Screening Your Network to Improve Roadway 

Safety Performance – Getting Started 

Network screening is a crucial step in the safety management process that identifies locations for potential 

safety investment according to their potential for future crashes. The potential for future crashes can be either 

directly based on the spot-specific crash history or on other factors that have potential to contribute 

to crashes, such as roadway factors and traffic characteristics. 

WHAT IS NETWORK SCREENING? 

Network screening is a method that objectively considers crash history, roadway factors, and traffic 

characteristics that may contribute to future crashes and helps agencies identify and prioritize locations for 

potential safety investment. The process includes the following five steps: 

1. Establish a focus. 

Network screening provides 

solid documentation and 

justification for prioritizing 

safety needs. 

2. Identify the types of sites or facilities to be screened. 

3. Select performance measures. 

4. Choose a screening method. 

5. Screen and evaluate results. 

Agencies can screen their networks through routine business practices by collecting and analyzing crash, 

roadway, and traffic volume data. Several guides can assist agencies with the screening process, including 

FHWA’s Systemic Safety Project Selection Tool,

1

 AASHTO’s Highway Safety Manual (HSM),2 and FHWA’s 

Improving Safety on Rural Local and Tribal Roads — Safety Toolkit.

3 

NETWORK SCREENING IN 5 EASY STEPS Employing traditional network 

screening with systemic safety 

analysis can be an agency’s first 

step toward a comprehensive 

safety management program. 

Although many network screening methods exist, the example below 

outlines a step-by-step “quick start” approach that almost every agency 

can use to screen its jurisdiction’s network for locations for potential 

safety investment. To get started with systemic safety analysis, see the 

4 companion guide: Quick Start Guide to Systemic Safety Analysis. 

Example: In “Springfield, USA,” a city of 30,000 people, the public works department experiences a high 

number of annual severe intersection crashes and wants to identify and prioritize potential safety investment 

locations. Springfield is a community hub centrally located in a mostly rural area. The city is host to many of 

the area’s employment opportunities, shopping centers, restaurants, and other entertainment venues. 

1 Federal Highway Administration. Systemic Safety Project Selection Tool. FHWA-SA-13-019. 2013. Washington, D.C. Accessible at: https://safety.fhwa.dot.gov/ 

systemic/fhwasa13019/sspst.pdf. 2 American Association of State Highway and Transportation Officials. Highway Safety Manual. 2010. 3 Federal Highway Administration. Improving Safety on Rural, Local, and Tribal Roads – Safety Toolkit, “Step 4. Diagnose Site Crash Conditions and Identify 

Countermeasures.” FHWA-SA-14-072. 2014. Washington, DC. Available at: https://safety.fhwa.dot.gov/local_rural/training/fhwasa14072. 4 Federal Highway Administration. Quick Start Guide to Systemic Safety Analysis. FHWA-SA-17-009. 2013. Washington, D.C. 
Number Severe 

Reference Intersection of Through Total Angle 

Population ID Lanes Crashes Crashes 

3 1 22 9 

Three- 5 1 20 8 

Legged 

Intersections 18 2 37 12 

22 2 32 5 

Four-Legged 

Intersections 

2 1 29 6 

7 1 24 7 

8 1 17 7 

11 2 30 5 

16 2 28 13 

29 2 23 9 

Screening Your Network to Improve Roadway Safety Performance – Getting Started 

STEP 1 ESTABLISH A FOCUS 

Identify sites with the potential to reduce future crash frequency or severity 

and focus on the most prevalent crash types. 

The city’s public works department operates and maintains 38 traffic signals. 

Agency staff know that angle crashes at signalized intersections have an 

increased potential for resulting in severe injuries or fatalities. They want to 

identify intersections with more severe angle crashes than expected. 

The agency decides that 

focusing on angle crashes at 

signalized intersections will 

assist it in effectively reducing 

overall severe injuries and 

fatalities. 

STEP 2 IDENTIFY THE TYPES OF SITES/FACILITIES TO BE SCREENED 

Select a subset of roads or sites on which to focus improvements, such as all two-way, stop-controlled 

intersections or urban flat, four-legged intersections. 

The city’s 38 signalized intersections have the following 

characteristics. Grouping the intersections based on 

these characteristics forms reference populations. 

` Seventeen signals are classified as being located 

on arterials, 8 are on major collectors, and 13 are 

on minor collectors. 

` Thirty-two signals are at four-legged intersections 

and 6 are at three-legged intersections. 

` Ten signalized intersections have more than 20,000 

Total Entering Vehicles (TEV) per day, 18 have 

between 10,000 and 19,999 TEV per day, and 10 

have less than 9,999 TEV per day. 

While screening a network allows agencies to 

screen hundreds of locations at once, we will 

assume the agency narrows its focus to 10 highvolume intersections for simplicity. The agency 

chose “number of approaches” as the reference 

population since the variation of intersection 

geometry within each is minimal compared to 

other grouping options. Four of these intersections 

are three-legged and six are four-legged. The 

staff enters the pertinent crash data for each 

intersection. 

The agency separates the intersections into two 

reference populations: (1) three-legged intersections, 

and (2) four-legged intersections. 

STEP 3 SELECT PERFORMANCE MEASURES 

Specify one or more performance measures to evaluate one or more sites from Step 2. Performance measures 

could include more traditional methods such as crash frequency and severity or more advanced methods, which 

involve more detailed analysis and produce more reliable outputs compared to the traditional methods. The HSM 

outlines several advanced analysis methods that rely on crash data: 

` Expected average crash frequency with empirical Bayes adjustment. 

` Excess expected average crash frequency with empirical Bayes adjustment. 

` Probability of specific crash types exceeding threshold proportion. 

www.fhwa.dot.gov/everydaycounts 
1 1 2 Var (Three-Legged Intersections) = x 0.422 x 1.289 = 0.002 

4–1 4 

N2

observed,i − Nobserved,i 

N2

observed,i(total)−Nobserved,i(total) 

92

 – 9 82

 – 8 122 – 12 52 – 5 = 222

 – 22 202 – 20 372 – 37 322 – 32 

= 0.156 + 0.147 + 0.099 + 0.020 = 0.422 

Var (N) = 1 

x n observed,i − Nobserved,i − 1 x ∑n Nobserved,i 2

( − N2 i ) 1) ( ∑ i=1 [ N2 

n − ] [ ] [ =1 ] sites observed,i(total) Nobserved,i(total) nsites Nobserved,i(total) 

Sum of observed severe angle crash frequency within the population Threshold Proportion = Sum of total observed crash frequency within the population

Example: Number of observed target crashes at Intersection 3 9 

Observed proportion at Intersection 3 = = — = 0.41 

(HSM Equation 4-18) Total number of crashes at Intersection 3 22 

 

 

 9 + 8 + 12 + 5 34 = — = 0.306 for three-leg intersections = 22 + 20 + 37 + 32 111 

Nobserved,i 9 8 12 5 

N = + + + = 0.409 + 0.400 + 0.324 + 0.156 = 1.289 observed,i(total) 22 20 37 32 

Screening Your Network to Improve Roadway Safety Performance – Getting Started 

While the agency can proceed with just one of 

these analysis methods for this step, using multiple 

performance measures to evaluate each site can 

improve the level of confidence in the results during 

network screening. 

The probability of specific crash types exceeding threshold proportion method, as noted in the HSM (p. 4-12), 

prioritizes the sites based on the probability that the long-term predicted proportion is greater than the 

threshold proportion identified for each crash type, showing whether the location is performing worse than 

expected. This performance measure is not affected by regression-to-the-mean bias, and the only data 

needed to apply this method is crash type and location data. The agency executed the following calculations 

and obtained the result in approximately 15 minutes. 

1) Agency personnel calculate the observed proportions for each intersection. 

2) They estimate a threshold proportion for each reference population. 

Example: 

(HSM Equation 4-19) 

3) Then they calculate sample variance for each reference population following the equation below. 

Example: 

(HSM Equation 4-20) 

Where: nsites = Total number of sites being analyzed 

Nobserved,i = Observed severe angle crashes for a site i 

Nobserved,i (total) = Total number of crashes for a site i 

Example: 

For Three-Legged Intersections 

nsites = 4 

The agency selects a more reliable performance measure 

and makes use of currently available data (i.e., probability 

of specific crash types exceeding threshold proportion) to 

evaluate each intersection’s safety performance. 

www.fhwa.dot.gov/everydaycounts 
(HSM Equation 4-22) 2 3 

* * s2 * 

a = 

Var (N) 

 0.3062

 – 0.3063 – 0.002*0.306 a (Three-Legged Intersections) = = 32.19 0.002 

a 

= – a 

* 

32.19 

(Three-Legged Intersections) = – 32.19 = 73.00 0.306 

 + Total Number of Crashes – Observed Severe Angle Crashes) 

Screening Your Network to Improve Roadway Safety Performance – Getting Started 

4) They calculate mean proportion of target crash types and alpha and beta parameters, which will be used in 

 the next step to calculate probability. 

Note: For higher accuracy, use a calculation software like 

Microsoft Excel. Ensure that all decimal places are carried 

through. Rounding to the first or second decimal place during 

calculations can result in significantly different final values. 

(HSM Equation 4-23) 

Where Var(N) = Variance (equivalent to the square of the standard deviations, s2) 

 = Mean proportion of target crash types. *

Example: 

5) They calculate the probability for each site. In an Excel spreadsheet, the agency staff inputs the below 

 equation using the “BETADIST” function of Excel. 

(HSM Equation 4-24) Probability of Severe Angle Crashes Exceeding Threshold Population 

= 1– betadist (Threshold Proportion, a + Observed Severe Angle Crashes, 

Reference 

Population 

Intersection 

ID 

Total 

Crashes 

Severe 

Angle 

Crashes 

Observed 

Proportion 

Threshold 

Proportion Sample Variance α β Probability 

Three-Legged 

Intersections 

3 22 9 0.41 

0.31 0.0022 28.99 65.66 

67% 

5 20 8 0.40 64% 

18 37 12 0.32 54% 

22 32 5 0.16 17% 

Four-Legged 

Intersections 

2 29 6 0.21 

0.31 0.0033 19.79 43.80 

24% 

7 24 7 0.29 45% 

8 17 7 0.41 65% 

11 30 5 0.17 16% 

16 28 13 0.46 82% 

29 23 9 0.39 66% 

For each intersection, the probability column shows the probability of 

exceeding the threshold number of severe angle crashes for its respective 

reference population. For example, there is a 67 percent chance that the 

long-term expected proportion of severe angle crashes at Intersection 3 is 

actually greater than the long-term expected proportion for three-legged 

intersections.5 

Network screening software can 

simplify these procedures. For 

further information on available 

network screening tools, see 

FHWA’s Roadway Safety Data 

Program (RSDP) Toolbox.5 

HINT! 

www.fhwa.dot.gov/everydaycounts 

5

 Federal Highway Administration. Road Safety Data Program. Available at: https://safety.fhwa.dot.gov/rsdp/toolbox-tool.aspx?pt=3. 
Every Day Counts (EDC), a State-based initiative of FHWA’s Center for Accelerating Innovation, 

works with State, local and private sector partners to encourage the adoption of proven 

technologies and innovations aimed at shortening and enhancing project delivery.

www.fhwa.dot.gov/everydaycounts 

Jerry Roche

FHWA Office of Safety

515.233.7323

Jerry.Roche@dot.gov

John McFadden

FHWA Resource Center

410.962.0982

John.McFadden@dot.gov

For additional 

information, 

please contact:

FHWA-SA-17-008

Screening Your Network to Improve Roadway Safety Performance – Getting Started 

STEP 4 CHOOSE A SCREENING METHOD 

Three screening methods exist: sliding window, peak searching, and simple ranking methods. Each requires 

a differing range of analysis, from most to least complex, respectively. 

After calculating the performance measures for the reference populations, the 

agency looks for the most suitable method to compare the numerical results. Only 

simple ranking is applicable for screening discrete nodes, such as intersections. 

The agency chooses the 

simple ranking screening 

method to evaluate the 

intersections. 

STEP 5 SCREEN AND EVALUATE RESULTS 

Example Results: Intersection Rankings 

Rank Intersection ID Probability (%) 

1 16 82 

2 3 67 

3 29 66 

4 8 65 

5 5 64 

6 18 54 

7 7 45 

8 2 24 

9 22 17 

10 11 16 

Use the completed evaluation for all sites to compare, rank, 

and prioritize sites for potential improvements. 

To screen the network, the agency ranks the intersections 

based on the probability of the target crash types (e.g., 

severe angle crashes) exceeding the threshold. 

CONCLUSION 

Following these five steps, Springfield Public Works 

Department identified intersections with the highest 

proportion of severe crashes among intersections with similar 

features. Thus, the network screening process objectively 

provides a list of locations where investing in improvements is 

likely to return the greatest benefit. 

Network screening is just a starting point for further investigation. The next step is for 

the agency to review locations and identify appropriate countermeasures. For som

locations on this list, a cost-effective solution may not exist. 

e 

The data and analytical methods each agency selects to screen its network should 

be based on available resources and technical expertise. More comprehensive data can help practitioners to 

make better decisions, but lack of data should not preclude an agency from screening its network. Agencies 

should start with the existing resources, data, and expertise at 

their disposal. They can then progressively shift to more advanced If Springfield had more comprehensive 

network screening methods as more and better quality data data, personnel could input other 

becomes available. Agencies can also incorporate a systemic roadway factors in addition to the crash 

component to address locations with roadway factors and traffic data to incorporate a systemic approach. 

characteristics similar to those with a history of severe crashes. 

The agency decides 

to prioritize the top five 

intersections for further 

investigation.