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FHWA Home / Safety / HSIP / Highway Safety Improvement Program Manual

3.0 Planning: Countermeasure Identification

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Identifying high-risk corridors, road segments, locations, etc., is a critical part of the road safety improvement analysis process; however, the analysis task is not complete until contributing crash factors are identified and appropriate, effective countermeasures are selected and prioritized.  The purpose of Unit 3 is to describe how to identify the factors or variables that contribute to crashes and countermeasures for preventing crashes and mitigating crash severity.

A common practice is to identify contributing crash factors through a post hoc analysis of all events, behaviors, and conditions preceding a crash to determine which specific events, behaviors, or conditions made the crash inevitable.  Another approach is to search a crash database to determine if certain factors, variables or sites are more prevalent in the crash data than in the normal driving population or in other locations.  An emerging approach is “naturalistic” studies where drivers and vehicles are monitored continuously to obtain objective information of the conditions preceding a crash.

For practical purposes, the analysis is typically conducted through an engineering study which may be supplemented by a road safety audit (RSA).  Engineering studies review recent crash data and existing roadway/‌intersection characteristics (i.e., geometry, control, sight distance, travel speeds, lane widths, etc.) to characterize crash data specific to the location of interest.  The studies are designed to accomplish four essential steps:  1) examine the crash data to develop an in‑depth analysis of the contributing crash factors; 2) conduct a field review; 3) identify alternative solutions or countermeasures; and 4) assess the effectiveness of individual and groups of countermeasures.  The unit describes these steps in more detail and concludes with a case study to demonstrate an application of the engineering study process.

3.1 Step 1 – Analyze the Data

A careful examination of the crash data will reveal contributing factors and patterns at sites and segments.  The review may examine individual crash reports or an aggregate of all the data.  It should result in:

Crash Type

After the unit of analysis (e.g., hot spot, road segment, corridor, etc.) has been identified, the data are further examined to determine the types of crashes occurring at those locations.  In some cases, a single crash type might be identified, such as rear-end collisions at specific intersections.  Other types of crash types include side-swipe, run-off-road, head-on, right-angle, left-turn, etc.

Figure 3.1 demonstrates an example of crash types for an intersection collision study.  It is obvious turning maneuvers and rear end crashes are important issues which need to be addressed at this particular intersection.

Figure 3.1 Crash Types at an Intersection

chart - Pie chart indicating typesof  crashes at an intersection by percentage (approach turn - 52%, rear end - 32%, broadside - 9%, sideswipe 6%, and fixed object 1%).

Just as identifying the high-risk locations does not complete the picture, focusing on solely the crash type may also be misleading.  For example, a large number of rear-end crashes may be due to misleading signage or short sight distance, but it also could be related to driver behavior.  Drivers may be distracted by a mixture of signs, billboards, etc., outside the vehicle or multitasking inside the vehicle (e.g., talking on cell phones, eating and drinking, etc.).  Also, drivers may not be giving a clear signal of their intent, such as when they approach a light and then slam on the brakes at the last second.

Contributing Crash Factors

Crash factors may be related to roadway geometrics, condition, etc.; human factors, such as driver/‌pedestrian/‌motorcyclist behavior; vehicle factors which contribute to crash avoidance and survivability; and environmental conditions such as snow, ice, rain, and wind.  Figure 3.2 illustrates an overall analysis of crash factors.  While these percentages may not hold true for any specific situation; they generally show human factors are a significant component in all crashes, but other factors, such as roadway factors, are related as well.  Engineers examine all crash factors to determine how human behavior and attributes can be affected by signage, roadway design, etc., to reduce crash risk.

Figure 3.2 Crash Factors

chart - The figure illustrates an overall analysis of crash factors.  While these percentages may not hold true for any specific situation; they generally show human factors are a significant component in all crashes but other factors, such as roadway factors, are related as well.

The Road Environment Factors in Figure 3.2 represent the surrounding environment, which includes both roadway factors and environmental factors.
The HSIP Manual focuses on addressing issues associated with roadway factors, but the others are important for developing a thorough understanding of the circumstances surrounding a crash.

Roadway Factors

The HSIP is focused primarily on roadway factors which may contribute to help avoid or mitigate the severity of crashes.  However, other factors may interact with roadway factors.  Figure 3.2 shows this interaction effect.  For example, 24 percent of crashes involve factors associated with both the roadway and road user behavior.

Roadway factors generally are grouped by the type of facility, including (but not limited to) interstates, freeways, intersections, rural highways, local roads, pedestrian facilities, and bicycle facilities.  Safety on different facilities varies because they are built to different standards and different types of activities occur on them.  Often simply knowing the type of facility provides an important safety indicator.  For example, intersections may involve a large number of conflicting vehicle movements, which increases the opportunity for incidents to occur.

Some of the roadway factors which may impact the safety of a particular facility include:

Human Factors

As Figure 3.2 shows, most crashes involve one or more human factors.  A host of behavioral factors are known to contribute to crashes.  Some factors are attributes of drivers themselves, while others are related to the behavior of drivers.  For example, advancing age is an unavoidable driver attribute, while driver intoxication is a behavioral choice.  Some of the human factors that contribute to crashes include:

Vehicle Factors

Vehicle design is a significant factor in road safety.  Tradeoffs between large and small vehicles are complex and not well understood because we typically only observe crashes after they happen (and not crashes which are avoided).  In general, newer vehicles have better safety equipment and performance characteristics than older vehicles, and larger vehicles afford more protection in a crash.

Motorcycles and large displacement vehicles (e.g., trucks and buses) involve crash factors different from passenger vehicles.  In both cases, crashes involving these vehicles tend to be more severe.  Although motorcycles are highly maneuverable, crashes involving motorcycles tend to be more severe due to the lack of protection and, in some cases, the operator’s behavior.  Trucks, on the other hand, have far less maneuverability, but provide a high degree of protection.  Crashes between a passenger vehicle and a large truck tend to result in injury to the passenger vehicle occupants rather than the truck driver.  The majority of these crashes are often attributable to driver error on the part of the passenger vehicle driver and not to the trucks’ maneuverability limitations.

Vehicle safety is generally approached from two perspectives:

  1. Crash Avoidance – Numerous factors are incorporated into vehicles to avoid crashes.  In general, the more maneuverable and agile a vehicle is the more likely it can avoid a crash.  Also light, compact, and low vehicles offer superior maneuverability compared to heavy, large, and tall vehicles.
  2. Crash Protection – Once a crash occurs, different vehicle factors become important (e.g., vehicle safety equipment, ability to absorb energy, etc.).

Environmental Factors

Environmental crash factors are usually weather-related and typically contribute to crashes through interactions with vehicle or driver-related factors, but sometimes these factors are responsible for crash occurrence.  The following environmental factors contribute to crashes.

Crash Pattern Analysis

Crash patterns should be identified through an analysis of the crash data for specific locations.  The crash patterns can be identified using a collision diagram, collision summary, field reviews, input from other disciplines, and other information.

When conducting a crash analysis, it is useful to create a summary table of the crashes that occurred during the study period.  The table could include a summary of the pavement conditions, crash type, lighting conditions, number of injuries or fatalities, and any other relevant information, such as driver-related facts (i.e., age, gender, restraint use).  The summary table can provide insight for identifying crash patterns.  An example collision summary is shown in Table 3.1.

Table 3.1 summarizes the date and time of each collision, the crash type, injuries, time of day (day or night), and the contributing cause reported by the law enforcement officer.  This summary can help identify any dominant crash types or prevailing conditions.  It may also be beneficial to summarize driver-related information such as age, gender, restraint use, level of impairment, etc.

As shown in Table 3.1, left turn collisions appear to be a significant problem at this intersection, comprising 60 percent of the crashes during the one-year time period shown.  In addition, it is sometimes helpful to compare site specific crash summaries to statewide averages to identify trends or overrepresentation.  In this case, there were no apparent trends in crashes occurring at night (27 percent) or on wet pavement conditions (13 percent).

Although a crash summary provides some insight on potential issues, the next step is to develop a collision diagram to better understand what is occurring on a study roadway segment or intersection.

Table 3.1 Intersection Collision Summary

STUDY PERIOD:  1/1/08-12/31/08

CITY:  Springfield

ROADWAY:  Center Street

COUNTY:  Orange

INTERSECTION:  Main Street

SOURCE OF DATA:  Local Law Enforcement

No.

Date

Time

Type

Ped
Bike

Fatal

Injuries

Property Damage

Day/
Night

Wet/
Dry

Contributing Cause

1

1/6/2008

7:30 p.m.

Left Turn

0

0

1

$2,500

Night

Dry

FTYROW*

2

1/21/2008

12:15 p.m.

Rear End

0

0

2

$1,500

Day

Dry

Followed too Closely

3

2/6/2008

2:30 p.m.

Left Turn

0

0

1

$3,000

Day

Dry

FTYROW

4

4/1/2008

4:50 p.m.

Angle

0

0

0

$2,000

Day

Dry

FTYROW

5

4/20/2008

8:25 p.m.

Left Turn

0

0

0

$2,500

Night

Dry

FTYROW

6

5/16/2008

5:30 p.m.

Rear End

0

0

2

$1,000

Day

Wet

Followed too Closely

7

5/26/2008

9:00 p.m.

Angle

0

0

1

$2,500

Night

Dry

FTYROW

8

6/9/2008

6:10 p.m.

Left Turn

0

0

0

$3,000

Day

Dry

FTYROW

9

7/19/2008

5:00 p.m.

Left Turn

0

0

1

$2,000

Day

Dry

FTYROW

10

9/1/2008

10:00 a.m.

Left Turn

0

0

0

$2,500

Day

Dry

FTYROW

11

9/8/2008

4:45 p.m.

Left Turn

0

0

2

$2,500

Day

Dry

FTYROW

12

10/30/2008

3:25 p.m.

Rear End

0

0

1

$1,000

Day

Dry

Followed too Closely

13

11/11/2008

6:30 p.m.

Rear
End

0

0

0

$1,500

Night

Wet

Followed too Closely

14

1/21/2008

5:00 p.m.

Left
Turn

0

0

0

$3,000

Day

Dry

FTYROW

15

12/19/2008

4:55 p.m.

Left
Turn

0

0

3

$2,000

Day

Dry

FTYROW

Total
No.

Ped/
Bike

Fatal

Injuries

Angle

Left
Turn

Rear
End

Side
Swipe

Out of
Control

Night

Wet

15

0

0

9

2

9

4

0

0

4

2

100%

0%

0%

60%

13%

60%

27%

0%

0%

27%

13%

* FTYROW – Failed to Yield Right-of-Way.

Collision Diagram

Transportation professionals prepare collision diagrams to demonstrate the flow and direction of travel to further illuminate the circumstances surrounding crashes.  The collision diagram provides a visual representation of the crash data and can help identify crash patterns.  Figure 3.3 shows an example collision diagram.

Figure 3.3 Collision Diagram

diagram - This is an example of a collision diagram which provides a visual representation of the crash data and demonstrates the flow and direction of travel, and the facility type to illustrate the circumstances surrounding crashes and help identify crash patterns.

Figure 3.3 illustrates 19 crashes occurring during the study time period.  The diagram shows the location of each crash, as well as the crash type.  The crashes are numbered in sequential order, starting with the most recent.

As shown in Figure 3.3, there are multiple driveways on the south side of the study roadway (First Avenue).  The collision diagram identifies the majority of the crashes are rear end collisions or left turn collisions with vehicles entering the driveways.

The collision diagram helps with identifying patterns, but it may not provide enough information to identify the contributing factors.  The next step is to conduct a field investigation to determine what might be causing these crashes.

3.2 Step 2 – Assess Site Conditions

After thorough analyses of the data, transportation professionals generally conduct a field or on‑site review of the identified crash sites.  The purpose of this review is to confirm the previous analysis as well as to identify additional conditions which may have contributed to the crash and to begin the process of identifying countermeasures.  The site is visited during the time of day representative of the safety problem to gather information.  At this stage, additional partners may be involved, such as law enforcement, local officText Box: One state found the value of digging deeper when a review of the crash diagrams in combina-tion with a field visit discovered the crashes were not occurring on the Interstate exit ramp, but were actually occurring at an off-system road in close prox-imity to the exit ramp.ials and citizens, etc.  The data gathered during the site visit includes, but is not limited to:

Viewing aerial photography prior to the site visit also can help assess the field conditions.  In some cases, it may help identify a
recent change in land use conditions or a potential issue to investigate further in the field.Text Box: RSAs can be integrated into Safety Circuit Rider programs which are aimed at improving safety on rural roads.  This approach has proven successful for improving safety at low cost.

Road safety audits (RSA) can be used to supplement the engineering study and provide a broader and more complete picture of the
crash problem.  The FHWA defines an RSA as “a formal and independent safety performance review of a road transportation project
by an experienced team of safety specialists, addressing the safety of all road users.”  RSAs provide an opportunity to improve safety by taking a detailed look at an existing or planned intersection or roadway segment and suggesting specific safety improvements.  They are performed by a team of at least three people who represent different areas of expertise, such as engineering (e.g., design, traffic, maintenance, etc.), law enforcement, public officials, community traffic safety advocates, and others.  Interdisciplinary groups provide a more comprehensive view of road safety while the perspectives of individual disciplines may be more limited.

3.3 Step 3 – Identify Potential Countermeasures

Once the crash experience and site conditions have been characterized, the next step is to identify potential countermeasures.  This is accomplished by identifying factors among the roadway, roadside, and operational features that are contributing to the crashes identified on the collision diagram.  However, the process of identifying countermeasures is more complex and often involves engineering judgment.  For each type of crash identified, you should ask these three questions:

  1. What road user actions lead to the occurrence of crashes?
  2. What site conditions contribute to these driver actions?
  3. What can be done to reduce the chances of such actions or what are the potential countermeasures?

The words countermeasure or intervention are largely synonymous for a device, engineering improvement, program (e.g., law enforcement, public education and awareness, coalition building, etc.; Appendix B provides a case study on multidisciplinary approaches), policy, or investment intended to improve safety.

While diagnosing the problem and identifying countermeasures is a skill developed through experience, there are several resources available to assist in identifying appropriate countermeasures.  The Resources section of this manual (Appendix E) outlines several of these resources and some of the documented best practices.  New knowledge is continuously generated relative to the effectiveness of countermeasure approaches; hence, it is important to keep abreast of the available resources and tools.

Countermeasures may be identified during a field study, an RSA, a search of the literature on effective countermeasures, by agency policy, etc.  It may prove fruitful to engage safety stakeholders and other partners when selecting potential solutions as they may provide unique perspectives.  Involving local officials and citizens, as well as the safety partners will result in more comprehensive and potentially more effective multidisciplinary solutions as well as more practical and cost-effective approaches.  For example, one study found a multimillion dollar engineering fix could be replaced with a few thousand dollars of law enforcement overtime and community education and achieve the same result.

Some states have initiated “fatality review committees.”  They are typically comprised of multidisciplinary members from various agencies which may include metropolitan planning organization (MPO) officials, elected officials, highway safety practitioners, law enforcement, etc.  The committees analyze the crash data for all traffic fatalities occurring in the jurisdiction and identify contributing crash factors and/or trends.  The committees use their findings to offer recommendations for traffic safety improvements.

Another tool that may support the countermeasure identification process is the Haddon Matrix.  The Haddon Matrix is a two-dimensional model that applies basic principles of public health to motor vehicle-related injuries.  It is widely used by the public health community and by some in the road safety community.  Each cell of the matrix represents a different area in which countermeasures can be implemented to improve traffic safety.  Those that apply to the pre-crash phase are designed to reduce the number of crashes, while on the other hand countermeasures that apply to the crash phase would not stop the crash, but could reduce the number or severity of injuries that occur as a result.  Countermeasures focusing on the post-crash phase optimize the outcome for people with injuries, and prevent secondary events.  (See Appendix C for more information on the Haddon Matrix.)

3.4 Step 4 – Assess Countermeasure Effectiveness

Countermeasure selection involves setting priorities.  Step 4 of the engineering study process assesses the effectiveness of individual and groups of countermeasures.  Once a set of countermeasures or potential solutions are identified, the list must be prioritized and pared to meet existing resources.  Engineers generally accomplish this task by examining benefit/‌cost ratios (e.g., the amount of safety benefit gained compared to the cost of the improvement), which is discussed in great detail in Unit 4.

Crash Modification Factors (CMFs) are an excellent tool that can be used to estimate the expected safety benefits of various countermeasures and are available for many engineering improvements; however, the benefit/‌cost science concerning behavioral countermeasures is in its infancy.  NCHRP 17‑33 Effectiveness of Behavioral Highway Safety Countermeasures (see Resources, Appendix E) is helpful for assessing the effectiveness of behavioral countermeasures.

Crash Modification Factors

Crash Modification Factors (CMF) and Crash Reduction Factors (CRF) provide agencies with a method for estimating the expected crash reduction and/or benefits associated with various countermeasures and may be useful in identifying appropriate countermeasures.  These terms are different methods for expressing the expected effectiveness of various countermeasures.  A CMF is a multiplicative factor used to compute the expected number of crashes after implementing a given countermeasure at a specific site, while a CRF is the percentage crash reduction that might be expected after implementing a given countermeasure.  The relationship between a CMF and CRF is quite simple.  The CMF is the difference between 1.0 and the CRF divided by 100 (e.g., CRF = 20 percent has a CMF equal to (1.0 ‑20/100) or 0.8).

CMFs are developed based on research studies and program evaluations (e.g., before/‌after studies and cross-sectional studies).  They can be used to compare safety conditions with or without a particular treatment, or they can be used to compare the safety outcomes of alternative countermeasures or treatments.

Generally, a CMF is determined by the ratio of the expected number of crashes with a countermeasure to the expected number of crashes under identical conditions without a countermeasure.

A CMF is determined by the ratio of the expected number of crashes with a countermeasure to the expected number of crashes under identical conditions without a countermeasure.

Where,

CMF = CMF for treatment ‘t’ implemented under conditions ‘a’;

Et = the expected crash frequency with the implemented treatment;

Ea = the expected crash frequency under identical conditions but with no treatment.  In a simple before-after study, the conditions before the treatment are used.

This comparison with and without a treatment is traditionally conducted at one location and then aggregated across several locations to obtain a CMF estimate.  The ratio involves expected values not counts.  One method for developing CMFs uses Empirical Bayes (EB) analysis which determines the expected number of crashes which would have occurred at the site with no treatment.  The expected value may be derived from the Safety Performance Function (SPF) value for a particular facility type and the average annual daily traffic (AADT) count.  CMFs start with a 1.0 number which indicates no change occurred; CMFs greater than 1.0 indicate an increase in the number of crashes and those less than 1.0 indicate a reduction in crashes can be expected.

In many cases, more than one treatment is implemented at the same time.  CMFs are assumed to be multiplicative (CMFcombined = CMF1 x CMF2 x CMF3 x …x CMFi), meaning that you simply multiply them by each other to calculate a combined CMF.  However, it is important to realize CMFs multiplied together, assumes the effects of each CMF are independent.  It is possible to overestimate the combined effect of multiple treatments, especially when more than one treatment is expected reduce the same crash type (e.g., widen lanes, widen shoulder).  When using CMFs to estimate the effectiveness of multiple countermeasures, engineering judgment must be used to assess the interrelationship and/or independence of the various countermeasures, especially if more than three CMFs are considered.

The following example demonstrates how to use CMFs to estimate the expected crash reduction associated with implementing two countermeasures:

Given a rural two-lane roadway segment with 19 single vehicle crashes in the last year, identify the expected crash reduction associated with increasing the pavement friction (CMF = 0.7) and installing shoulder rumble strips (CMF = 0.79).

The first step is to calculate the combined CMF:

  1. CMFcombined = 0.7 x 0.79 = 0.55
  2. Next, calculate the estimated reduction in single vehicle crashes:
    Crash reduction = (19 crashes/year) x (1 – 0.55) = 8.55 crashes/year

Several states and local jurisdictions use CMFs, but the value of the CMF used for a particular countermeasure may vary by agency.  In many cases, multiple CMFs exist for the same countermeasure, which may provide varying levels of effectiveness in improving safety.  Multiple resources are available from which widely accepted CMFs can be obtained to provide safety practitioners with an estimate of countermeasure effectiveness (resources are presented later in this section).  Even when using published CMFs, practitioners should make every effort to use a CMF applicable to their state and local roadway conditions.

Agencies can incorporate CMFs into safety tools to estimate the safety benefits associated with various countermeasures and to identify which countermeasure will provide the greatest return on the investment.  However, agencies should use caution in selecting CMFs, as not all CMFs are equally reliable.

CMF Considerations

Several of the underlying problems with the reliability of CMFs can be attributed to the following issues (Harkey et al., 2008):

Variability – CMFs may be dependent on a variety of factors such as traffic volumes, crash experience, and site characteristics which may limit the applicability of a single CMF value.

Crash Migration and Spillover Effects – Some countermeasures may cause crashes to migrate to adjacent locations.  For instance, converting a two-way stop-controlled intersection to all-way stop may increase crash frequency at nearby two-way stop-controlled intersections due to driver confusion and expectation.  This phenomenon is rarely accounted for in existing CMFs.

Lack of Effectiveness Information – CMFs have not been developed for many Intelligent Transportation System (ITS) improvements and operational strategies.  While many of these strategies are focused on improving traffic flow, they also may benefit traffic safety.  For example, improving traffic signal coordination on a corridor may not only improve traffic flow, it also might reduce the number of rear end collisions.

Combination of Improvements – When a facility is rebuilt, multiple improvements are typically implemented; yet CMFs were developed for individual improvements.  Typically the CMFs are assumed to be multiplicative (CMFcombined = CMF1 x CMF2 x CMF3 x …x CMFi); however, very little sound research exists on the combination of treatments which leads to uncertainty in the accuracy of combining individual CMFs to capture a true combined effect.

Publication/Citation Issues – Another potential weakness is a tendency to publish studies which produce favorable results for the treatment being evaluated, as well as a tendency to ignore the negative aspects of results (i.e., declining effects over time or unintended consequences leading to increases in other crash types).
It is important to recognize the potential limitations and vulnerabilities associated with CMFs.  Engineering judgment should always be applied when using CMFs.  Despite the potential weaknesses, valid CMFs are a key component of existing safety tools and resources used to prioritize safety programs.

Countermeasure Research

Staying current on effective countermeasures requires research, continuing education, and peer networking.  The research and literature are constantly changing as policies, procedures, engineering judgment, conventional wisdom, etc., are constantly evaluated to determine new and improved methods for improving road safety.  The Resources section of this manual (Appendix E) provides several tools and references related to CMFs.

The CMF Clearinghouse is an example of an available tool to assist transportation professionals with assessing countermeasure effectiveness.  It is a web site that contains a searchable database of CMFs.  Users can search by countermeasure, crash type and severity, and other variables.  Transportation professionals also can submit their own CMF studies to the Clearinghouse.

The four steps of the engineering study process (analyze the data, assess site conditions, identify potential countermeasures and assess countermeasure effectiveness) are demonstrated using a case study in the next section.

Text Box: When obtaining crash data, it is important to realize roadways may be referenced by several different names, depending on the reporting officer.  They may be referred to by the state route number or by the local street name; additionally, abbrevia-tions may be used to identify the roadway (e.g., State Road 400, SR 400, Center Street, Center St, Ctr St). The engi¬neer should search for crash reports using all possible refer¬ences for the desired location.3.5 Engineering Case Study

This example case study is presented to provide a more thorough understanding of steps involved in an engineering study.

In this case study, a particular intersection already has been identified as having a greater than normal crash experience, compared to intersections on similar roadways in the state.  To identify any potential safety problems, as well as potential countermeasures, the first step is further analysis of the intersection crash data.

Step 1 – Analyze the Data

Two years of crash reports were obtained from local law enforcement for the intersection.  The major route in this study is State Road 400; however, this roadway is referenced locally as Center Street.  Both roadway names and any variations should be used in the crash records search.

During the two-year study period a total of 17 crashes occurred at the intersection which is summarized in Table 3.2.

Table 3.2 Collision Summary

STUDY PERIOD:  1/1/07-12/31/08

CITY:  Smithville

ROADWAY:  State Road 400

COUNTY:  Red River

INTERSECTION:  Shopping Center Drive

SOURCE OF DATA:  Local Law Enforcement

No.

Date

Time

Type

Ped
Bike

Fatal

Injuries

Property Damage

Day/
Night

Wet/
Dry

Contributing Cause

1

1/6/2007

3:25 p.m.

Angle

0

0

0

$2,000

Day

Dry

FTYROW

2

1/21/2007

5:15 p.m.

Rear End

0

0

0

$1,500

Day

Dry

Followed too Closely

3

2/6/2007

6:40 p.m.

Angle

0

0

1

$3,000

Night

Dry

FTYROW

4

4/1/2007

4:50 p.m.

Angle

0

0

0

$2,000

Day

Dry

FTYROW

5

4/20/2007

4:00 p.m.

Left Turn

0

0

2

$2,500

Day

Dry

FTYROW

6

6/9/2007

5:30 p.m.

Angle

0

0

0

$1,500

Day

Wet

FTYROW

7

7/19/2007

7:00 p.m.

Angle

0

0

0

$2,000

Night

Dry

FTYROW

8

10/30/2007

6:10 p.m.

Angle

0

0

1

$3,000

Day

Dry

FTYROW

9

12/1/2007

5:00 p.m.

Angle

0

0

0

$1,500

Day

Dry

FTYROW

10

12/19/2007

10:00 a.m.

Rear End

0

0

0

$1,000

Day

Dry

Followed too Closely

11

1/2/2008

4:45 p.m.

Rear End

0

0

1

$1,500

Day

Dry

Followed too Closely

12

1/9/2008

5:25 p.m.

Rear End

0

0

0

$1,000

Day

Dry

Followed too Closely

13

2/19/2008

6:30 p.m.

Rear End

0

0

0

$1,500

Night

Wet

Followed too Closely

14

4/27/2008

5:00 p.m.

Angle

0

0

3

$3,000

Day

Dry

FTYROW

15

6/21/2008

4:55 p.m.

Angle

0

0

1

$2,000

Day

Dry

FTYROW

16

10/9/2008

6:15 p.m.

Angle

0

0

0

$2,000

Day

Dry

FTYROW

17

11/23/2008

5:30 p.m.

Angle

0

0

0

$1,500

Night

Dry

FTYROW

Total
No.

Ped/
Bike

Fatal

Injuries

Angle

Left
Turn

Rear
End

Side
Swipe

Out of
Control

Night

Wet

17

0

0

6

12

0

5

0

0

4

2

100%

0%

0%

35%

71%

0%

29%

0%

0%

24%

12%

As shown in Table 3.2, angle collisions appear to be a significant problem at this intersection, comprising 71 percent of the crashes during the two-year time period.  In this case, no apparent trends in crashes occurred at night (24 percent) or on wet pavement (12 percent); however, further analysis of this crash data reveals the majority of these collisions occur during the evening peak period.

To better understand the crash experience at this intersection, the next step is to develop a collision diagram.  In most cases, the crash reports will provide sufficient information to develop the collision diagram; however, if the engineer is unfamiliar with the area or if the intersection is complex, a preliminary field visit may be required to determine the layout of the intersection.

The collision diagram for the study intersection is shown in Figure 3.4.  The diagram shows the location of each crash, as well as the crash type (the crash numbers on the diagram correspond to the crash number in Table 3.2).

Figure 3.4 Intersection Collision Diagram

diagram - This is the collision diagram for the study intersection.  The diagram shows the location of each crash, as well as the crash type (the crash numbers on the diagram correspond to the crash number in Table 3.2

The collision diagram identifies the majority of angle collisions occur in median of this intersection, but based on the data, it is unclear why so many collisions are occurring in the median.  The next step is to conduct a field investigation to determine what might be causing these crashes.

Step 2 – Assess Site Conditions

The study intersection is unsignalized and located in a suburban area.  The intersection is at the connection of a shopping center with Center Street (State Road 400), which is an east-west four-lane divided roadway with a striped median.  The shopping center driveway connects on the south side of Center Street (State Road 400) and has a two-lane approach – one left turn lane and one right turn lane.  A major signalized intersection is located approximately 500 feet east of the study intersection.

Since the majority of the crashes occurred during the p.m. peak hour, the site was observed during this time period to identify operational issues.  The field observations revealed significant vehicle queues resulting from the major signalized intersection located to the east.  The queues extended almost a mile beyond the intersection.  Several drivers were observed using the striped median as a travel lane to bypass the queue and enter the left-turn lane at the adjacent intersection.  The site visit also revealed several near-misses between vehicles exiting the shopping center driveway to turn left and vehicles driving in the median.

No sight distance issues were identified based on the roadway alignment at the intersection, but the vehicle queues limit the sight distance of the vehicles turning left out of the shopping center driveway.  The limited sight distance, in combination with illegal use of the median as a travel lane, were identified as factors contributing to crashes occurring at the intersection.

Now that the problem has been identified, the next step is to identify countermeasures to address the safety issue.

Step 3 – Identify Potential Countermeasures

A number of countermeasures could be selected to improve safety at this intersection.  Some options include:

Each of these countermeasures would have a different impact.  The next step is to assess their effectiveness.

Step 4 – Assess Countermeasure Effectiveness

CMFs can be used to estimate the expected safety benefits of various countermeasures.  The countermeasure with the lowest CMF will be the most effective; however, when CMFs are not available, engineering judgment should be used.
In this case study, locally calibrated CMFs were not available, so engineering judgment was used to assess the effectiveness of the various countermeasures.  Since installing a raised median completely removes the potential conflict, it is the most effective alternative for addressing the problem.  The next best option is to prohibit left turns from the driveway by adding channelization and signage; however, since access is not restricted in the median, some vehicles will still try to make the turn.  Increased enforcement is likely to work when law enforcement is observed but will be less likely to address the problem long term.  Finally, adding signage to restrict vehicles from the median or implementing a public awareness campaign will have less of an impact on addressing the issue compared to the other options, since both of these options are reliant on driver decisions.

Although installing the raised median is the most effective option in this case in terms of reducing crashes, the most effective countermeasure may not always be feasible because of funding limitations or political constraints.  The next unit demonstrates how to prioritize countermeasures and projects based on available resources.

3.6 Summary

In this unit, we learned how to identify contributing crash factors, as well as potential countermeasures for preventing crashes and mitigating crash severity.  An engineering case study illustrated the process.  This unit also described how CMFs can be used to assess the effectiveness of various countermeasures; however, other factors need to be considered, such as costs and available funding.  Unit 4 provides guidance on how to establish priorities for project implementation based on available resources.

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