Estimating Cumulative Traffic Loads, Volume II:
Traffic Data Assessment and Axle Load Projection for The Sites With Acceptable Axle Weight Data, Final Report for Phase 2
Alternative Text
Figure 1. Text boxes. Overview of main traffic
data assessment and projection activities. The figure is a list of
assessments of traffic data and the development of traffic
projections carried out in two phases over the course of 30 months
and consisting of 8 main activities. Each of the three phases is
separated into its own box. Phase 1 has three activities numbered 1
through 3; Preliminary assessment of Long-Term Pavement Performance
traffic data, Development of Long-Term Pavement Performance traffic
projection procedure, and Validation of Long-Term Pavement
Performance traffic projection procedure using case studies. Phase
2 has five activities numbered 4 through 8, which are Development
of Long-Term Pavement Performance traffic feedback and resolution
package, Preparation of Long-Term Pavement Performance traffic
feedback and resolution packages for all participating agencies,
Review of Long-Term Pavement Performance traffic feedback and
resolution packages by regional coordination offices, Review of
Long-Term Pavement Performance traffic feedback and resolution
packages by participating agencies, and Implementation of review
comments received from participating agencies. Phase 3 is the
recommended phase, and the recommendations are provided in chapter
6.
Return to Figure 1
Figure 2. Form. Initial site-specific report
for Mississippi. The figure is a 4-page feedback and resolution
report prepared for the Mississippi Department of Transportation.
The sheet includes procedures for the reviewer and refers to
figures 3 through 10 to help assist the reader. The reference to
figures 3 through 10 briefly describes the purpose of each sheet in
the report. The purpose of this figure is to give an example of an
initial feedback and resolution report.
Return to Figure 2
Figure 3. Questionnaire. Feedback and data
resolution sheet for site 285805. The figure is a questionnaire,
filled out for site 285805, Mississippi in March 2001. This
questionnaire is the first sheet in the site-specific report. The
purpose of this sheet is to summarize all major site-specific
features that may influence traffic projection.
Return to Figure 3
Figure 4. Map. Site map for site 285805. The
figure is a map of the southern region of the United States. Baton
Rouge and New Orleans, Interstates 59 and 10, and test sites 5805,
3093, and 3094 are labeled on the map. This figure is the second
sheet in the site-specific report. The purpose of the map is to
clearly identify the location of the site tested, as well the
location of other sites nearby.
Return to Figure 4
Figure 5. Graphs. Annual traffic projection
sheet for site 285805. The figure shows graphs and a table
comparing annual average daily volumes, annual average daily truck
volumes, average equivalent single axle loads and truck factors.
This figure is the third sheet in the site-specific resolution and
feedback report. The purpose of the projection sheet is to
summarize the trends in historical and monitoring traffic data. It
is expected that traffic volumes and equivalent single axle loads
will exhibit an increasing trend. Truck factors (equivalent single
axle loads per truck) should be at a level or perhaps increasing to
reflect the increased cost-efficiency of the trucking industry. The
total annual average daily traffic volume increased only slightly
from 11,000 in 1991 to 12,800 in 1996. The truck volume increased
from 11,000 in 1991 to 15,000 in 1996. Both the average equivalent
single axle load per day and per truck increased their average from
1992 to 1996. The trend increased as expected.
The figure also includes a table showing the availability of
monitoring data by data type (automatic vehicle classifiers and
weigh-in-motion) and for years 1990 through 1998.
Return to Figure 5
Figure 6. Graph. Projected annual average daily
traffic volumes for site 285805. The figure shows a graph and a
table comparing annual average daily traffic volumes and projected
growth, which is usually a smooth line or a curve. The purpose of
this sheet is to show historical and monitoring truck volumes and
the suggested projection model used to estimate truck volumes for
all in-service years. Historical, monitoring, and projected data
increases steady, as expected.
Historically the volume of trucks rises from 970 average annual
daily traffic in 1975 to a peak of 2190 in 1989. In 1990 there is a
sudden drop down to 1544. The line ends in 1991 with an annual
daily traffic volume number of 1524. The projected line climbs
steadily from 885 in 1975 to 2429 in 1998. Monitoring from 1992
through 1996 matches the projected line.
This figure also includes a table showing the numbers of the
average annual daily traffic truck volume (historical, monitoring,
and projected) from 1975 through 1998. Projected growth as a
percentage and factor are depicted for the same time
period.
Return to Figure 6
Figure 7. Graphs. Annual vehicle class
distribution for site 285805. The figure shows two graphs. The
first graph shows the actual axle counts for different truck
classes. The second graph shows the distribution of trucks as a
percentage of the total truck count. The years tested include 1992
to 1996. Vehicle class 9 and class 5 are significant for sit 285805
in Mississippi. Class 9 has 70 percent of vehicle counts and class
5 has 10 percent of the vehicle counts.
Return to Figure 7
Figure 8. Graphs. Annual load spectra for the
site 28-5085. The figure shows three graphs comparing annual load
spectra for all available years with single, tandem, and triple
axle loads. The first graph labeled single axle is used to
represent traffic during the years before the installation of a
weigh-in-motion scale, and during the initial operation of the
scale. The spectrum of the second graph labeled tandem axle is used
to represent traffic levels for the most recent years, with and
without the weigh-in-motion scale data. The last graph is labeled
triple axle. Both the first and the last graphs' spectra can be the
averages of several annual spectra. Tandem axle distribution
usually has two peaks. The first peak corresponds to unloaded
tandems, and the second peak to the fully loaded tandems.
Return to Figure 8
Figure 9. Graphs. Average annual load spectrum
for site 285805. The figure shows three different graphs comparing
the axle load and axle counts for single, tandem, and triple axles.
The average annual load spectrum is obtained by calculating the
average of the annual spectra, presented in figure 8. The single
axle spectra peaks at 9,000 pounds and 17,800 axles. The tandem
axle spectrum has two peaks, the firs t 9,000 pounds and the second
at 27,000 pounds. The triple axle spectra decreases but peaks at
32,000 pounds.
Return to Figure 9
Figure 10. Graphs. Projected annual equivalent
single axle loads for site 285805. The figure shows a graph and a
table comparing the average equivalent single axle loads for all
in-service years. This figure is the last page of the initial
site-specific report. The purpose of traffic collection and
analysis is to obtain axle load spectra and not equivalent single
axle loads. Equivalent single axle loads are used mainly for
comparison and quality assurance purposes. The historical,
monitoring, and projected data are increasing on the graph. The
historical line for equivalent single axle loads starts at 330,000
and rises to 1,063,000 in 1989, after which it drops to 837,000 and
827,000 for 1990 and 1991 respectively. The line stops there. The
line for the projected ESAL starts in 1975 at 359,237 and rises
steadily through 1998 to 986,994. The monitor line covers the
period from 1992 through 1996 and increases rapidly from 618,395 to
1,256,965.
A table is included in this figure showing numbers of the annual
equivalent single axle loads from 1975 through 1998 in the three
categories of historical, monitoring, and projected.
Return to Figure 10
Figure 11. Graph. Projection of truck volumes
using historical and monitoring data. The figure is a line graph of
the historical and monitoring truck volume data being backcasted,
interpolated, and forecasted. The year is graphed on the horizontal
axis from 1980 to 2000. The annual average daily traffic truck
volume is graphed on the vertical axis. The line increases from
1980 to 2000. Backcasting begins before 1980 and increases
gradually to 1988. Interpolation is increases from 1990 to 1994.
Forecasting increases from1995 to 2000. The purpose of this graph
is to estimate traffic loads for all in-service years.
Return to Figure 11
Figure 12. Graphs. Comparison of annual average
daily traffic volumes for class 14 vehicles with annual average
daily traffic volumes for all trucks. The figure shows three graphs
comparing class 14 vehicles to trucks for three different Minnesota
sites. The year is graphed on the horizontal axis on all three
graphs. The annual average daily volume is graphed on the vertical
axis on all three graphs. The trucks had higher annual average
daily traffic volumes throughout the year compared to class 14
vehicles. Class 14 vehicles and trucks followed the same trend, the
data increased and decreased on the same years. Class 14 vehicles,
or passenger cars had higher volumes than trucks.
Return to Figure 12
Figure 13. Graphs. Use of the mean of all
annual axle load spectra to obtain base annual spectrum The figure
shows three graphs comparing the mean of all annual load spectra
for all available years with single, tandem, and triple axle loads
from site 063042. The tests include years from 1990 to 1998. The
axle load is graphed on the horizontal axis and the axle count is
graphed on the vertical axis. All the tests increase and decrease
in the same trend for each axle load. The single axle has 3 peaks
at 400, 1000, and 1700 pounds. Tandem axle load has 2 peaks at 1000
and 32,000 pounds. Triple axle load has its peak between 2,500 to
35,000 pounds. The base annual spectrum was obtained as a mean
value of the annual spectra for 1990 to 1998.
Return to Figure 13
Figure 14. Graphs. Use of the mean of 1991,
1992, and 1995 annual axle load spectra to obtain base annual
spectrum. The figure shows three graphs comparing the axle load
spectra historically from site 185518. The axle load is graphed on
the horizontal axis and the axle count is graphed on the vertical
axis. The first graph measures single axles and has all the data
increasing and decreasing in the same pattern. The highest year is
1995 with 43,000 axle counts at 11,000 pounds before decreasing
gradually to zero. The second graph measures tandem axles and all
the years increase and decrease in a wavy pattern, or in an M
pattern before returning to zero. The third graph measures triple
axles and most of the data has a minor wave-like pattern. Only the
1997 data zigzags. Most of the data follow the same trends.
Return to Figure 14
Figure 15. Graphs. Use of the mean of 1991 and
1992 annual axle load spectra to obtain base annual spectrum. The
figure shows three graphs comparing the annual load spectra from
site 124057. The axle load is graphed on the horizontal axis and
the axle count is graphed on the vertical axis of all three graphs.
The first two graphs increase slightly, and then gradually decrease
to zero. Two different years, 1994 and 1991, zigzag up and down a
couple of times before descending to zero. The last graph, most of
the years remain at zero. The years 1993 and 1991 increases
slightly at 5,000 axles and 53,000 pounds. Most of the data follow
a similar trend in the graphs
Return to Figure 15
Figure 16. Graphs. Rejection of all available
annual axle load spectra. The figure shows three graphs comparing
annual load spectra from site 473104. The axle loads are graphed on
the horizontal axis and the axle counts are graphed on the vertical
axis. The years graphed include the time between 1992 and 1996. The
first graph compares annual single axles. All the years tested
increase in axle counts at 5000 pounds, which decreases to zero.
The second graph compares tandem axles. The years 1993through1996
have a random zigzag pattern; increasing and decreasing axle counts
as the load increases. Only 1992 remain at zero. The third graph
compares triple axle counts. Only 1994 and 1996 have a random
zigzag pattern. Both years increase and decrease in number of axles
as the load increases. The rest of the years do not have any
axles.
Return to Figure 16
Figure 17. Graph. Projected annual average
daily traffic truck volumes for site 124057. The figure shows a
graph and a table comparing the annual average truck volume per
year. The graph has three tests: historic, monitoring, and
projected. The years are graphed on the horizontal axis from 1985
to 1998. The annual average daily truck volume is graphed on the
vertical axis up to 4500. The monitored data starts with an outlier
point in 1991 at a volume of 4000. The monitored data decreases to
a volume of 1000 the next year. The purpose of this graph is to
show an example of an outlier, or error.
This figure also includes a table showing the numbers of the
annual average daily truck volumes truck volume (historical,
monitoring, and projected) from 1986 through 1998. Projected growth
as a percentage and factor are depicted for the same time
period.
Return to Figure 17
Figure 18. Graphs. Annual traffic projection
sheet for site 063042. The figure has two graphs that follow the
historical and monitoring truck factors. The first graph has the
year graphed on the horizontal axis from 1978 to 1998 and the
annual average daily traffic truck volume and total volume graphed
on the vertical axis. Both historical data increases in volume from
1980 to 1989. The average equivalent single axle loads per day
increase in a zigzag pattern from 11,000 to 16,000. The average
equivalent single axle loads per truck increase from 1990 to 1991,
then remains steady at a volume of 10,000. The second graph has the
year graphed on the horizontal axis from 1978 to 1998 and the
average equivalent single axle load per day and per truck graphed
on the vertical axis. The historical data increases in loads per
day. The monitored date decreases in average loads per truck.
The figure also includes a table showing the availability of
monitoring data by data type (AVC and WIM) and for years 1990
through 1998.
Return to Figure 18
Figure 19. Graph. Projected annual average
daily traffic truck volumes (initial) for site 473104. The figure
shows a graph and a table of annual average daily truck volumes.
The year is graphed on the horizontal axis from 1985 to 1998. The
truck volume is graphed on the vertical axis up to 14. Three lines
are graphed, which are historical, monitoring, and projected.
Historical zigzags from 1986 at a volume of 5 to 1992 at a volume
of 9. Historical begins with a volume of 5 in 1986, which increases
to 10 in 1987, then decreases to 6 in 1988, and ends at 9 in 1992.
Monitoring also increases and decreases in a zigzag patter between
the years 1992 to 1996. Monitoring begins with a volume of 2 in
1992, increases to 9 in 1993, then decrease to 6 in 1995, and ends
at 12 in 1996. Projected increases in a straight line with a volume
of 6 in 1986 to a volume of 12 in 1997. The outlier is monitoring
data in 1992 with a volume of 2.
This figure also includes a table showing the numbers of the
annual average daily truck volumes truck volume (historical,
monitoring, and projected) from 1986 through 1997. Projected growth
as a percentage and factor are depicted for the same time
period.
Return to Figure 19
Figure 20. Pie Charts. Summary of Long-Term
Pavement Performance sites sorted by data presence and data
usability for projection. The figure shows nine different pie
graphs separated into three sections: data presence, data usability
for projection, and data quality for projection. Under the two
sections, data presence and data usability for projection, the
charts depict four categories: axle weight, truck class, only
historical truck, only truck class, and no traffic data or no
usable data. Each section has three pie charts. The first is built
on the total 890 sites, then two pie charts with a breakdown by the
791 general pavement study sites and the 99 specific pavement
sites.
- Data presence total sites. The pie chart shows the total sites
of 890 depicts 695 at axle weight, truck class; 87 in only
historical truck; 59 in no traffic data; and 49 in only truck
class.
- Data presence GPS sites. The pie chart is for general pavement
studies with a total of 791, with 650 being axle weight, 83 only
historical truck, 48 only truck class, and 10 with no traffic
data.
- Data presence SPS sites. The chart for specific pavement study
sites represents the remaining 99 sites with 49 having no traffic
data, 45 for axle weight, truck class, 4 for only historical truck,
and 1 for only truck class.
- Data usability total sites. The pie chart under the section
titled data usability for projects shows the 890 total sites having
543 in axle weight, truck class; 199 in only truck class; 85 in
only historical truck; and 63 in no traffic data.
- Data usability GPS sites. The pie chart for general pavement
studies shows a total of 791, has 511 being axle weight; 199 in
only truck class; 85 only historical truck; and 10 with no traffic
data.
- Data usability SPS sites, Last, the chart for specific pavement
study sites represents the remaining 99 sites with 53 having no
traffic data; 32 for axle weight; truck class; 12 for only
historical truck; and 2 for only truck class.
The third set of pie charts measure data quality for projection.
The data is divided into three categories: axle weight, truck class
and volume yielding acceptable; axle weight, truck class and volume
yielding questionable; and all other.
- Data quality total sites. The total 890 sites has 364 sites
measuring axle weight of truck class and volume yielding acceptable
projections, 332 sites measuring all other sites, and 194 sites
measuring axle weight of truck class and volume yielding
questionable projections.
- Data quality GPS sites. The 791 general pavement studies has
342 axle weight, truck class and volume yielding questionable; 265
other, and 184 axle weight, truck class and volume yielding
acceptable.
- Data quality SPS sites The last pie chart for specific pavement
study 67 other; 22 axle weight, truck class and volume yielding
questionable; and 10 axle weight, truck class and volume yielding
acceptable.
Return to Figure 20
Figure 21. Map. Geographical distribution of
Long-Term Pavement Performance sites with acceptable projection
confidence codes. The figure is a map of the United States with the
Long-term Pavement Performance sites pinpointed. Multiple pinpoints
are identified as either rural or urban depending on their highway
functional class.
Return to Figure 21
Figure 22. Graph. Mean vehicle class
distribution for Long-Term Pavement Performance sites with
acceptable and questionable projection confidence codes located on
rural highways. The figure is a graph showing the average rural
performance site for each vehicle class. The Federal Highway
Administration vehicle class is graphed on the horizontal axis from
4 to 13. The percentage of vehicles is graphed on the vertical
axis. There are four sites tested: rural principal arterial for
interstate, rural principal arterial for other, rural minor
arterial, and rural major collector. All four sites peak at in
percentage for vehicle class 5 and 9. The rural principal arterial
for interstates has the highest percentage, 60 percent at class
9.
Return to Figure 22
Figure 23. Graph. Mean vehicle class
distribution for Long-Term Pavement Performance sites with
acceptable and questionable projection confidence codes located on
rural highways. The figure is a graph showing the mean or average
percentage of urban performance sites for each vehicle class. The
Federal Highway Administration vehicle class is graphed on the
horizontal axis from 4 to 13. The percentage of vehicles is graphed
on the vertical axis. The sites tested are urban principal arterial
for interstates, urban principal arterial for freeways or
expressways, and urban other principal arterial. All three sites
climax on vehicle class 5 and 9. Vehicle class 5 has an average
between 20 to 27 percent. Vehicle class 9 has a mean between 35 to
41 percent.
Return to Figure 23
Figure 24. Graph. Trends in the number of
monitoring axle load spectra. The figure is a graph illustrating
the overall historical trend in the available axle load spectra.
The year is graphed on the horizontal axis from 1998 to 1999. The
number of sites with axle load data is graphed on the vertical axis
up to 500. The annual axle load spectra compared are available in
information management system and used for projection. The
available in information management system increases from 1990 to
1993, from 58 sites to 446 sites. The trend decreases gradually and
ends in 1998 with 287 sites. Used for projection increases from
1990 to 1993, from 26 sites to 200 sites. Used for projection
increases slightly and remains constant until 1995, then decreases.
In 1998, used for projection ends with 150 sites. Available in
information management system had more sites overall.
Return to Figure 24
Figure 25. Flowchart. Overview of the
information management system traffic module showing the proposed
addition of projected traffic data. The figure is a flowchart of
information management traffic. Information management traffic
module includes historical, monitoring, and projected traffic data.
The major elements in historical data are total volume and
equivalent single axle load. The major elements for monitoring data
are axle load spectra, volume by class, total volume, and
equivalent single axle load. The major elements for projected data
are projected annual axle load spectra and intermediate data
elements.
Return to Figure 25
Figure 26. Flowchart. Flowchart used for
calculating computed parameter tables. The figure is a flowchart
with two main categories, which are historical and monitoring data,
and projected data. Historical and monitoring data has two
sections. The first section is estimated annual total general
pavement study lanes and monitored vehicle distribution. The second
section in historical and monitoring data includes monitored basic
information.
The first section in historical and monitoring data leads to
Annual Projection factors in the Projected data category. The
projection factors leads to projection summary and computation of
projected annual axle load spectra, then ends at cumulative axle
loads by year. The second section in historical and monitoring data
category leads to the projected data category, which is computed
normalized base annual axle load and computed bases annual axle
load. The base annual axle load leads to reporting projection
summary and computation of projected annual axle load spectra, and
ends with cumulative axle loads by year.
Return to Figure 26
Figure 27. Flowchart. Flowchart for computation
of the normalized base annual load spectra. The figure is a
flowchart for finding the normalized base annual axle load
spectrum. Information management system splits into two directions.
The first is to find monitored basic information and retrieval of
supporting traffic data and other information. The other direction
is to find the axle distribution and extract available annual load
spectra for all monitoring year. The two separate direction meet
again to select the annual axle load spectra and calculate the base
annual spectrum by averaging the selected annual axle load spectra.
Next normalize axle counts in base spectrum with respect to the
total number of axles for each axle type to end with the computed
normalized base annual axle load spectra.
Return to Figure 27
Figure 28. Flowchart. Flowchart for computation
of the base annual axle load summary. The figure is a flowchart to
find base annual axle load. The information management module can
either start with monitor basic information of monitor axle
distribution. Both data leads to select annual axle load spectra
and calculate the base annual spectrum by averaging the selected
annual axle load spectra. The next box is to obtain base total
annual number of axles for each axle type, which leads to the end
to the traffic projected base annual axle summary.
Return to Figure 28
Figure 29. Flowchart. Flowchart for computation of the
annual projection factors. Information management system traffic
module. The chart begins with one of three tables; either estimated
annual total general pavement study lanes, basic information, or
monitor vehicle distribution and monitor axle distribution. The
estimated annual general pavement study lanes leads to extract
site-specific historical annual average daily traffic volume and
equivalent single axle load information. The monitor basic
information can either be empty or not empty. If it is empty, then
extract site-specific monitoring annual average daily traffic
volume and equivalent single axle load information. If the
information is not empty, then estimate the annual average daily
traffic volume and equivalent single axle load based on
site-specific monitoring vehicle class and axle count data. These
three tables all lead to analyze monitoring and historical traffic
data and develop traffic projection model. Next is to compute the
annual traffic projection factors for each in-service year. The
computed annual projection factors is the result.
Return to Figure 29
Figure 30. Flowchart. Flowchart for computation
of projected annual axle load spectra. There are two different
openings to the flowchart. The first is to multiply normalized
number of axle and total number of axles to get the base number of
axles. The other start is the annual projection factors for each
year y since site opening to traffic to 1998 or "out of study"
date. Both data leads to obtaining annual axle load spectrum for
each year by multiplying base number of axles in each weight
category by annual projection factors, or multiply the base number
of axles with annual projection factor for year y to get the
projected number of axles for year y. The final computation results
in projected annual axle load spectra.
Return to Figure 30
Figure 31. Text boxes. Overview of pavement
loading guide functions. The pavement loading guide functions
include database management, data comparison and assessment,
development of pavement loading estimates, and development of axle
load spectra and cumulative traffic estimates. The operations for
database management includes data storage; selection, sorting, and
retrieval; and importing and exporting data. The operations for
data comparison and assessment include selection of sites using
different filters; display of selected data for truck distribution,
axle load spectra, and site location; and data comparison for
Long-Term Pavement Performance and other data, and generic data.
The operations for development of pavement loading estimates
include selection of truck class and axle load distribution for
individual vehicle classes using direct input, data from other
sites, and generic data. The operations for development of axle
load spectra and cumulative traffic estimates include base annual
axle load spectra, projected axle load spectra for all years,
cumulative axle load spectra, and annual and cumulative equivalent
single axle loads.
Return to Figure 31
Figure 32. Graph. Comparison of truck class
distributions for sites 062040, 066044, and 068150. The figure
shows a graph inside a screen from pavement loading guide software.
The screen is on substep 3B; Select sites and compute vehicle
distribution. The Federal Highway Administration vehicle class is
graphed on the horizontal axis from 4 to 13. The percentage of
total truck counts is graphed on the vertical axis. There are three
California sites graphed on the screen, which are 62040, 66044, and
68150. Sites 62040 and 68150 are general pavement study 2. Site
66044 is general pavement study 6A. All three sites have the
greatest percentage of trucks for class 5.
Return to Figure 32
Figure 33. Computer screen. Comparison of
single axle load distributions for vehicle class 9 for sites 062040
and 066044 with computed mean distribution. The figure shows a
screen from the pavement loading guide software. Inside the screen
is a graph of normalized axle load distribution. The axle weight is
graphed on the horizontal axis up to 30,000 pounds. The percentage
of single axle counts is graphed on the vertical axis up to 30
percent. There are three sites tested on the graph: site 6-2040,
6-6044, and computed. All three increase to 20 percent at 10,000
pounds and then decrease again. All three sites have similar
trends.
Return to Figure 33
Figure 34. Computer screen. Comparison of
tandem axle load distributions for vehicle class 9 for sites 06040
and 066044 with computed mean distribution. The figure is a screen
from the pavement loading guide software. Inside the screen is a
graph of normalized axle load distribution. The axle weight is
graphed on the horizontal axis up to 60,000 pounds. The percent of
tandem axle counts is graphed on the vertical axis up to 20
percent. All three have the same pattern, increasing and decreasing
a couple times in an M pattern.
Return to Figure 34
Figure 35. Graphs. Comparison of site-specific
and surrogate base annual spectra for site 068150. The figure shows
three graphs mapping the trend of axle loads and axle counts of
site-specific and surrogate data. Axle loads are graphed on the
horizontal axis. Axle counts are graphed on the vertical axis.
Site-specific and surrogate tests increase and decrease together in
a wave-like patter for both single and tandem axle graphs. There is
no pattern in data for the triple axle graph. Site specific remains
below 100 axles throughout the axle loads. Surrogate and
site-specific data had similar results in single axle
loads.
Return to Figure 35
Figure 36. Graph. Comparison of projected,
historical, and monitoring annual equivalent single axle loads for
site 068150. The figure shows a graph and a table on the projected,
historical and monitoring annual equivalent single axle loads. The
year is graphed on the horizontal axis from 1983 to 1998. The
average equivalent single axle load per year is graphed on the
vertical axis up to 500,000. Site-specific category 2 and surrogate
category 3 increase in a straight line from 1983 to 1998 at 100,000
to 200,000 loads per year. The monitoring load only shows for 1995
to 1997 at 160,000 loads per year. From 1984 to 1991, Historical
load has remained at a steady pace of 60,000 to 80,000 loads per
year. Historical load increases dramatically in 1993 to 450,000
loads per year. The cumulative number of equivalent single axle
loads using surrogate spectra was 2.06 million, while the
corresponding number of equivalent single axle loads for
site-specific spectra was 2.18 million.
A table is included in this figure showing numbers of the annual
equivalent single axle loads from 1984 through 1998 in the three
categories of historical, monitoring, and projected. Projected is
divided into two subcategories: site-specific spectra category 2
and surrogate spectra category 3.
Return to Figure 36
Figure 37. Graph. Comparison of truck class
distributions for sites 041007 and 041017. The figure is a graph
inside the pavement guide software screen. The Federal Highway
Administration vehicle class is graphed on the horizontal axis from
4 to 13. The percentage of total truck counts is graphed on the
vertical axis up to 80. Two sites are graphed on the figure, which
are 041007 and 041017. Both sites increase to 76 truck counts at
class 9.
Return to Figure 37
Figure 38. Graphs. Comparison of site-specific
and surrogate base annual spectra for 041017. The figure shows
three different graphs measuring site-specific and surrogate axle
loads per counts. The first graph measures single axle counts. Both
loads increase and decrease in the same pattern. Surrogate
increases at 10,000 pounds to 50,000 axles, then decrease to 9,000
axles at 1,400 pounds. Surrogate increases to 45,000 axles at
10,000 pounds, and then decreases to 7,000 axles at 14,000 pounds.
The second graph measures tandem axle counts. Both bases increase
and decrease in the same pattern also. The third graph measures
triple axle loads. Site-specific decreases drastically in axle
counts between 12,000 to 18,000 pounds at 220 to 40 axle counts.
Site-specific has below 50 axles from 18,000 to 66,000 pounds.
Surrogate increases and decreases in a zigzag pattern. There is a
good agreement between traffic loads using surrogate and
site-specific data.
Return to Figure 38
Figure 39. Graph. Comparison of projected,
historical, and monitoring annual equivalent single axle loads for
site 041017. The figure is a graph and a table of projected,
historical, and monitoring equivalent single axle loads per year.
The year is graphed on the horizontal axis from 1974 to 1998. The
average equivalent single axle load per year is graphed on the
vertical axis up to 1,800,000. The four sites examined are
historical, monitored, site-specific category 2, and surrogate
category 4. Both site-specific and surrogate increase in a straight
line from 1976 to 1998 at an average of 58,000 to 200,000 loads per
year. Monitoring has only two plots in 1993 and 1997 at about
102,000 and 132,000 loads per year. From 1978 to 1983, historical
remains approximately close to 800,000 loads per year, and then
increases to 1,556,000 in 1988. Historical drops off in 1991 at
150,000 loads per year. This figure shows a very good agreement
between traffic loads estimated using surrogate data and
site-specific data.
A table is included in this figure showing numbers of the annual
equivalent single axle loads from 1976 through 1998 in the three
categories of historical, monitoring, and projected. Projected is
divided into two subcategories: site-specific spectra category 2
and surrogate spectra category 4.
Return to Figure 39
