Skip to contentUnited States Department of Transportation - Federal Highway Administration FHWA Home
Research Home
Report
This report is an archived publication and may contain dated technical, contact, and link information
Publication Number: FHWA-HRT-05-051
Date: October 2005

Crash Cost Estimates by Maximum Police-Reported Injury Severity Within Selected Crash Geometries

PDF Version (424 KB)

PDF files can be viewed with the Acrobat® Reader®

RESULTS

The results of the analyses are included in Microsoft® Excel tables found in the appendix. They are organized into the following six categories or levels:

  • Level 1-For each of the 22 crash geometries, estimates of cost for crash severity levels K, A, B+C, and O. (Sample size issues in the cost databases made it impossible to develop reasonable estimates of B versus C separately.) These are first presented categorized by the two speed limit categories (<=72 km/h (<=45 mi/h) and >=80 km/h (>=50 mi/h)),and then with all speed limits combined.
  • Level 2-For each crash geometry, estimates of cost when K and A are combined into one cost level and B and C are combined into one cost level-thus K+A, B+C, O. Again, estimates were calculated with and without categorization by the two speed limit categories.
  • Level 3-This level was defined to allow for comparison of "injury" versus "noninjury" crashes. Note that some crash forms (and some reporting officers) define a "C-injury" as a "minor injury" while others define it as a "possible injury." Thus, two definitions of Level 3 costs were used.
    • 3.A -- For each crash geometry (with and without speed limit categorization), estimates of cost when all injuries are combined into one cost level separated from the PDO cost level-thus K+A+B+C versus O.
    • 3.B -- For each crash geometry (with and without speed limit categorization), estimates of cost when K, A, and B injuries are combined into one cost level separated from the C and PDO cost level-thus K+A+B versus C+O.
  • Level 4-For each crash geometry (with and without speed limit categorization), estimates of crash cost without regard to crash severity (i.e., no division by levels of severity).
  • Level 5-For each level of crash severity (with and without speed limit categorization), estimates of cost without regard to crash geometry.
  • Level 6-Level 5 cost estimates, but with the following categories-K+A, K+A+B, K+A+B+C, B+C, C+O.

At each level, in addition to estimates for individual KABCO levels and combinations, crash cost estimates are also included for two additional categories-"Injured, severity unknown," which means there was at least one injury in the crash, but the severity was not recorded in the police files, and "Unknown severity," which means no injury severities were provided on the police report. These cost categories are not expected to be used very often, but they are included for completeness.

The output is presented in tabular form in appendix B. The title of each tables provides the number of the Level (e.g., "Level 1...") and a designation of whether the estimates are categorized by speed limit (e.g., "Level 1 w SL") or not (e.g., "Level 1 no SL"). An example of the top portion of the "Level 2 w SL" output is shown in table 1 below. The first column, which is a crash geometry number, and the columns labeled "Maximum Injsev Code" are included to assist the user in later sorts of the data. The remaining columns headings are self-explanatory.

In the more detailed levels such as Levels 1 and 2, one finding that appears somewhat counter-intuitive is that the cost estimates for the same crash injury level within the same crash type are sometimes greater for the lower speed limits. For example, in the table below, the human capital and comprehensive cost estimates for a K+A injury crash at the lower speed limit (row three) is greater than for the comparable crash at the higher speed limit in row eight (i.e., $576,985 versus $425,414 for mean comprehensive costs). This resulted from the fact that the cost for the A-injury crash at the lower speed limit was greater than the cost for the A-injury crash at the higher speed limit. Examination of the base data indicated that this may be a function of the fact that lower speed limits are generally in urban areas, where there may be more occupants (and younger occupants) in the involved vehicles (or more or younger pedestrians in the same crash). It is noted, however, that this pattern does not hold for all crash types even at the lower levels. This means that there are other unknown factors at work in the database used in the cost development. The user will note that this counter-intuitive finding can be overcome by using costs with combined speed limits, or using higher-level cost (e.g., Level 3 estimates include fewer of these counter-intuitive findings than Level 2 estimates, which have less than in Level 1).

Small Samples and Outliers

Note that some of the rows in the table are color-coded S, I, and N. All three codes are included as "flags" to the user that these estimates are felt to be less accurate than estimates in other rows. The S-coded rows indicate estimates that were derived from small sample sizes. For example, the second S-coded row in the table (i.e., the sixth row of data in the table) indicates that there were only five observations (i.e., crashes in the CDS files used) where a no-injury pedestrian crash occurred at an intersection with a speed limit of 80 km/h (50 mi/h) or greater. A decision was made to flag fatal crash cost estimates where less than five observations were present, and to flag estimates in all other injury levels where less than 10 observations were present. In these rows, only the mean crash cost estimates are included. The standard deviations and confidence intervals are omitted from the output since these are felt to be virtually meaningless given the small sample sizes. Suggestions to the user for dealing with these questionable estimates are included in the next section.

The I-coded rows indicate what are felt to be "illogical values" or "outliers" in the data-cells with ample sample sizes, but where the cost for a given injury level is an outlier when compared with either other costs within the same crash type (e.g., a B+C cost that is greater than an A-injury cost for a given crash type), or when compared to costs of different crash types at the same injury level (e.g., a no-injury cost that is much greater than all other no-injury costs). These illogical estimates were identified by looking at patterns of costs in similar severity levels or crash types. For example, the first I-coded row in table 1 (i.e., the tenth row of data in the table) indicates a very high cost per crash when compared to other no-injury level pedestrian crashes and other no-injury level crashes in general. Additional examination of the cost-development data indicated that some of these outliers might be due to erroneous coding by the police officer (e.g., in one case, a "no-injury" pedestrian crash was found to have two rather severe injuries.) Since it was not possible to examine each illogical finding in detail, they were flagged for the user's benefit. Again, suggestions for dealing with these are found in the next section.

In addition, there are crash types in the NASS data used to develop these estimates where no fatal crashes were present. For example, if the comparable "Level 1 w SL" table had been presented here, the user would note the absence of a crash cost estimate for fatal crashes within the Type 3, single-vehicle animal crashes. No such fatal crash existed in the NASS data used to develop these estimates. As a result, the estimate for "K+A" crashes in the final row of table 1 below does not have a fatal crash cost component, and is less accurate than similar combined costs where both K and A crashes existed in the NASS data. All combined estimates (e.g., K+A, K+A+B, K+A+B+C) with no fatal component are coded N in the tables.

Table 1. Level 2 crash cost estimates categorized by speed limit

Code Crash geometry Speed limit (mi/h) Maximum injsev in crash Maximum injsev code Observ Mean human capital cost per crash Std. Err. [95% Conf. Interval] Mean comprehensive cost per crash Std. Err. [95% Conf. Interval]
  1
sv, ped, int
<=45
No injury
0
31
$ 8,512
997
6,537
10,486
$ 10,249
1,408
7,461
13,036
  1
sv, ped, int
<=45
B or C
1.5
515
$ 33,369
4,561
24,340
42,398
$ 60,333
9,021
42,474
78,192
  1
sv, ped, int
<=45
K or A
3.5
401
$ 235,729
17,317
201,444
270,013
$ 576,985
53,159
471,743
682,227
  1
sv, ped, int
<=45
Injured, sev unk
5
53
$ 67,342
22,127
23,536
111,149
$ 129,418
42,249
45,774
213,061
S 1
sv, ped, int
<=45
Unknown
9
4
$ 14,386
-
-
-
$ 22,841
-
-
-
S 1
sv, ped, int
>=50
No injury
0
5
$ 3,672
-
-
-
$ 4,015
-
-
-
  1
sv, ped, int
>=50
B or C
1.5
35
$ 54,605
32,590
-
119,126
$ 101,712
61,756
-
223,975
  1
sv, ped, int
>=50
K or A
3.5
17
$ 182,970
52,554
78,925
287,014
$ 425,414
161,107
106,460
744,369
  1
sv, ped, int
>=50
Injured, sev unk
5
2
$ 61,573
-
61,573
61,573
$ 146,281
-
-
-
I 2
sv, ped,n-int
<=45
No injury
0
33
$ 28,370
18,026
-
64,059
$ 40,428
27,351
-
94,577
  2
sv, ped,n-int
<=45
B or C
1.5
721
$ 38,674
3,258
32,225
45,123
$ 70,188
7,021
56,288
84,087
  2
sv, ped,n-int
<=45
K or A
3.5
733
$ 322,119
21,628
279,301
364,937
$ 918,824
71,514
777,243
1,060,406
  2
sv, ped,n-int
<=45
Injured, sev unk
5
59
$ 26,089
8,056
10,139
42,039
$ 42,107
14,891
12,627
71,587
  2
sv, ped,n-int
<=45
Unknown
9
25
$ 24,427
8,511
7,578
41,276
$ 35,189
10,607
14,190
56,189
  2
sv, ped,n-int
>=50
No injury
0
18
$ 2,797
145
2,509
3,085
$ 2,831
175
2,484
3,178
  2
sv, ped,n-int
>=50
B or C
1.5
54
$ 31,103
8,051
14,967
47,240
$ 54,703
16,739
21,563
87,843
  2
sv, ped,n-int
>=50
K or A
3.5
121
$ 465,397
60,737
345,152
585,643
$ 1,389,804
214,297
965,546
1,814,062
S 2
sv, ped,n-int
>=50
Injured, sev unk
5
3
$ 36,790
-
-
-
$ 65,026
-
-
-
S 2
sv, ped,n-int
>=50
Unknown
9
2
$ 12,423
-
-
-
$ 18,224
-
-
-
  3
sv, animal
<=45
No injury
0
10
$ 2,617
-
2,617
2,617
$ 2,617
-
2,617
2,617
S 3
sv, animal
<=45
B or C
1.5
3
$ 37,280
-
-
-
$ 89,287
-
-
-
S 3
sv, animal
<=45
K or A
3.5
3
$ 67,137
-
-
-
$ 96,055
-
-
-
  3
sv, animal
>=50
No injury
0
61
$ 4,904
2,047
852
8,956
$ 5,619
2,661
351
10,887
  3
sv, animal
>=50
B or C
1.5
18
$ 14,246
3,482
7,353
21,139
$ 22,916
7,663
7,745
38,087
N 3
sv, animal
>=50
K or A
3.5
20
$ 76,781
20,958
35,288
118,273
$ 165,302
40,911
84,308
246,296

45 mi/h = 72 km/h 50         mi/h=80 km/h


Code S = Derived from small sampleInjsev = Injury severityConf. Interval = Confidence Interval
Code I = Illogical values or outliers in data.Observ = Observations. - = Sample size was too small to calculate or the lower bound of the confidence interval was below zero.
Code N = Combined estimate with no fatal component.St. Err. = Standard Error  

While these flagged estimates do exist, in general, most estimates are felt to be stable and usable in analysis. Many of the small sample estimates are for "unknown severity" conditions, where the officer either failed to code the injury level or simple coded it as "injured" without a specific level provided. As noted earlier, these categories are not likely to be used very often in subsequent analyses.

Suggestions for Handling Flagged Estimates

There are at least four alternative "corrections" a user could consider when a pertinent cost estimate is flagged for sample size or as an outlier or questionable combined-severity estimate.

  1. Use the small sample estimate as is. There may be cases where, even though a given estimate is flagged as having a small sample size, the estimate may appear sound. This decision can be based on study of costs within the same crash type or similar crash types. For example, while the sixth-row comprehensive-cost estimate of $4,015 for a no-injury intersection-related pedestrian crash with a speed limit of 80 km/h (50 mi/h) or greater is only based on five observations and is coded red, it is not greatly different from the comprehensive-cost estimate of $2,831 for the same type crash in a nonintersection location shown in the fifteenth row of the table. If so, the user might then decide that the first estimate is suitable for use.
  2. Substitute an estimate from a similar category. Using the same example as above, the user might decide that the estimate the no-injury nonintersection pedestrian crash with a speed limit of 80 km/h (50 mi/h) or greater could be substituted for the small sample estimate for the comparable intersection-related crash.
  3. Use the "combined speed limit" estimate from the same Level. If using crash costs at a level where speed limit categories are important, a flagged crash cost and its companion cost (i.e., same crash type but at the other speed limit) can be replaced with the same estimate where speed limits are combined. For example, both the first and sixth-row speed limit based estimates for no-injury intersection-related pedestrian crashes could be replace with the estimate for the same crash type where speed limits are combined (e.g., $5,432 in this case-not shown in this table, but found in the appendix table entitled "Level 1 no SL").
  4. Use the "next-level" cost estimate. If the user is trying to use the combined speed limit costs or feels that substituting for cost is not preferable, the user could decide to use the next higher level cost in all analyses (e.g., moving from a Level 1 to a Level 2 or Level 3 cost), since the higher levels will have larger sample sizes and fewer outliers.

Finally, it might appear that a fifth option would be for researchers to develop a customized cost specific analysis using a weighted combination of estimates provided. This should not be done. To combine different estimates (e.g., combine a K estimate and an A estimate into a K+A estimate), it is necessary to weight the individual estimates by the national estimates of the number of applicable crashes in each cell. The sample sizes provided in the output under "Observ" represent the number of raw cases in the NASS files used to develop the estimate provided. (See appendix B.) They do not represent the extrapolation of this raw frequency into a national estimate. (Pacific Institute for Research and Evaluation (PIRE) used the extrapolated national estimates in developing the combined estimates in the appendix tables.)

Previous | Table of Contents | Next

ResearchFHWA
FHWA
United States Department of Transportation - Federal Highway Administration