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OCR for page 193
APPENDIX F
M.O.E SAMPLING PLAN DEVELOPMENT
INTRODUCTION
An essential step in the conduct of NCHRP Project 20-34 was the development of an aid to
state highway and enforcement agencies in their determination of how many data-collection sites
are required to detect regional M.O.E. differences which may result from a truck weight enforce-
ment effort. The applied approach to this process is that the user agency would specify what level
of M.O.E. difference (e.g., 5-, ~ 0- , 20-percent) is to be detected. The user would then apply results
of this sampling guide, based on a statistical analysis of nation-we M.O.E. data, to determine how
many study sites are required.
M.O.E sampling requirements were developed on Me basis of M.O.E. distributional data
gathered at a sample of LTPP sites. Each site provided 24-hour continuous WIM monitoring and
afforded observations of both weekday and weekend traffic.
The site utilization strategy for this Sampling Plan development process designated high,
intermediate, and low truck volume sites, representative of the following three functional classes:
Interstate, Pnmaty Adenal, and Minor Arterial routes. A minimum of Free sites was chosen Mom
each of We above functional classification groups. The selection process avoided sites wad very
low average ESAL values, as M.O.E.s do need to address violation occurrences.
.
Table 1 on Me next page lists locations of We sites for which data were collected In the de-
velopment of this Sampling Plarl.
The selection process designated Me 22 sites noted above, resuming In a highway functional
class distribution as follows: 6 Rural Interstates, 6 Rural Pnncipal Arterials, 3 Rural Minor Arteri-
als, 4 Urban Interstates, and 3 Urban Primary Arterials . The resulting distribution by region is as
follows: ~ Central, 5 West, 4 Atlantic, 5 South. Thus, data were collected for the LTPP sites to fill
the functional cIass/truck volume matrix of Table 2 on the next page. Site designations noted in
the cells consist of state name abbreviations followed by LTPP site number.
' The substantive contributions to this appendix of Statisticians, Dr. Olga Pendleton of Pen-Hock Statistical Con-
sultants, and Ms. Cindy Cornell, of Chaparral Systems Corporation, are gratefully acknowledged.
Appenclix F
OCR for page 194
Table I. Applied LTPP Sites in Sampling Plan Development
Arkansas
Arkansas
Florida
Florida
Indiana
Kansas
Kansas
Kansas
Kentucky
Michigan
Missouri
Missouri
Nova Scotia
Rhode Island
Tennessee
Virginia
Virginia
Washington
Washington
Washington
W:~U~
State Highway I
I U 540, Nosh of Sate Highway 253
U.S. 1, South of State Route 442
U.S. 92, East of U.S. 17
State Route 37, Norm of State Route 469
State Route 68
U.S. 50
U.S.166
I-65,Nodh of Lebanon Junction
U.S.23, Dundee
I - 44, West of Route H
I - 435, South of Route 291
Route 201, Kelly Lake
I State Route 146, Massachusetts State Line
I -75, North of State Route 61
Route 8, Floyd County
I - 95, Sussex County
State Route 5, South of State Route 104
State Route 14, East of State Route 105
State Route 167, South of State Route 405
State Route 82, West of State Route 22
. . . . . . .. . ..
Table 2. Sites selected for sampling plan development
% Buck volume
Functional Class
~ r Low ~Medium
j Rural Interstates T WA7409 ~VAl023
NS6802 TN1023
RuralPrincipalArte- T FL4109 ~RI7401
nals FL4138 KSI006 .
Rural Minor Arterials T VA1002 ~
IN2009 None
KS1005 .
Urban Interstates WA3812 MO4036
AR3059
_ WA3019 .
UrbanPrimaryArte- ~WA3813 ~KS4067
rials ~WA6049 l
2
Appendix F
High
KY3016
MO1010
MI9030
AR3011
None
None
-
None
OCR for page 195
Sites were not available for some cells, probably due to the fact that such sites are not
plentiful in reality. For example, rural minor arterials tend to have low truck volumes and urban
highways do not typically support high truck volume as these are not the roads of choice for
truckers. At least two sites were needed per cell to provide an estimate of within cell variability
needed for developing sample size. In the case of urban interstates with low truck volumes arid
urban primary arterials with medium truck volume, only one site was available for those cells so
cell sample size could not be developed. However, these sites were used in combining urban in-
terstates and primary arterials.
Documented truck weight sampling literatures has applied criteria for establishing low,
medium, and high truck presence on the traffic stream. Low truck volume sites were considered
to contain less than ~ percent Mucks as a proportion of the total traffic volume. Medium truck
presence was considered to be in Me range of 8-16 percent trucks, and high truck presence was
taken to be greater than 16 percent. Given the documented significance of considering low-, me-
dium, and high truck presence, candidate M.O.E. distribution site were accordingly stratified.
The noted truck proportion criterion was applied as a guideline; however, due to site availability
and observed nationwide traff~c-mix trends (i.e., low rural volumes, producing large truck pro-
portions) the applied percent varied slightly from the Texas study. Table 3 presents the truck vol-
ume percentages for utilized sites in the Sampling Plan development.
Table 3. Percent truck volume for sampling plan development
% buck volume
Functional Class
Low ~Medium
Rural Interstates ~7.9, 10.5 ~21.8, 30.2
RuralPrincipalArterials | 3.1,3.6 | 11.4,9.1
.
RuralMinorArterials ~4.9,6.8, 10.4 ~None
Urban Interstates 4.0 ~ 5.3, ~ 3, 28.3
Urban Primary Arterials ~7.3,8.9 ~23.9
High
61.4, 42.5
41.3, 38.5
None
None
None
2 Maxwell, D. A. et al, Evaluation of the Texas Truck Weighing Program, Research Report 424-1 F. Texas Trans-
portation Institute, College Station, 1X, 1986
3
Appendix F
OCR for page 196
The Sampling Plan development process first applied a detailed examination of site mlm-
ber requirements on the basis of two M.O.E.s, ESALs and Excess ESALs. Statistical distr~bu-
tions for these two M.O.E.s were examined for Vehicle Classifications shown in Table 4 below.
Given the results of this analysis, a more limited approach was applied with regard to site num-
ber requirements on the basis of remaining M.O.E.s.
Table 4. Description of Vehicle Classifications
vCs
vc6
vc7
vc8
vcs
vc 10
VC 11
vc 12
vc 13
Two-axle Single Unit
Three-axle Single Unit
Four or More Axle Single Unit
Four or Less Axle Single Trailer
Five-axle Single Trailer
Six or More Axle Single Trailer
Five or Less Axle Multi-Trailer
Six-Axle Multi-Trailer
Seven to More Axle Multi-Trailer
SITE NUMBER REQUIREMENTS FOR ESALs AND EXCESS ESALs
Sample size estimates are determined herein for a wide range of precision levels for two
M.O.E.'s - percent Excess ESALs and average ESALs. The main purpose in providing estimates
over a range of precisions is to give the user some idea of the maximum and minimum sample
size requirements Mat exist based on these data. The final sample size determination wall depend
on Me factors which are most important In evaluating enforcement and the feasible arid practical
expectations for unplementation. Some states may have more resources and want to aim at
higher precision levels Man others. Also, the amount of roadway mileage for a particular func-
tional class may be greater in some states than others so they may opt to focus on maximizing the
precision for that functional class. For example, if a state like Texas believes that enforcement is
a bigger problem on rural interstates and there are a tot of miles of rural interstates in Texas, the
state may opt to aim for selecting a 20 percent reduction In Excess ESALs after enforcement as
opposed to 30 percent, i.e. they want to be able detect a smaller change in violations for this
functional class.
The precision levels in the sample size computations were based on Minnesota data
where truck weights were measured when weight scales were and were not opened. The change
in percent Excess ESALs when stations were and were not opened ranged from 2 percent to 30
percent. Hence, the selected range for Excess ESALs in the sampling plan was from 5 to 20 per-
cent. The average ESAL`s in these data had relative changes of between 10 to 55 percent of the
average when scales were opened to when they were closed
4
Appendix F
OCR for page 197
Truck weight enforcement effects comparing baseline and enforcement conditions in
Idaho were also examined in the development of the Sampling Plan. The Idaho results confirmed
application of the 5 to 20 percent range for Excess ESALs and 10 to 50 percent for average
ESALs.
Sample size tables for each cell of Table 2, i.e., functional class for low-, medium-, and
high- truck percentage, are indicated in the discussion which follows. A brief explanation of the
interpretation of these tables follow the first cell analysis. Graphs of these changes are also pro-
vided.
Rural Interstates with Low % Truck Volumes (WA7409,NS6X02)
All sample sizes are based on the five- percent significance level with 80% power of detecting
the corresponding precisions. Table 5 lists summary statistics, table 6 lists sample sizes for the
M.O.E. percent Excess ESALs and table 7 lists these for the M.O.E. average ESALs.
Table 5. Sublunary Statistics for Rural Interstates with Low % Truck Traffic
1 WA7409 1 NS6802.
; Vehicle ~ TotalVe- ~ % Excess | Average | TotalVe- | % Excess
L Class | hicles | ESA~s | ESA~s | hicles | ESA~s
~. _
5 46618 0.356 0.1762 64830 2.314
L 6 1 14243 1 0.828 1 0.39411 274581 20.355
_
7 1862 O 0.9517 144 21.528
~8 1 20413 1 0.652 1 0.6872 1 42410 1 0.424
L 9 1 150197 1 1.399 1 1.1763 1 109908 1 8.060
L 10 1 8429 1 0.5461 1.1641 242721 27.076
[ r7712 1 2.0361 1.3321 263441 6.111
12 1 8139 0.7621 1.1781 5813 1 26.922
13 ~ 25400 0.169 1 1.7485 5431 1 1.639 1
_
All 1 283013 1.376 1 0.9908 306610 1 8.478 0.9538 1
Average
ESALs
0.1464
0.9085
1.4411
0.1051
1.1277
3.2464
0.966
3.732
0 8917
s
Appendix F
OCR for page 198
Table 6. Number of Sites Required to Detect 5-20 percent change in % Excess ESALs.
:
Percent Charge to be detected
Vehicle Class | 5 l 10 | 15 20 l
31 8 1 3
.
6 248 62 28
7 1 32 8 1 4
.
8 10 3 1
9 85 21 9
10 337 84 38
11 1 103 26 1 12
12 217 54 24
13 1 9 2 1 1 1
[ Total ~ 98 1 24 1 11 1 6
2
16
2
s
21
7
14
6
Appendix F
OCR for page 199
Table 7. Number of Sites Required to Detect ~ 0-50 percent Charge in Average ESALs.
Percent Change to be detected
Vehicle ~ O 20 30
Class
33 16 11
3
8 113 57 38
10 47 23 16
11 1 5 3 1 2
12 57 28 19
13 22 11 7
All 68 34 23
40
50
8
2
1
28
23
1
12
9
1
14
11
6
17
4
14
Table 6 is to be interpreted as follows: If we want to be able to say Mat a 10 percent de-
crease in the percentage of trucks with Excess ESALs after enforcement is a statistically signifi-
cant reduction in violations (at the 5 % level with 80% power), and if we are most interested in
detecting this for vehicle class 9, we will need 21 sites. If we are willing to lower our precision
requirement to detecting a 20 percent reduction in Excess ESALs, we can do this with only 5
sites. If we want to do this for all vehicle classes, we will need 6 sites.
Table 7 focuses on the M.O.E. of average ESALs. For vehicle class 7 to declare a 30
percent reduction in average ESALs as a statistically significant reduction due to enforcement,
three sites are needed. To detect this for vehicle class 8, 38 sites are needed. Thus, it is impor
Appendix F
OCR for page 200
tarot to know which vehicle class is most important and this may well be determined by the per-
centage of vehicles in this class typically travel rural interstates or by the class with the highest
percentage frequency of Excess ESALs. Figure 1 provides the total vehicle frequency distribu-
tion arid figure 2 the frequency distribution of vehicles with Excess ESALs (violators) by vehicle
class. Figures 3 arid 4 show sample size requirements for each vehicle class (corresponding to
tables 6 and 71.
Since vehicle class 9 was dominant in both frequency on rural interstates with low truck
volume arid frequency of violations (percent Excess ESALs), we might focus on this vehicle
class In determining sample size. In this case, 5 sites would be sufficient to detect a 20 percent
change in Excess ESALs and a 10 percent change in average ESALs on rural interstates with-
truck volumes of 7-10 percent.
Rural Interstates with Medium % Truck Volumes (VAl023,TNI023)
Table 8 lists summary statistics, table 9 lists sample sizes for the M.O.E. percent Excess
ESALs and Table 10 lists these for the M.O.E. average ESALs.
Table 8. Summary Statistics for Rural Tnterstates with Medium % Truck Traffic
.
l ~ VAl 023 ~ TN1023
Vehicle ~ TotalVe- ~ %Excess ~ Average ~ TotalVe- ~ %Excess
| Class ~ hicles ~ ESALs ~ ESALs ~ hicles ~ ESALs
5 ~1 2802 ~2.114 ~01188 ~113763 ~1 .908,
6 1 15928 5.198 1 0.413713879 1 14.338
.
7 1 413 1 26 877 1 2 2417 1920 1 57.609
_ _ _
8 1 91545 1 1.784 1 0.2861 137618 1 13.563
9 1 785951 1 9.86i 1 1.4935 1448886 1 27.038
10 1 4951 3.016 1 0.9927 13417 1 20.076
11 1 43397 1 10.174 1 1.7424 130237 1 39.257
12 1 3786 1 0.924 1 0.7539 15295 1 7.970
13 1 349 1 6.304 1 1.4010 13525 1 38.922 1 1
All 1 1109112 1 7947 1 1.1818 1657540 1 24.206 1 2.4250
Average
ESALs
0.9241
1.1493
5.7411
1.2974
2.8013
2.8910
4.2635
2.0508
6.1977
8
Appendix F
OCR for page 201
Table 9. Number of Sites Required to Detect 5-20 percent charge In % Excess ESALs.
Percent Change to be detected
Vehicle Class ~5 10 ~15 20
5 1 136 34 1 15
6 1 180 45 1 20
7 1 524 131 1 58
8 1 104 26 1 11
9 1 284 71 1 32
10 1 188 47 1 21
11 1 362 90 1 JO
12 1 100 25 1 11
13 1 484 121 1 54 1
Total 1 252 1 63 1 28 1 16
11
33
6
18
12
23
6
3()
9
Appendix F
OCR for page 202
Table 10. Number of Sites Required to Detect 10-50 percent Charge in Average ESALs.
| Percent Change to be detected
Vehicle I 10 20 1 30 1 40
5 1 125 1 63 1 42 1 31
6 1 70 1 35 1 23 1 18
7 1 65 1 33 1 22 1 16
8 1 95 1 47 1 32 1 2
9 1 45 23 1 15 1 11
L 10 1 73 T 36 1 24 : 18 1
1 11 1 62 1 31 1 21 1 16 1
l
12 68 34 23 17
.
L 13 1 94 1 47 1 31 1 23 1 ~
[ All 1 45 1 30 1 23 | 18
50
25
14
13
19
9
15
12
14
19
Since vehicle class 9 was dominant in bow frequency on rural ~nterstates with medium
truck volume and frequency of violations (percent Excess ESALs), we again focus on this vehi-
cle class in determining sample size. In this case, 18 sites are needed to detect a 20 percent
change in Excess ESALs and a 20-30 percent change in average ESALs have to occur to con-
clude Mat enforcement was successful on rural interstates with truck volumes of 20-30 percent.
10
Appendix F
OCR for page 203
Rural Interstates with High % Truck Volumes (KY3016,MOlOlO)
Table 11 lists sublunary statistics, table 12 lists sample sizes for the M.O.E. percent Excess
ESALs and Table 13 lists these for the M.O.E. average ESALs.
Table 11. Summary Statistics for Rural Interstates w~th Low % Truck Traffic
| KY3016 r MO1010
. . .
Vehicle | To~Ve- | %Excess | Average | TotalVe- T %Excess ~
Class | hicles | ESALs | ESALs | hicles | ESALs |
5 1111747 1 3.929 1 0.2442 1291531 1 0.763
6 1330411 15.2421 1.4038115282 T 27.164
7 125471 61.7981 S.99051904 T 43.142
~ 8 1790921 7.3931 0.7362174754 T 3.203
9 19698681 18.2391 1.8413147l43sT 12.5901
10 139221 14.3291 S.345712207 T S.437
11 155438 ~18.7671 2.6332740224 14.974
12 17145 3.639 1 2.48965442 1 5.7332
13 11888 ~14.6721 36.61192T 0OOO
~. . ~
All 1 1264688 1 16.229 1 1.7292 1 935672 1 8.557 1
Average
ESALs
~1
1
0.0479
2.151
4.380
0.368
2.109
1.232
- 1
2.592
1.178
0.2427
11
Appendix F
OCR for page 224
Urban Primary Arter~als with Low % Truck Volumes (WA 3813, WA 6049)
Table 32 lists summary statistics, table 33 lists sample sizes for the M.O.E. percent Excess
ESALs and Table 341ists these for the M.O.E. average ESALs.
Table 32. Summary Statistics for Urban Primary Arterials with Low % Truck Traffic
1 WA3813 1 WA6049
Vehicle ~ To~Ve- | %Excess ~ Average | TotalVe- ~ %Excess
Class hicles ESALs ESALs |hicles | ESALs
.
5 141473 1 3.947 1 0.28901420144 1 2.927
6 123898 1 7.5911 1 0.6638 1151406 1 3.453
7 1311 1 10.006 1 1.6908 16833 1 6.586
8 112707 1 2.849 1 0.3850168363 1 2.233
9 46167 11.287 1.4753492414 1 3.827
10 17730 4.585 0.876878564 1.148
11 13153 1 12.908 1 1.690444956 1 5.085
12 13980 1 5.276 1 1.310336356 1 2.580
13 116097 5.237 1 1.8900 166500 1 1.290 1
All T1655161 6.8591 0.9540114655361 3.1091 0.51~09
Average
ESALs
0.1712
0.3194
0.9614
0.3743
0.6937
0.6166
0.9464
0.7667
1 479n
32
Appendix F
OCR for page 225
1
Table 33. Number of Sites Required to Detect 5-20 percent charge in % Excess ESALs.
| Percent Change to be Detected
Vehicle Class | 5 | 10 | 15 l
5 1 62 15 1 7
6 1 81 20 1 9
1 138 35 1 15
8 1 47 12 1 5
1 go 22 1 10
10 1 37 9 1 4
1 1 1 91 23 1 10
12 1 58 13 1 6
13 1 53 13 1 6
All 1 71 1 18 1 8 1 4
20
4
s
9
3
6
3
6
3
3
33
Appendix F
OCR for page 226
Table 34. Number of Sites Required to Detect 10-50 percent Change in Average ESALs.
~ Percent Change to be Detected
.
Vehicle 10 20 30
Class
- s T 38 1 19 1 13
6 T 52 1 26 1 l7
L 7 T 41 1 21 r 14
8 T 2 1 1 1 1
~9 T 54 1 27 1 18
10 T 26 1 13 r 9
1 11 T 42 1 21 r 14
T 12 T 40 1 19 1 13
3 T 18 1 9 1 6
All T 62 T 31 r21
40
50
10
8
13
10
10
8
1
1
15
11
6
s
10
8
10
8
s
16
4
12
The most prominent vehicle classes in both total frequency and frequency of violations
(percent Excess ESALs) on urban primary arterials troth low truck volume were vehicle class 9
and 5, respectively. Examining the sample size requirements for these classes, 15 sites would
allow a declaration of a 15 % reduction in Excess ESALs and a 40 percent reduction in average
ESALs to be a statistically significant indicator of an effective enforcement program. If we were
only interested in the M.O.E. of Excess ESALs, only 7 sites would be necessary to detect a sig-
n~ficant difference for urban primary arterials with 7-9 percent truck volume.
34
Appendix F
OCR for page 227
Urban Interstates and Primary Arterials with Low % Truck Volumes VIVA 3813, WA
6049, WA3XI2)
Table 35 lists sublunary statistics for urban interstates with low truck volume (table 33 lists
these for primary arterials), table 35 lists sample sizes for the M.O.E. percent Excess ESALs and
Table 37 lists these for the M.O.E. average ESALs.
Table 35. Summary Statistics for Urban Interstates (WA 3812) with Low % Truck Traffic
WA 3812
C ~Total | %Excess |
5 264994 0.702
6 32771 3.405
7 3157 5.195
8 57515 0.847
9 221963 1.029
10 30794 0.786
11 13081 0.742
12 10535 1.187
13 32901 0.602
All 1 667711 T 0.984 T 0.476
Average
ESALs
0.077
0.439
0.804
0.412
0.749
0.848
0.871
0.815
1.366
3s
Appendix F
OCR for page 228
Table 36. Number of Sites Required to Detect 5-20 percent charge in % Excess ESALs.
~Percent Change to be Detected |
Vehicle Class 5 10 15
5 30 7 3
6 53 13 6
7 1 85 21 1 9
8 1 27 7 1 3
1 47 12 1 5
10 1 21 1 2
11 1 61 15 1 7
12 1 34 9 1 4
13 1 23 6 1 3
All 1 38 9 1 4 2
20
2
3
1
4
2
1
36
Appendix F
OCR for page 229
Table 37. Number of Sites Required to Detect 10-50 percent Change in Average ESALs.
Percent Change to be Detected
, _
10 20 30
5 37 19 12
6 14 7 5
7 18 9 6
21 11 7
4 2 1
16 8 5
l
10 5 3
All 1 36 1 18 1 12 1 9 1 7
Vehicle
Class
40
9
4
4
50
7
4
8
9
5
4
10
1
11
4
1 ~
3
13
1
1
The most prominent vehicle classes in both total frequency and frequency of violations
(percent Excess ESALs) on urban interstates and urban primary arsenals wad low truck volume
were vehicle classes 9 and 5, respectively. Examining the sample size requirements for these
classes, 9 sites would allow a declaration of a 10-15 % reduction in Excess ESALs and a 40 per-
cent reduction in average ESALs to be a statistically significant indicator of an effective en-
forcement program. If we were only interested in the M.O.E. of Excess ESALs, only 5 sites
would be necessary to detect a significant difference for urban interstates and primary arterials
with 4-9 percent truck volume.
37
Appendix F
OCR for page 230
ESALs and Excess ESALs Sampling Requirements Conclusion
Depending on the M.O.E. of interest, the required sample sizes differ. Detecting changes
in percent Excess ESALs generally requires more samples than detecting a percentage change in
Excess ESALs. That is, if we are most interested in declaring a ~ 5 percent reduction in the per-
cent of Vehicle Class 9 trucks with Excess ESALs after enforcement, this requires more sites
than if we want to be able to say that the reduction in average ESALs was ~ 5% less than the av-
erage ESALs before enforcement. Table 38 shows the number of sites for detecting a 15 percent
change in excess ESAL change and table 39 shows the number of sites required to detect a 30
percent change in average ESALs (detecting a ~ 5 percent change in average ESALs is probably
an unrealistic). Alternative site number requirements to these can be constructed from preceding
tables in this report in order to assess the significance of other observed ESAL changes.
Table 38. Number of sites required to detect a ~ 5% charge in Excess ESALs.
% truck volume
. .
Functional Class ~Low Medium
Rural Interstates 9 32
Rural Principal Arte- | 2 15
nals
RuralMinorArterials | 9 l
Urban Interstates 15
Urban Principal Arte- ~10 ,
nals
Barbara Interstates and 10 14
Pnncipal Arterials
Combined
Tom | 30 ~ 5
High
32
15
47
38
Appendix F
OCR for page 231
Table 39. Number of sites required to detect a 30°/O change in average ESALs.
_. .
TO truck volume
.
Functional Class Low Medium
Rural Interstates 2 ~ 5
Rural Principal Arte- 2 4
reals
Rural Minor Arteriole 6
Urban Interstate s 12
Urban Principal Arte
nals
.
Urban Interstates and 5 4
Pr~ncipla Arter~als
Combined
Total 1 5 60
High
2
2
4
SITE NUMBER REQUIREMENTS FOR OVERWEIGHT VIOLATIONS
Given the foregoing detailed development of ESAL and Excess ESAL sampling reqliire-
ments, a more streamlined approach was applied with regard to the remaining M.O.E.s, i.e., Pro-
portion of trucks with Gross Weight Violations' Proportion with Tandem Violations' arid Pro-
portion with Single Axle Violations. On the basis of field observations and preliminary Sam-
pling Plan developmental effort, it was evident that M.O.E. development needed to concentrate
on the Vehicle Class 9 truck type as these were the predominate truck type and He predominate
violators. Therefore, development of sampling requirements for these measures addressed
M.O.E. distributions exhibited by Type 9 trucks at the 22 LTPP sites.
As in the process which established ESAL and Excess ESAL sampling requirements, ac-
tual truck weight enforcement effects were examined for existing project databases, e.g., Califor-
nia, Georgia, Idaho, and Minnesota. On the basis the data examination, sampling requirements
were developed to accommodate the detection of 10-, 20-, 30-, 40- and 50-percent changes in the
M.O.E.s.
39
Appendix F
OCR for page 232
Proportion of Gross Truck Weight Violations
Table 40 below indicates the required site numbers to detect changes in the proportion of
trucks exceeding the legal gross weight limit, given the specified detection level thresholds.
Table 40. Site Number Requirements for Gross Truck Weight Violations
11
PERCENT CHANGE TO BE DETECTED
FUNCTIONAL CLASS 10 ~20 l 30 ~50
Rural Interstate
< 15 % Trucks 40 10
15 to 30 %; 24
Trucks
> 30% Trucks 48 12
Rural Primal Arterial
< 9 TO Trucks 40 1 0
9 to 30 % Trucks 105 26
.
> 30°/O Trucks 20 5
Rural Minor Arterial 44 1 1
Urban Interstate
< 9% Trucks 5 1
> 9% Trucks 25 6
Urban Primary Arterial
< 9% Trucks 32 ~
> 9°/O Trucks ~ ~ 49 ~12
2
4
s
2
2
2
4
2
. .
2
s
1
l
3
4
2
The shaded cell above indicates the most likely expected percent change and site re-
qu~rements to be associated wad truck weight enforcement activity on Me basis of field observa-
tions conducted in the current study.
Proportion of Trucks with Overweight Tandem Violations
Table 41 on the next page indicates the required site numbers to detect changes in the
proportion of trucks exhibiting at least one tandem axle pair that exceeds the legal
weight limit, given the specified detection level thresholds.
40
Appendix F
G; ....
.,
OCR for page 233
Table 4 1. Site Number Requirements for Tandem Weight Violations
PERCENT CHANGE TO BE DETECTED
.
FUNCTIONAL CLASS 10 20
Rural Interstate
< 15 TO Trucks 54 13
15 to 30 % Trucks 24
> 30% Trucks 48 12
Rural Primary Arterial
< 9 % Trucks 40 1 0
9 to 30 % Trucks 105 26
> 30% Trucks 20 5
Rural Minor Arterial 44 1
Urban Interstate
< 9% Trucks 5 3
> 9°/0 Trucks 25 6
Urban Primary Arterial _
< 9°/0 Trucks 32 ~
> 9°/O Trucks 49 12
_ ~ ~ ~ ~ ~
_ ~ ~
i 1 1 ~
_ ~ ~ ~
_ ~ ~ ~
~ ~ 1. l ~
~ ~ i .
_ E wee i' ~
_ _ ~ ~ i2~i2ff
_'
i_ ~ He _3
i jA~_i ~ _i Ray
_~
it=
_
___
__
_ ~
_ __
__
_ _
___
_
_
___
~ _
_~
_
ma_
_ _
_ .~
~ _~
__
~ _
_ _
_ ~
_ ~3
_ __
30
50
4
1
s
2
4
2
4
12
2
s
2
4
2
l
1
2
4
s
2
The shaded cell above indicates the most likely expected percent change and site re-
qu~rements to be associated with truck weight enforcement activity on the basis of field observa-
tions conducted in the current study.
Proportion of Trucks with Single Axle Weight Violations:
Table 42 on We next page indicates the required site numbers to detect changes in the
proportion of trucks exhibiting at least one overweight
axle which exceeds We legal weight Innit, given the specified detection level thresholds.
41
Appendix F
OCR for page 234
Table 42. Site Number Requirements for Single-AxIe Violations
PERCENT CHANGE TO BE DETECTED
FUNCTIONAL CLASS 10 _| 30 40
Rural nte ate
<15%Trucks 1 33 ~4 LO
is to 30 % Trucks 84 81_ 5
> 30% Trucks 50 _ 6 - 3
Rural Primary Arterial ~
< 9 % Trucks 45 Em_ 5 3
9 to 30 % Trucks 98 ~ ~6
> 30% Trucks 20 ~j 2 1
Rural Minor Arterial 36 ~4 2
Urban Interstate
< 9% Trucks 7
> 9% Trucks 24 ~3
Urban Prima Ar erial
< 9% Trucks 1 28 ~3 LO
> 9% Trucks 3 ~3 2
5(}
2
3
.
2
2
4
l
l
l
42
Appendix F
Representative terms from entire chapter:
percent change
