vehicle crashes
			0%
			0%
			1
			0%
			7
			1%
			17Highways – Road departure crashes
			28% (Top 5 Emphasis Area by Jurisdiction)
			27% (Top 5 Emphasis Area by Jurisdiction)
			807 (Top 5 Emphasis Area by Jurisdiction)
			32% (Top 5 Emphasis Area by Jurisdiction)
			1,090 (Top 5 Emphasis Area by Jurisdiction)
			22% (Top 5 Emphasis Area by Jurisdiction)
			420 (Top 5 Emphasis Area by Jurisdiction)Highways – Intersection crashes
			42% (Top 5 Emphasis Area by Jurisdiction)
			40% (Top 5 Emphasis Area by Jurisdiction)
			1,212 (Top 5 Emphasis Area by Jurisdiction)
			42% (Top 5 Emphasis Area by Jurisdiction)
			1,422 (Top 5 Emphasis Area by Jurisdiction)
			45% (Top 5 Emphasis Area by Jurisdiction)
			871 (Top 5 Emphasis Area by Jurisdiction)Highways – Head-on and Sideswipe (opposite) crashes
			15%
			17%
			51
			14%
			489
			14%
			263Highways – Work zone crashes
			2%
			2%
			69
			1%
			38
			1%
			20Note: Numbers are not additive, as one crash may involve a young driver at an intersection. The numbers represent severe crashes (Fatal and A-type Injury crashes).

Source: Department of Public Safety Crash Data Records, 2006 to 2010

Purpose

Identify the high-priority emphasis area – categories of severe crashes that represent the greatest opportunities for reduction.

Description

Demonstrates disaggregation of Minnesota's statewide crash data into AASHTO's designated emphasis areas.
	In this case, the data suggests Minnesota's high-priority emphasis areas (focus crash types) include:
	Drivers
		Seatbelt usage
			Impaired driving
			Young drivers
		Highways
		Intersections
			Road departure
	The data also supports the importance of actively including the county highway system in statewide safety planning efforts.Identify Focus Crash Types and Risk Factors – Task 2: Select Focus Facilities – Crash Tree for All Public Roads

Crash Tree for All Public Roads - This crash tree breaks down the type and location of crashes in a five-year period.

Purpose

Identify where crash types most frequently occur.

Description

This is a crash tree analysis focusing on the county highway system in Minnesota.
	Analysis shows there are more severe crashes on the county system than the state system, and the majority of these crashes are rural, involve road departure, and occur on curves more than 50 percent of the time.
	Rural intersection crashes primarily occur at thru-stop controlled intersections. The most common crash type is a right-angle crash.
	Urban intersection crashes primarily occur at signalized intersections. The most common crash type is a right-angle crash.
	This chart provided a reasonable preview of the likely outcome of the safety analysis – the safety focus of Minnesota's County Roadway Safety Plans has been rural, road departure, curves, and angle crashes at intersections.Identify Focus Crash Types and Risk Factors – Task 3: Identify and Evaluate Risk Factors – Risk Factor Identification

Road Features

Shoulder Width/Type
	Horizontal Curvature
	Access Density
	Roadside Rating
	Intersection SkewTraffic Volume

Average Daily Traffic (ADT)Other Features

Presence of Commercial Development
	Proximity to Rail Crossing
	Distance from Previous Stop
	Operating Speed**Potential Risk Factors for Facilities**
	Facility
			Potential Risk FactorsRural Segments
			ADT, curve density, access density, edge ratingRural Curves
			ADT, radius, intersection, visual trapRural Intersections
			ADT, geometry, RR crossing, commercial development, distance from previous stopUrban Signals
			Speed, geometry, commercial developmentData screened by:

Agency Experience
	AvailabilityPurpose

Identify roadway characteristics to use as an initial set of potential risk factors to be further evaluated for use in systemic network screening.

Description

MnDOT reviewed published research to identify roadway features strongly related to crash experience. MnDOT compared these findings to available data and identified potential crash risk factors to apply to:
	Two-lane rural county highways
		Rural horizontal curves
		Rural thru-stop intersections
		Urban signalized intersections – focus on angle and pedestrian crashes
	The potential risk factors for each facility type selected by MnDOT are shown in the bottom table.Identify Focus Crash Types and Risk Factors – Task 3: Identify and Evaluate Risk Factors – Evaluation of Segment Traffic Volume as a Potential Risk Factor

**Road Departure Crashes**

Bar Graph - This bar graph evaluates ADT as a risk factor for road departure crashes.

Purpose

Use descriptive statistics to evaluate Average Daily Traffic (ADT) as a potential risk factor.

Description

600-1,200 ADT was selected as a risk factor because severe crashes were overrepresented on roadways with ADTs in this range.

Identify Focus Crash Types and Risk Factors – Task 3: Identify and Evaluate Risk Factors – Evaluation of Access Density as a Potential Risk Factor

**Crash Rate for Minnesota State Highways Based on Access Density**

Graph - This graph displays Crash Rate as a function of Access Density. There two main series and three subcategory series. Rural highways and Urban highways are the main series, with 2-lane conventional, 4-lane conventional, and Expressway as the subcategory series. For all series, as access density increases, crash rate increases as well. The maximum observed access density for rural highways is significantly smaller than that for urban highways, with the median number of access densities at 8 for Rural highways and 28 for Urban highways.

**Crash Rate for Rural Minnesota County Roadways Based on Access Density**

Graph - This graph displays two sets of data: Crash Rate as a function of Access Density per Mile, and Proportion of Focus Facility Roadway System (percent) as a function of Access Density per Mile. Density per Mile ranges from less than two to greater than 20. The Proportion of Focus Facility Roadway System exhibits a bell curve-like trend, peaking between 8 and 10 accesses per mile. 25% of the accesses statewide fall within this range. The crash rate exhibits a general upward trend as access density increases, with the exception of the lowest Access Density per Mile between zero and two, which demonstrates a high crash rate. The average crash rate is 0.85.

Purpose

Evaluate access density as a potential risk factor.

Description

Illustrates macro analysis showing that as access density increases, crash rates increase.
	Shows significant relationship between density and crash rate – risk factor selected for systemic network screening.Identify Focus Crash Types and Risk Factors – Task 3: Identify and Evaluate Risk Factors – Evaluation of Edge Risk Assessment as a Potential Risk Factor

**1 – Good Shoulder, Good Clear Zone**

Photograph - Photograph displaying a rural two-lane highway with a useable composite shoulder and a large, relatively flat clear zone.

**2 – Good Shoulder, No Clear Zone**

Photograph - Photograph displaying a rural road with a useable paved shoulder but no clear zone, considering a steep slope and trees near the shoulder.

**2 – No Shoulder, Good Clear Zone**

Photograph - Photograph displaying a rural two-lane highway with no shoulder but a large, usable clear zone.

**3 – No Shoulder, No Clear Zone**

Photograph - Photograph displaying a rural two-lane highway with no useable shoulder and no useable clear zone, considering a steep slope, trees, and roadside rock cliff.

Identify Focus Crash Types and Risk Factors – Task 3: Identify and Evaluate Risk Factors – Evaluation of Edge Risk Assessment as a Potential Risk Factor

Graph - This graph displays Severe Road Departure Density and Rate as a function of Risk Rating. There are three risk ratings, with 1 being the lowest and 3 the highest (these correspond to the photographs). All three demonstrate approximately equal severe road departure densities around 0.044 crashes per mile. Risk Ratings 1 and 2 demonstrate low severe road departure rates of 0.005 and 0.007 crashes per million vehicle miles of travel, with rating 3 demonstrating a tenfold increase with a severe road departure rate of 0.071.

Purpose

Use descriptive statistics to evaluate edge risk assessment as a potential risk factor.

Description

Severe road departure density is the number of crashes per mile per year, which illustrates the frequency of these crashes.
	The crash rate is the number of crashes normalized by vehicle miles traveled, indicating the relative risk based on exposure.
	Shows that a roadside condition of no usable shoulder and the presence of fixed objects (Risk Rating = 3) generates a higher severe road departure rate.Screen and Prioritize Candidate Locations – Task 1: Identify Network Elements to Analyze

**Network Elements to Analyze**
	Corridor
			Route Type
			Route Number
			Start
			End
			Length (miles)
			Average Daily Traffic144.01
			CNTY
			89
			CSAH-30
			CSAH-30
			1.4
			48040.04
			CSAH
			40
			New London Corp Limit
			CSAH-2
			5.9
			450131.01
			CNTY
			89
			CSAH-30
			MNTH-23
			0.7
			1459.02
			CSAH
			9
			CR-90, Willmar Corp Limit
			CSAH-10
			5.6
			9405.06
			CSAH
			5
			150th Ave NW, CSAH-29
			CSAH-1
			10.1
			62831.02
			CSAH
			31
			New London Corp Limit
			MNTH-23
			1.6
			9208.01
			CSAH
			8
			Renville County Line
			Lake Lillian Corp Limit
			3.6
			7504.01
			CSAH
			4
			CSAH-8
			CSAH-20
			6.7
			3202.05
			CSAH
			2
			CSAH-10
			MNTH-23
			9.8
			3854.04
			CSAH
			4
			CR-98
			CSAH-40
			2.4
			29038.01
			CSAH
			38
			CSAH-40
			CSAH-48
			2.1
			130132.01
			CNTY
			89
			CSAH-8
			CSAH-8
			2.2
			19042.01
			CSAH
			42
			CSAH-7
			County Line
			0.5
			1209.03
			CSAH
			9
			CSAH-10
			CSAH-40, Redwood Street
			4.9
			1,80025.01
			CSAH
			25
			CSAH-5
			USTH-71
			3.2
			1,3151.03
			CSAH
			1
			MNTH-23
			Pennock Corp Limit
			7.0
			333116.02
			CNTY
			89
			CSAH-3
			MNTH-40
			7.0
			982.04
			CSAH
			2
			Atwater Corp Limit
			CSAH-10
			6.7
			1,01828.02
			CSAH
			28
			CSAH-2
			County Line
			2.0
			315This table represents 19 of the 77 segments.

Purpose

Identify the network elements from the focus facility types which represent the locations where the focus crash types tend to occur. The elements are for use in network screening.

Description

For the application of the Systemic Safety Planning Process on corridors, the Minnesota process split corridors into segments with consistent design features (e.g., cross section or volume) to minimize the variation of risk factors within a corridor and so that the same countermeasure could be applied to the entire segment.
	The end points of the segments also considered practical issues about how projects could be deployed. Segments typically ended at the edge of cities since the preferred countermeasure, shoulder and edgeline rumble strips, could not be deployed within cities.
	The table on this page illustrates the results of segmentation of Minnesota 2-lane county roads.Screen and Prioritize Candidate Locations – Task 2: Conduct Risk Assessment

**Ranked Risk Assessment**
	Rank
			Corridor
			ADT Range
			Road
			Departure Density
			Access Density
			Curve Critical
			Radius Density
			Edge Risk
			Totals1
			144.01
			one star
			one star
			one star
			one star
			one star
			five stars2
			40.04
			one star
			one star
			one star
			one star
			one star
			five stars3
			131.01
			–
			one star
			one star
			one star
			one star
			four stars4
			9.02
			one star
			one star
			one star
			one star
			–
			four stars5
			5.06
			one star
			one star
			one star
			one star
			–
			four stars6
			31.02
			one star
			one star
			one star
			one star
			–
			four stars7
			8.01
			one star
			one star
			–
			–
			one star
			three stars8
			4.01
			–
			one star
			one star
			–
			one star
			three stars9
			2.05
			–
			–
			one star
			one star
			one star
			three stars10
			4.04
			–
			–
			one star
			one star
			one star
			three stars11
			38.01
			–
			–
			one star
			one star
			one star
			three stars12
			132.01
			–
			–
			one star
			one star
			one star
			three stars13
			42.01
			–
			–
			one star
			one star
			one star
			three stars14
			9.03
			–
			one star
			one star
			one star
			–
			three stars15
			25.01
			–
			one star
			one star
			one star
			–
			three stars74
			1.03
			–
			–
			–
			–
			–
			–75
			116.02
			–
			–
			–
			–
			–
			–76
			2.04
			–
			–
			–
			–
			–
			–77
			28.02
			–
			–
			–
			–
			–
			–This table represents 19 of the 77 segments.

Purpose

Evaluate the risk factors of the systems and locations selected for analysis using roadway and traffic characteristics in order to rank/prioritize at-risk locations.

Description

Risk factors are not weighted.
	A star indicates the corresponding risk factor is present.
	More stars identify locations as higher priority candidate for safety investment.Screen and Prioritize Candidate Locations – Task 2: Conduct Risk Assessment – Determine Feasibility of Selected Risk Factors

**Greater Minnesota Segment Risk Factors**

Graph - This graph displays the Crash Density and Proportion of Focus Facility Roadway System against the presence or absence of five Risk Factors: Average Daily Traffic, Road Departure/Lane Departure Density, Access Density, Curve Radius, and Edge Risk Assessment. For all Risk Factors the Crash Density is higher with the presence of the risk factor than without it. For Access Density the difference is only slight, whereas for Road Departure/Lane Departure Density there is a fourfold difference.

Purpose

Assess selected risk factors to determine their feasibility for differentiating between elements (curves, segments, and intersections) on the focus facility type.

Description

The line representing the percent of focus facility locations with the risk factor present indicates that the risk factors generally appear in 20 to 30 percent of focus facility type segments.
	MnDOT concluded these percentages are high enough to distinguish between segments, but not so high that most or all segments had the risk factor present (making it difficult to distinguish between segments for prioritization purposes.)
	Additionally, the bars representing segments with the risk factors present show a higher severe lane departure crash density than segments without the risk factor.Screen and Prioritize Candidate Locations – Task 3: Prioritize Focus Facility Elements – Threshold for Selecting Candidate Locations

Graph - This graph displays the Proportion of Focus Facility Roadway System and Crash Density as a function of the Stars Received. A roadway may receive between zero and five stars, with one star representing the presence of one risk factor. There are two Crash Density trends: Severe crash density and Severe lane departure crash density. 15% of the system received zero stars, 27% received one star, 28% received two stars, 18% received three stars, 9% received four stars, and 3% received five stars. Both Severe crash density and severe lane departure crash density exhibit increasing exponential trends as the number of Stars Received, or presence of risk factors, increases.

Purpose

Summarize the locations based on the number of risk factors present to establish a threshold for selecting candidate locations.

Description

The bars indicate the percent of the system that has the number of risk factors present (i.e., stars received). Additionally the chart shows that the severe crash density and severe lane departure crash density increases as more risk factors are present. MnDOT used this chart to determine that those locations with three or more stars present, approximately 30 percent of the focus facility type, would be candidate locations for systemic safety projects.

**Select Countermeasures**

Graphic - This graphic shows a group of countermeasures put through a sieve, with the outcome producing Countermeasures for Deployment. This metaphorically demonstrates that for any risk factor there are a number of countermeasures that may be implemented, but that care should be taken in selecting the best countermeasures to deploy. Countermeasures for Deployment can be grouped into four categories: Education Countermeasures, Engineering Countermeasures, Emergency Medical Service Countermeasures, and Enforcement Countermeasures.

Purpose

Review NCHRP 500 Reports, Highway Safety Manual, CMF Clearinghouse, FHWA Office of Safety website, and state Strategic Highway Safety Plans to identify a comprehensive list of potential countermeasures for each focus crash type.

Description

The key is to review the latest research and other available information to identify those countermeasures with the greatest potential to address the focus crash types.
	The countermeasures will be screened using:
	Crash data,
		Effectiveness,
		Cost, and
		Agency policies, procedures, and experience.
	The end result will comprise a short list of countermeasures for each focus crash type to use in development projects.Select Countermeasures – Task 1: Assemble Comprehensive List of Countermeasures – List of Potential Countermeasures

**List of Potential Countermeasures**
	Objectives
			Countermeasures
			Relative Cost to Implement and Operate
			Effectiveness
			Typical Timeframe for Implementation15.1 A: Keep vehicles from encroaching on the roadside
			15.1A1: Install shoulder rumble strips
			Low
			Tried
			Short (<1 year)15.1 A: Keep vehicles from encroaching on the roadside
			15.1 A2: Install edgelines “profile marking”, edgeline rumble strips or modified shoulder rumble strips on section with narrow or no paved shoulders
			Low
			Experimental
			Short (<1 year)15.1 A: Keep vehicles from encroaching on the roadside
			15.1 A3: Install midlane rumble strips
			Low
			Experimental
			Short (<1 year)15.1 A: Keep vehicles from encroaching on the roadside
			15.1 A4: Provide enhanced shoulder or delineation and marking for sharp curves
			Low
			Tried/Proven/Experimental
			Short (<1 year)15.1 A: Keep vehicles from encroaching on the roadside
			15.1 A5: Provide improved highway geometry for horizontal curves
			High
			Proven
			Long (>2 years)15.1 A: Keep vehicles from encroaching on the roadside
			15.1 A6: Provide enhanced pavement markings
			Low
			Tried
			Short (<1 year)15.1 A: Keep vehicles from encroaching on the roadside
			15.1 A7: Provide skid-resistance pavement surfaces
			Moderate
			Proven
			Medium (1-2 years)15.1 A: Keep vehicles from encroaching on the roadside
			15.1 A8: Apply shoulder treatments

			Eliminate shoulder drop-offs
				Shoulder edge
				Widen and/or pave shoulders
			Low
			Experimental
			Experimental
			Proven
			Medium (1-2 years)15.1 B: Minimize the likelihood of crashing into an object or overturning if the vehicle travels off the shoulder
			15.1 B1: Design safer slopes and ditches to prevent rollovers
			Moderate
			Proven
			Medium (1-2 years)15.1 B: Minimize the likelihood of crashing into an object or overturning if the vehicle travels off the shoulder
			15.1 B2: Remove/relocate objects in hazardous locations
			Moderate to High
			Proven
			Medium (1-2 years)15.1 B: Minimize the likelihood of crashing into an object or overturning if the vehicle travels off the shoulder
			15.1 B3: Delineate trees or utility poles with retroreflective tape
			Low
			Experimental
			Short (<1 year)15.1 C: Reduce the severity of the crash
			15.1 C1: Improve design of roadside hardware
			Moderate to High
			Tried
			Medium (1-2 years)15.1 C: Reduce the severity of the crash
			15.1 C2: Improve design and application of barrier and attenuation systems
			Moderate to High
			Tried
			Medium (1-2 years)Source: NCHRP 500 Volume 6 (2003)

Purpose

Assemble an initial comprehensive list of countermeasures associated with focus crash type.

Description

Initial list of countermeasures MnDOT identified to reduce road departure crashes using the NCHRP 500 Volume 6 report.

Select Countermeasures – Task 2: Evaluate/Screen Countermeasures – Countermeasure Effectiveness

**Proven**

Graduated drivers licensing
	Safety belt enforcement campaigns
	DWI checkpoints
	Street lights at rural intersections
	Access management
	Roadside safety initiatives
	Pave/widen shoulders
	Roundabouts
	Exclusive left turn signal phasing
	Shoulder rumble strips
	Improved roadway alignment
	Cable median barrier
	Removing unwarranted traffic signals
	Removing trees in hazardous locations
	Pedestrian crosswalks, sidewalk, and refuge islands
	Left turn lanes on urban arterials**Tried**

Rumble strips (on the approach to intersections)
	Neighborhood traffic control (traffic calming)
	Overhead red/yellow flashers
	Increased levels of intersection traffic control
	Indirect left turn treatments
	Restricting turning maneuvers
	Pedestrian signals
	Improve traffic control devices on minor intersection approaches**Experimental**

Turn and bypass lanes at rural intersections
	Dynamic warning devices at horizontal curves
	Static/dynamic gap assistance devices
	Delineating trees in hazardous locations
	Marked pedestrian crosswalks at unsignalized intersectionsSource: NCHRP 500 Reports

Purpose

Evaluate and screen the initial list of countermeasures based on documented effectiveness of reducing the focus crash types and consistency with the agency's policies, practices, and experiences.

Description

MnDOT used the NCHRP 500 reports to determine an initial estimate of effectiveness with their classification of each countermeasure as Proven (effective), Tried, or Experimental to narrow down the initial list of countermeasures.

Select Countermeasures – Task 3: Select Countermeasures for Deployment – Countermeasures Selected for Deployment

Countermeasures Selected for Deployment
	Objectives
			Countermeasures
			Relative Cost to Implement and Operate
			Effectiveness
			Typical Timeframe for Implementation15.1 A: Keep vehicles from encroaching on the roadside
			15.1 A1: Install shoulder rumble strips
			Low (<$10,000/mile)
			Proven (information updated by CH2M HILL)
			Short (<1 year)15.1 A: Keep vehicles from encroaching on the roadside
			15.1 A2: Install enhanced pavement markings, edgeline rumble strips or modified shoulder rumble strips on section with narrow or no paved shoulders
			Low (<$10,000/mile)
			Experimental/Tried
			Short (<1 year)15.1 A: Keep vehicles from encroaching on the roadside
			15.1 A3: Install centerline rumble strips
			Low (<$10,000/mile)
			Proven (information updated by CH2M HILL)
			Short (<1 year)15.1 A: Keep vehicles from encroaching on the roadside
			15.1 A4: Provide enhanced shoulder or delineation and marking for sharp curves
			Low (<$10,000/mile)
			Tried/Proven
			Short (<1 year)15.1 A: Keep vehicles from encroaching on the roadside
			15.1 A5: Provide improved highway geometry for horizontal curves
			High
			Proven
			Long (>2 years)15.1 A: Keep vehicles from encroaching on the roadside
			15.1 A8: Apply shoulder treatments

			Eliminate shoulder drop-offs
				Shoulder edge
				Widen and/or pave shoulders
			Moderate (information updated by CH2M HILL)
			Experimental
			Experimental
			Proven
			–15.1 B: Minimize the likelihood of crashing into an object or overturning if the vehicle travels off the shoulder
			15.1 B1: Design safer slopes and ditches to prevent rollovers
			Moderate to High (information updated by CH2M HILL)
			Proven
			Medium (1-2 years)15.1 B: Minimize the likelihood of crashing into an object or overturning if the vehicle travels off the shoulder
			15.1 B2: Remove/relocate objects in hazardous locations
			Moderate to High (information updated by CH2M HILL)
			Proven
			Medium (1-2 years)Source: NCHRP 500 Volume 6 (2003)

Purpose

Identify and select a few countermeasures for each focus crash type based on the evaluation of the countermeasures and consideration of agency priorities, practices, and policies.

Description

MnDOT paired down the list of countermeasures identified in Task 1 to address road departure crashes based on the evaluation. These countermeasures were selected to develop safety projects.

Prioritize Projects – Task 1: Create a Decision Process for Countermeasure Selection – Decision Tree

Tree Diagram – This decision tree considers the following factors: whether rumble strips are allowed, existing ADT, county treatment preference, existing shoulder surface type, and existing lane width. The recommended projects depending on the outcome of these factors include various rumble strips and striping options.

Purpose

Develop a decision process to facilitate consistency in the selection of countermeasures.

Description

Adapted from Minnesota County Road Safety Plan Project to represent a typical decision process for selecting roadway departure countermeasures on county roads.
	Utilizes Average Daily Traffic (ADT), lane width, and shoulder surface type to determine project type for rural 2-lane segments.Key Point

Provides county engineer with opportunity to identify treatment preferences while selecting projects that MnDOT is comfortable funding.

Prioritize Projects – Task 2: Develop Safety Projects – Safety Projects Selected for Development

**County Highway 26 from State Highway 23 to County Highway 15**

Table – One table on this page presents a summary of a project developed to address safety issues on County Highway 26. The information generally includes roadway data, 5-year crash data, the risk factors and assessment results, the short list of countermeasures considered, and the estimated implementation cost. The page also includes a table that summarizes by region the number of miles proposed for installation of five countermeasures. The installation of edge line rumble strips is proposed for 2,232 miles within the four regions.

Region
			2-ft Shoulder Pave, Rumble Strips, and Safety Edge (miles)
			Shoulder Rumble Strips (miles)
			Edgeline Rumble Strips (miles)
			6-inch Edgelines (miles)
			Ground in Wet-Reflective Markings (miles)
			Total Project Value1
			180
			373
			673
			50
			636
			$16,106,1072
			151
			147
			560
			210
			180
			$10,095,8683
			153
			91
			332
			46
			306
			$10,196,4284
			106
			139
			758
			200
			85
			$8,158,210Total
			591
			749
			2,323
			505
			1,207
			$44,556,613Purpose

Apply decision process to develop specific safety projects for each candidate site selected for safety investment.

Description

County Highway 26 Segment Project Form (left), provides information on:
	Roadway Data – Average Daily Traffic (ADT), length, lane width, shoulder width/type
		Crash Data – total and road departure crashes, density, rate
		Deficiencies – risk ranking
		Countermeasures Considered
		Selected Countermeasure
		Project Cost
	The table on this page provides regional summaries of the projects identified using the systemic process.Prioritize Projects – Task 3: Prioritize Safety Project Implementation – Project Prioritization Process

Flowchart – This flowchart demonstrates that the first step toward prioritizing projects is to conduct Risk Based Prioritization. Four other factors that may need to be considered as part of the project prioritization process include: existence of Other programmed Projects, required Time to Develop Project Plans, Available Funding, and Other Considerations.

Purpose

Identify the order in which projects will be implemented.

Description

Prioritizing the projects for implementation will start with the number of risk factors present at a given location. Several other factors may play a role in the selection process, such as funding availability, other programmed projects, time to develop project plans amount of public outreach needed, etc. For example, a lower priority project may be selected over a higher priority project if the location is in an established capital improvement program.

Summary

Element 1 of the Systemic Safety Project Selection Tool presents a general process for conducting systemic safety planning efforts, which is intended to complement an agency's site-specific analysis process—not replace it.

This systemic safety planning process involves four steps:

Identifying the problem by looking at systemwide data;
	Screening and prioritizing candidate locations across the network;
	Selecting relevant mitigating countermeasures most appropriate for broad implementation across those locations; and
	Prioritizing projects for implementation.The systemic safety planning process is a data-driven process that identifies the types of crashes which represent the greatest opportunity for substantially reducing the number of severe crashes, the locations that have the greatest potential for severe crashes but do not have a high crash history, and a short list of highly effective countermeasures. The systemic safety planning process is flexible. Any agency can adapt the tool to fit their needs, and this flexibility allows agencies to develop a process that leads to implementation within the constraints of their data availability, program requirements, staff capabilities, and funding. While there can be variation in the detail and time invested or specific actions conducted for each task, the ultimate goal is to direct low-cost, effective countermeasures where the greatest opportunities exist to prevent severe crashes and improve safety.
      
  Book traversal links for Element 1: The Systemic Safety Planning Process
      ‹ Introduction
                    Up
                    Element 2: A Framework for Balancing Systemic and Traditional Safety Investments ›
                
                Book:Systemic Safety Project Selection Tool
              Foreword
                Preface
                Introduction
                Element 1: The Systemic Safety Planning Process
                Element 2: A Framework for Balancing Systemic and Traditional Safety Investments
                Element 3: Evaluation of a Systemic Safety Program
                References
                Appendix U.S. DEPARTMENT OF TRANSPORTATION

**Federal Highway Administration**

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WASHINGTON, DC 20590

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