Network Screening

State highway agencies generally have automated procedures for network screening to identify potential improvement sites, often known as high-accident locations. Typically, these procedures use threshold values of observed accident frequencies or accident rates, at times combined with an accident severity index.

There are several potential drawbacks to the traditional procedures:

• Observed accident data are subject to regression to the mean, because high short-term accident frequencies are likely to decrease and low short-term accident frequencies are likely to increase as a matter of course, even if no improvements are made.
• The relationship between accident frequency and traffic volume is known to be nonlinear, but procedures based on accident rates treat that relationship as if it were linear.
• Most existing procedures focus on which sites have experienced the most accidents, not which sites could benefit most from a safety improvement.
• Some existing procedures do not explicitly distinguish between intersection and non-intersection accidents.
• Most existing procedures do not explicitly address the safety performance of individual interchange ramps.

Research over the last 20 years has developed new measures of effectiveness and new statistical methodologies for network screening to overcome the drawbacks of existing procedures highlighted above and the SafetyAnalyst software implements these new approaches. SafetyAnalyst uses an Empirical Bayes (EB) approach that combines observed and expected accident frequencies to provide estimates of the safety performance of specific sites that are not biased by regression to the mean. The EB approach incorporates nonlinear regression relationships between traffic volume and expected accident frequency. The sites identified by the network screening methodology are referred to as "sites with promise" because they will be sites that have promise as locations where improvements can result in substantial accident reduction.

One new measure that has been proposed for network screening application is the potential for safety improvement (PSI) index. PSI is a measure of the excess accident frequency, above the expected value, that might be reduced if a safety improvement were implemented. Tables 1 and 2 present some simple numerical examples with actual data for signalized intersections from a particular city to show that PSI provides site rankings that differ from those based on accident frequency and accident rate.

In Table 1, a group of signalized intersections has been ranked according to their accident frequencies during a five-year period. The last column in the table shows the ranking based upon the PSI. It should be noted that, based on the accident frequency rankings, the city would improve the highest-volume location first. Based on PSI, the highest-ranking intersection would be a lower-volume intersection, ranked sixth in accident frequency, showing a greater potential for accident reduction.

Intersection	Total Accident Frequency (1995-99)	Average Annual Daily Traffic (veh/day)	Accident Frequency Ranking	Potential for Safety Improvement (PSI) Ranking
A	131	63502	1	2
B	104	35284	2	3
C	77	57988	3	11
D	75	46979	4	6
E	66	51933	5	10
F	51	48427	6	1
G	51	20423	7	15
H	46	34759	8	5
I	42	53396	9	61
J	38	25223	10	17

In Table 2, the intersections in the same city have been ranked according to accident rate. The last column in the table shows the ranking based upon the PSI. It should be noted that, if the city improved the five highest-ranking intersections based on accident rate, it would not improve any of the three highest-ranking intersections based on the potential improvement benefits. It should also be noted that scarce financial resources will be allocated to sites ranked 33rd and 35th in PSI, while over 30 intersections with greater potential for safety improvements might go untreated.

Intersection	Total Accident Frequency (1995-99)	Average Annual Daily Traffic (veh/day)	Accident Frequency Ranking	Potential for Safety Improvement (PSI) Ranking
N	18	5063	1	33
M	22	7009	2	9
L	27	8152	3	8
R	14	4402	4	35
K	33	10458	5	4
B	104	35284	6	3
O	18	4242	7	14
A	131	63502	8	2
P	16	7815	9	19
J	38	25223	10	17

These comparisons show that state-of-the-art technology can help highway agencies make better decisions about where to invest the funds available for safety improvement.

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United States Department of Transportation - Federal Highway Administration