MnDOT Procedure

Manual for
Forecasting Traffic

Prepared by:
MnDOT Traffic
Forecasting and
Analysis Section
Office of
Transportation
System Management
Table of Contents
INTRODUCTION ........................................................................................................................................................................ 1
About the document.................................................................................................................................................. 1
What is Traffic Forecasting? .................................................................................................................................... 1
Overview .................................................................................................................................................................. 1
TRAFFIC FORECASTING PROCESS FLOWCHART ............................................................................................................. 2
TRAFFIC FORECASTING & ANALYSIS WEBSITE .............................................................................................................. 3
TRAFFIC FORECASTING PROCEDURE................................................................................................................................. 3
MnESAL Program .................................................................................................................................................... 3
STEPS TO CREATE A FORECAST........................................................................................................................................... 4
Obtain General Information about the Forecast ....................................................................................................... 4
Create a map of the forecasted location .................................................................................................................... 5
Fill out the MnESAL ................................................................................................................................................ 6
Title Sheet ............................................................................................................................................................. 6
Cover Sheet ........................................................................................................................................................... 6
Forecast A Worksheet ........................................................................................................................................... 7
Forecast B(s) Worksheet ....................................................................................................................................... 7
Interpolation ..................................................................................................................................................... 7
VC 1-4 Worksheets ............................................................................................................................................... 8
VC Average Worksheet ........................................................................................................................................ 9
ESAL A Worksheet and Report.......................................................................................................................... 10
ESAL B(s) Worksheet and Report...................................................................................................................... 11
Submit forecast to the Office of Traffic Forecasting and Analysis ........................................................................ 12
MnDOT STATE AID AND CONSTRUCTION DISTRICTS .................................................................................................. 12
TRAFFIC DATA COLLECTION .............................................................................................................................................. 13
Tube Counts ............................................................................................................................................................ 13
Vehicle Class Groupings for Forecasting ............................................................................................................... 15
Automatic Traffic Recorder (ATR) ........................................................................................................................ 16
Weigh-In-Motion (WIM) ....................................................................................................................................... 16
Manual Counts ........................................................................................................................................................ 17
TRAFFIC MONITORING PROGRAM OVERVIEW .............................................................................................................. 18
RESOURCES ............................................................................................................................................................................. 19
AXLE CORRECTION FACTORS ............................................................................................................................................ 20
DESIGN LANE FACTOR ......................................................................................................................................................... 20
ADJUSTMENT FACTORS ....................................................................................................................................................... 21
24 Hour Adjustment Factors................................................................................................................................... 21
16 Hour Adjustment Factors................................................................................................................................... 21
Analysis of a 16 Hour Count .............................................................................................................................. 22
HOURLY DISTRIBUTIONS OF TRAFFIC BY VEHICLE TYPE ......................................................................................... 22
Hourly Expanding................................................................................................................................................... 23
DESIGN HOURLY VOLUME (DHV)...................................................................................................................................... 24
ESAL CONCEPT ....................................................................................................................................................................... 24
ESAL EQUIVALENCE FACTORS FOR FLEXIBLE PAVEMENT ....................................................................................... 25
TRUCK WEIGHTS AND AXLE CONFIGURATIONS .......................................................................................................... 26
Example of Modifying Default ESAL Values for Heavy Trucks .......................................................................... 26
Transit, Bus, and ESAL Information ...................................................................................................................... 27
Sugar Beet Routes .................................................................................................................................................. 28
ESAL THRESHOLDS ............................................................................................................................................................... 28
County Road Thresholds ........................................................................................................................................ 28
Truck Highway Thresholds .................................................................................................................................... 28
PAVEMENT SECTION PROCESS AND ESALS ................................................................................................................... 29
MNPAVE ................................................................................................................................................................................... 29
ADDITONAL PRODUCTS ....................................................................................................................................................... 30
Planning Tool ......................................................................................................................................................... 30
ESAL Forecasting Tool .......................................................................................................................................... 30
ESAL Calculator..................................................................................................................................................... 30
Roundabout Tool .................................................................................................................................................... 31
ADDITIONAL FORECAST KNOWLEDGE ........................................................................................................................... 33
Obtaining Data from a 3 Legged Intersection ........................................................................................................ 33
Traffic Forecasting from Proposed (Non-Existent) Roadways .............................................................................. 33
Bypass ................................................................................................................................................................. 33
New Alignment ................................................................................................................................................... 34
New Route .......................................................................................................................................................... 34
TRAFFIC TERMINOLOGY AND DEFINITIONS .................................................................................................................. 35
APPENDIX ................................................................................................................................................................................ 36
1980-2010 Seasonal Adjustment Factors ............................................................................................................... 36
Rural and Urban defaults by AADT Range............................................................................................................ 38
Double Tube Data ................................................................................................................................................... 39
Breakdown of the 8 Vehicle Types for Forecasting ............................................................................................... 40
Example of Heavy 5+ Axle Semi Types ................................................................................................................ 40
Traffic Counting Schedule...................................................................................................................................... 41
Comparing Interstates and Non-Interstates Hourly Factor Distribution by Rural and Urban ................................ 42
Contacts Regarding this Manual................................................................................................................................................. 42
INTRODUCTION
Minnesota Department of Transportation (MnDOT) has district traffic forecasters that have been trained by the
Office of Transportation System Management (OTSM) in the Transportation Data and Analysis (TDA) Section.
The traffic forecasters have the responsibility of preparing project level forecasts. After their forecast is approved
by TDA, it is dispersed to designers and engineers. The approved forecasts are also entered into eDOCS, which
allows for storing and retrieving information. Traffic forecasts play an important role in geometric design,
structural pavement design, safety analysis, environmental analysis, benefit cost analysis, and access management.
Check out TDA products at http://www.dot.state.mn.us/traffic/data/index.html.

About the document

This manual is intended to be used as a guide for preparing traffic volume and equivalent single axle load (ESAL)
projections. The following procedures will help standardize techniques used by traffic forecasters throughout the
state. This manual was originally created in July 2002, and has been revised several times with the latest revision in
May 2019.

What is Traffic Forecasting?

Traffic forecasting is the projection of traffic volumes and loads on specific roadway segments. The forecasts are
derived by trending historic data and socioeconomic factors that affect future changes on particular roadways.
The most common requests for traffic forecasts are:
• Base and design year annual average daily traffic (AADT)
• Design hour volumes (DHV) with associated directional distribution (DD)
• Base year and design year heavy commercial annual average daily traffic (HCAADT)
• 20 year cumulative equivalent single axle loads (ESALs)

Overview
Traffic forecasters estimate the traffic volume and equivalent single axle load (ESALs) on Minnesota’s roadway
systems. An Excel spreadsheet, called the MnESAL, is used to streamline the forecasting procedure. The MnESAL
has undergone several revisions since the change from the initial Lotus version. Designers and engineers use these
forecasts to ensure proper geometric and structural designs. The geometric design is generally based on forecasted
traffic volumes, and the structural design is based on forecasted ESALs.
1. Traffic Volume
The traffic volumes are estimated from historical volume data and the trending of future observations. Linear
regression is used to project future traffic growth based on the slope of historic data. In Greater Minnesota,
forecasts can be estimated from historical observations. In the Metro areas the Metropolitan Planning Organization
(MPO) Travel Demand Models can be used to forecast the traffic volume. Under Federal transportation
regulations, the travel demand model is maintained by Metropolitan Council, the MPO serving the Twin Cities
seven-county metropolitan area. This model considers the impact of highway design changes and regional travel
patterns. Generally, the models produced by the Met Council and other local Minnesota agencies don’t produce
ESALS. Instead, they may hire consultants to produce results that is verified by MnDOT’s Traffic Forecasting
Section.

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 2. Equivalent single axle load (ESAL)
Equivalent Single Axle Loads (ESALS) are used to measure the decrease in roadway quality over time. An ESAL
is defined as an 18,000 pound load on a single axle with dual tires. An ESAL should be thought of as a damage
factor. It is the average damage one vehicle has on the roadway, depending on structure and quality reduction. The
ESAL estimation is calculated by forecasting traffic the road is subject to over its design life, and then converted to
a specific number of ESALs. A typical ESAL estimation requires:
• A traffic volume count which is used as a starting point
• A count or estimation of the number of heavy vehicles
• An estimated traffic growth rate over the design life of the pavement
• Appropriate factors to convert truck traffic into ESALs
An ESAL forecast will apply the distribution of heavy vehicles to the ESAL factors and calculate the cumulative
ESAL loadings for a specific time period, typically 20 years.

TRAFFIC FORECASTING PROCESS FLOWCHART

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TRAFFIC FORECASTING & ANALYSIS WEBSITE
The main webpage from MnDOT’s Traffic Forecasting and Analysis Section is
http://www.dot.state.mn.us/traffic/data/index.html. There are links to find data and methods for the collection of
volume, vehicle classification, weight, vehicle miles traveled (VMT), and forecasts.
The most updated MnESAL excel spreadsheet, this forecasting manual, a study on the amount of historical traffic
volume data to use, vehicle classification groupings for forecasting, and a tabulation of previous forecasts can all
be found under data products at the bottom.
An overview of traffic forecasting and contact information for district traffic forecasters can be found under
collection methods.
The Traffic Mapping Application is also on the TFA website or by clicking this link:
http://mndotgis.dot.state.mn.us/tfa/Map. Traffic segments, vehicle class sites, ATR/WIM sites, AADT, and
HCAADT can all be found in this application.

TRAFFIC FORECASTING PROCEDURE

• Obtain general information about the forecast
• Create a map of the forecast
• Assemble the appropriate data
• Project the AADT for base year and design year
• Calculate vehicle type percentages
• Analyze 20 year flexible and rigid ESALs
• Submit forecast to Office of Traffic Data and Analysis and they will:
o Enter forecast into eDOCS
o Return approved forecast to the district forecast and materials engineer

MnESAL Program
The traffic forecasting Excel spreadsheet, called the MnESAL, was developed to calculate forecasted traffic
volumes and ESALs. The most updated version is available on the Traffic Forecasting and Analysis website under
Forecasts at the bottom: http://www.dot.state.mn.us/traffic/data/data-products.html
The MnESAL is made up of 9 different worksheets:
1. Instructions Page
2. Title Page
3. Cover Page
4. Forecast A (Least Squared Worksheet for the A segment)
5. ESAL A (ESAL Worksheet and Report for the A segment)
6. Forecast B 1-5 (Least Squared Worksheet for B segment(s))
o Generated on Cover Page
o Can have up to 5 B segments in each MnESAL excel spreadsheet
7. ESAL B 1-5 (ESAL Worksheet and Report for B segment(s))
o Generated on Cover Page
o Can have up to 5 B segments in each MnESAL excel spreadsheet
8. VC 1-4 (Vehicle Class Count Expansion Worksheets)
o Can have up to 4 years of Vehicle Class Data
9. VC Averages

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Inputs into the MnESAL program include:
• General Project Information
• Historic traffic volumes
• Historic vehicle classification breakdowns (Up to 4 years)
• Heavy 5+ Axle Semi percentage(s)
Outputs from the MnESAL program include:
• Projected average annual daily traffic (AADT) – base and design year
• Projected heavy commercial distribution (HCAADT) – base and design year by vehicle type
• Total 20 year design-lane cumulative ESALS (flexible and rigid)
• Flexible and Rigid total ESALS for 10, 15, 20, 25, 30, and 35 years.

STEPS TO CREATE A FORECAST

Obtain General Information about the Forecast

The first step is to determine the exact limits of the project and general information from the project manager or the
PPMS program listing in CHIMES: https://chimes.dot.state.mn.us/secure/login.asp
The link above will open to a home page where a User ID and password are needed. Once logged in, however, you
can type in the SP number and find all of the information for the project.
General information from PPMS will be entered on the Cover Page of the MnESAL. Information needed is
District, Letting Date, Program Category, Project Manager, SP Number, Route Number, Route Type, County, Beg
Reference Points, End Reference Points, Miles and Project Limits (Description).
Example of a PPMS:

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Create a map of the forecasted location
Maps are a good visual of the segments and sites that are being used for the forecast.
There are two types of segments that are used to forecast:
A segments: Any segment that contains a VC, ATR, or WIM site.
B segments: Any other segment within the forecast.
The association between A and B segments is called a Parent Child relationship. A is the Parent and B is the Child.
Each forecast requires at least one A segment because that is where the vehicle class data is located. The
relationship is based on distance and junction with major roadways. To determine the location of each segment and
their sequence numbers, visit the Traffic Mapping Application: http://mndotgis.dot.state.mn.us/tfa/Map
The Traffic Mapping Application, GIS, Google Maps, and others can be used to create maps for forecasts.
Shown to the right is an example of a Map
used for a forecast using GIS ArcMap:
In this example, there is one A segment
(sequence number 6401) containing VC
site 9098, and three B segments (sequence
number 6480, 6479, and 6491). The
forecasted construction area is shown in
orange. Since the forecasted construction
area does not contain a VC site, we are
required to use an A segment off of the
construction area. All segments that
contain part of the forecasted construction
area must be used. We can see that a
portion of all three B segments are in the
forecasted construction area. There are also
segment(s) in between CSAH 32 and 8th
Street SE that do not need to be forecasted
because they are not part of the
construction location and do not contain a
VC, ATR or WIM site. (Note any VC,
ATR, or WIM sites adjacent to the project,
or further along the trunk highway for
future reference.)

5
Fill out the MnESAL
At this point, PPMS and the forecast map show the information that is needed to fill out the MnESAL. The most
updated MnESAL spreadsheet is on the TFA website at the bottom under forecast:
http://www.dot.state.mn.us/traffic/data/data-products.html. Each MnESAL can only contain one A segment and up
to five B segments. If there is more than one A segment in the forecast, you must create a new MnESAL for every
additional A segment.
Note: Cells that are filled in with a light orange color indicate that information needs to be entered.

Title Sheet
General information like the forecast #, SP#,
Route Name and Description will automatically
transfer from the Cover Sheet.

Cover Sheet
Fill in general information about the forecast
listed on the PPMS. Light orange filled cells
denotes fields to be filled in. There is space
for remarks at the bottom for all additional
information.

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Forecast A Worksheet
This worksheet is used to forecast the AADT of the
base year and forecasted year. Enter information in
the light orange filled cells. Once the sequence
number is entered, the historical data will be listed to
the right of the print area. Click copy AADT over to
worksheet for the data to appear in cells A7:B22.
Linear regression projects that traffic will grow at a
constant rate based on the slope of historic data
(shown in the white box). Then, a county growth
factor is applied to reflect socioeconomic data trends
(shown in the yellow box). The county factors are
updated based on vehicle miles traveled (VMT). In
this example, the base year AADT is 3680 and the
forecasted year AADT is 5220.
Note: The MnESAL only allows for a minimum
growth rate of 0.5%.

Forecast B(s) Worksheet

The forecast worksheets for the B segment(s) are used the same as the A segment forecast worksheet (refer above).
The forecaster must complete a least squared worksheet for every segment along the project. On the cover page,
there is a drop down to select the number of B segments. The system only generates one B segment at a time.

Interpolation
In the Metropolitan Area, the Travel Demand Model should be used. This model estimates the projected AADTs
based on roadway and transit networks, population, land use, and employment data. MnDOT does not have a
statewide Travel Demand Model, therefore, in Greater Minnesota we rely on regression analysis for forecasting
traffic volumes.
To obtain the base year and future year AADT, the forecaster should interpolate between the last counted AADT
and the forecasted AADT from the Travel Demand Model.
In this example, all of the segments were last counted in 2016, the Travel Demand Model produced AADT’s in
2040, the base year is 2019 and the future year is 2039.

The 2019 and 2039 AADTs for all of the segments should be entered in the MnESAL on the Forecast Worksheets.
These values will go in the yellow box at the bottom to then be transferred to other worksheets.
VC 1-4 Worksheets
The heavy commercial traffic (HCAADT) from vehicle classification counts are determined using these
worksheets. Enter the site number and the count year for the four most recent years of data. The worksheet will
automatically fill in afterwards. The manual (16 hour) and tube (48 hour) counts have different formats, but the
vehicle type breakdowns are the same. Note: for tube counts, motorcycles and passenger vehicles are added
together.

The raw count data is located in the yellow cells above. The raw data is then adjusted for the month the count was
taken, whether it is a tube (24 hour) count or manual (16 hour) count, and if the location is in a rural or urban area.
These factors were developed by looking at continuous ATR and WIM data. Click here to learn more about the 24
hour and 16 hour adjustment factors. The AADT adjusted factors are multiplied by the raw data to get the adjusted
data. The adjusted total is constrained by the AADT in the count year.
The axle correction factor (ACF), shown above on the right side of the worksheet, is the total number of vehicles
divided by half of the total number of axles to account for trucks with more than two axles. Click here to learn
more.
The VC 1-4 worksheets do not need to be filled out when using ATR or WIM data. Since ATR and WIM sites are
counting traffic continuously, the data does not need to be adjusted.
VC Average Worksheet
This worksheet shows the average of the truck volumes and percentages. All of the data is automatically
transferred from the VC 1-4 worksheets. Any columns that are not being used, may be erased.
A manual count is needed to obtain the heavy 5+ axle semi percentage. In this example, a manual count was taken
in 1994 and was one of the four most recent years of data. If one or more manual count(s) were taken at the site,
but were not the four most recent years of data, provide the heavy 5+ axle semi percentages(s) in cells D20, F20,
H20 and J20. Only one manual count is needed but if there are multiple manual counts, the spreadsheet will take
the average of the heavy 5+ axle semi percentages. If the average of the heavy 5+ axle semis percentage is greater
than 30%, then the heavies will split causing the ESALs to be higher. In this example the heavy 5+ axle semis split
at 32.8%. If the 5+ axle semis split, they are broken down into “Maximum” and “Other”. The max is 0.69% and the
other is 1.41% in this example. Click here to learn more about manual counts.
When using an ATR or WIM site, the VC 1-4 worksheets are not used so the forecaster should enter in the four
most recent years of data manually in cells C10:C17, E10:E17, G10:G17, and I10:I17. Since ATR and WIM sites
do not breakdown the 5+ axle semis, the forecast should look at nearby VC sites containing manual counts. (If a
VC site is used, but does not contain a manual count, nearby VC sites should also be used.) Look for manual
counts on the same route as the project and in the surrounding area. The forecaster should use their best judgement
on the amount and where the heavy 5+ axle semis are traveling.
It is important to compare the truck volume to other years. If there is a year that is not consistent with the others, it
should be thrown out and replaced with the next most recent year. Some sites may not have four years of data and
that is okay, as long as the average truck volumes are most accurate to the forecaster’s knowledge.
ESAL A Worksheet and Report
The ESAL worksheet and report will calculate
values automatically from data being
transferred from other worksheets.
The base year proportions are directly
transferred from the average vehicle percent
column of the VC Average Worksheet above.
The average heavy 5+ axle split information is
also transferred to the ESAL Worksheet. In
our example, the heavy 5+ axle semis split.
Therefore, there is zero for 5AX+ TST. The
5+ axle semis are broken into max (0.69%)
and other (1.41%). If the heavy 5+ axle semis
did not split, the sum of max and other
(2.10%) would indicate 5AX+ TST, and there
would be a zero for max and other.
The MnESAL defaults to two-way roads. The
drop down in cell C3 can be changed to one-
way for roads, ramps, and roundabouts. This
information along with the number of lanes is
needed to calculate the design lane factor
(DLF). Click here to learn more.
The ESAL factors for flexible and rigid are
shown at the bottom of the worksheet above.
Flexible is bituminous and rigid is concrete.
The 20 year cumulative equivalent single axle
loads (ESALS) for this forecast is 921,000 for
flexible and 1,354,000 for rigid. The 10, 15, 25,
30, and 35 year cumulative ESALs are also
shown to the left on the Cumulative ESAL
Report.
ESAL B(s) Worksheet and Report
The ESALs for B segment(s) are computed similar to an A segment besides Urban and Rural defaults (shown
below in the light gray table) are used to obtain the base year proportions.
The % change from the A segment located on the right side of the worksheet must be between -50% and 50%.
Change User Adjustment to Base/Future Yr Vol accordingly (shown in orange).

The B segment(s) represent the addition or

subtraction of trucks on the trunk highway system
to or from other road systems. Thus, the B concept
is a way to forecast traffic and ESALS along a
roadway using vehicle class data from another
segment.

Click here to see Urban and Rural defaults

percentages by AADT range.
In this example the 20 year cumulative equivalent
single axle loads (ESALS) for this forecast is
1,270,000 for flexible and 1,856,000 for rigid.
Similar to the A segment, there are also 10, 15, 25,
30, and 35 year cumulative ESALs listed on the
Cumulative ESAL Report (shown to the right).
Note: There are small “safety factor” built into
formulas throughout the MnESAL. This is
provided in case of future changes in truck
regulations and changes to truck weight laws.
Submit forecast to the Office of Traffic Forecasting and Analysis
The forecast should be a PDF saved as: F + district number – last two digits of the current year + two digit
sequential requested order
Example F2-1704: In district 2, the current year is 2017 and the forth report requested in 2017
Order of report:
Title Sheet
Cover Sheet
Project Location Map
ESAL A Report and Worksheet
ESAL B Reports(s) and Worksheet(s)
Appendix
Least Square Analysis
Vehicle Class Expansion Worksheet
Vehicle Class Reports
AADT Diagram
Other Supporting Documents including PPMS

Once approved, the forecast will be entered into the statewide database (eDOCs) and returned to the district
forecaster and material engineers.
A tabulation of previous forecasts is on TDA’s website at the bottom under forecast:
http://www.dot.state.mn.us/traffic/data/data-products.html.

Note: This manual cannot attempt to cover every situation that forecasters may encounter.

MnDOT STATE AID AND

CONSTRUCTION DISTRICTS
The state is broken into state aid districts and
construction districts. Forecasters follow the
construction districts when performing
forecasts, therefore, some forecaster’s
complete forecasts outside of the district they
work in.
TRAFFIC DATA COLLECTION
Minnesota’s traffic data collection program is designed to gain an understanding of the volume and type of heavy
commercial vehicles that are utilizing Minnesota’s Highway System. The Highway System consist of Interstates,
US Highways, and State Truck Highways. Some data is also collected on County State Aid Highways (CSAH),
County Roads (CR), and Municipal State Aid Streets (MSAS).
The Traffic Forecasting and Analysis Section rely on several data collection devices to produce forecasts. The data
collected is available to our clients through our website or by our analysts if special requests are made. Some
principle users are forecasters, programmers, planners, preliminary design engineers, safety engineers, and the
Federal Highway Administration.

Tube Counts
The most frequently used device is pneumatic tube counters. The pneumatic tubes are placed across the roadway
surface to count axles and measure axle spacing. The tubes are supplied by the Office of Transportation Data and
Analysis.
There are two types of tube counts:
• Single tube count – collects volume data
• Double tube count – collects volume and vehicle classification data
The majority of traffic data is collected by MnDOT District staff, but some Counties and Cities, especially the
Metro, submit their own count data. Most traffic counting occurs on weekdays between April and October of each
year. The official traffic volume maps are posted on the website the following spring. Click here to look at the
Traffic Counting Schedule.

The vehicle classification data from double tube counts are developed by measuring the vehicle’s axle
configurations and spacing. All vehicle classifiers collect data based on the FHWA classification scheme shown
below.
The FHWA classification data is then fit into MnDOT’s 13 different classes shown below. The difference between
the two classification schemes is that the FHWA scheme has truck with trailers in class 3 and buses in class 4, but
MnDOT’s scheme has trucks with trailers and buses together in class 4.

Some locations with high traffic are unsafe for people to walk across the street to lay down tubes. If a single tube
count is needed at an unsafe location, Wavetronix radar units can be used to collect volume. Wavetronix radar also
counts vehicle type, but it can only separate the data into four classes, which is not useful for forecasting.
Therefore, if a double tube count is needed at an unsafe location, a video camera can be set out and used to count
the 13 different vehicle classes manually.
Single tube counts, double tube counts, Wavetronix radar counts and video camera counts are generally taken for a
48 hour period. Click here to see an example of double tube data.
MnDOT’s 13 vehicle classes then get joined into 8 classes. The 8 vehicle classes (shown below) are used in the
MnESAL for forecasting.

Vehicle Class Groupings for Forecasting

1. Passenger Vehicles = Motorcycles + Cars + Pickups
[Class 1 + 2 + 3]
2. 2 Axle Single Unit = 2AXSU
[Class 5]
3. 3+ Axle Single Unit = 3+AXSU + 4+AXSU
[Class 6 + 7]
4. 3 Axle Semi = 3&4SEMI * 0.35
[Class 8 * 0.35]
5. 4 Axle Semi = 3&4SEMI * 0.65
[Class 8 * 0.35]
6. 5+ Axle Semi = 5AXSEMI + 6+AXSEMI
[Class 9 + 10]
7. Heavy Truck with Trailer / Bus = HTWT & BUS
[Class 4]
8. Twins = TWINS 1 + TWINS 2 + TWINS 3
[Class 11 + 12 + 13]

Click here to see a breakdown of the 8 Vehicle Types for Forecasting.

Automatic Traffic Recorder (ATR)
Automatic Traffic Recorders (ATR) are devices with magnetic loops and/or piezo sensors in the pavement that
continuously collect data. ATRs come in four difference configurations:
• Single Loop per Lane – collects volume data
• Double Loops per Lane – collects volume and speed data
• Piezo ATR – collects volume, speed, and vehicle classification data
• Weigh-in-motion (WIM) – collects volume, speed, vehicle classification, and weight

These sensors are all located at sites that have a cabinet

with power and phone lines.
ATR sites collect data 24 hours a day, seven days a week,
and 365 days per year. They are the most valuable
component of our traffic data collection system. By
obtaining complete coverage, we are able to establish
hourly, daily, weekly, and monthly variations of traffic
flow. We are also able to develop factors that are used to
adjust shorter duration counts to annual average daily
traffic (AADT) and heavy commercial annual average
daily traffic (HCAADT). Click here to learn more about
adjustment factors.

Weigh-In-Motion (WIM)
Weigh-in-motion sites are permanent devices in the road that continually collect and store axle weight data. WIM
sites have two Kistler piezo sensors and two magnetic loops. The device collects volume, speed, vehicle
classification, and weight data.
WIM sites classify vehicles based on axle configuration in combination with weight on the front axle. The data also
provides factors that are used to expand shorter counts. In addition, WIM sites include ESAL factors for truck types,
and axle weights.
The data collected consists of axle weight, gross weight, axle spacing, vehicle length, vehicle type, speed, time,
lane, and equivalent single axle load (ESALS). ESALS are calculated based on the weight of individual axles or
groups of axles; not on gross weight. Processing of weight data is done by vendor software, which produces
summary tables. The purpose is to produce WIM reports to calculate and update ESAL factors. Click here to learn
more about ESALs.
Over time the loops and piezos used at ATR and WIM sites stop working and need to be replaced. The Office of
Transportation Data & Analysis pay for the installation and maintenance of the ATR and WIM site.
Manual Counts
Manual counts are taken by someone going to a site and manually keeping record on paper or on a laptop of the
vehicles passing. Manual counts collect vehicle classification data including the six different 5 axle semi types.
Most manual counts have been taken for 16 hours. Recently, they have been counted for 4 hours and then adjusted
to a 16 hour count by using the monthly and seasonal factors developed from the ATR and WIM data. Then
adjusted again for the missing 8 hours in a day and the effect of weekends to change the 16 hour manual count to
Annual Average Daily Traffic (AADT) and Heavy Commercial Annual Average Daily Traffic (HCAADT). In
general, a 16 hour volume count is about 90% of a 24 hour volume count. Click here to see more analysis on 16
hour volume count traffic behavior.
In order to obtain an accurate ESAL forecast, it is important to know the percentage of heavy 5+ axle semis
because they typically do the most amount of damage to the roads. The heavy semis are tank trucks, dump trucks,
grain trucks, and stake loaded trucks. Click here to see example of heavy 5+ axle semi types. Manual counts are
the only counts that classify the different 5 axle trucks.
Example of obtaining the percent of heavy 5+ axle semis from a manual count:

Heavy 5+ axle semis: (2+10+47+13) / (2+10+47+13+4+23+6) = 72 / 105 = 68.6% heavies

TRAFFIC MONITORING PROGRAM OVERVIEW
Methods used for collection:

1. Short Duration Counts (48 hour tube counts)

o Volume Sites (Single Tube)
o Collects traffic volumes
o Vehicle Classification Sites (Double Tube)
o Collects volume and vehicle classification

2. Automatic Traffic Recorder (ATR)

o In-pavement sensors
o Collects volume, vehicle classification and/or speed

3. Weigh in Motion System (WIM)

o In-pavement sensor
o Collects volume, vehicle classification, speed, and weight

4. Manual counts (4 hour counts)

o Collects vehicle classification including the different 5 axle semi types

5. Regional Traffic Management Center (RTMC)

o Annual duration vehicle counts
o Primary purpose is traffic management
o Data is stored, processed and converted to an AADT

The data collected is used for:

1. Annual reporting of Vehicle Miles Traveled (VMT) and AADT estimates to the Federal Highway
Administration (FHWA) for use in Federal level travel analysis and determination of funds.

2. Traffic volume data is used in the formula for annual allocation of state funds for roadway maintenance
and construction on the County and Municipal State Aid road system.

3. Providing information to help facilitate decision making for planners, engineers, forecasters, businesses,
and the general public.

Produces AADT estimates on:

• Truck Highways (Interstates, US Highways, and MN Highways)
• County State Aid Highways (CSAH)
• County Roads
• Municipal State Aid Roads (MSAS)
RESOURCES
The Office of Transportation Data and Analysis is the source of the data needed for traffic forecasting. Each
district forecasters is provided with the following resources:
• Traffic Volume Maps – located on the TDA website are metro, county, and municipality AADT maps:
http://www.dot.state.mn.us/traffic/data/data-products.html
Official AADT is published each spring from the previous year’s data and can be viewed by going to
Traffic Mapping Application on our website: http://www.dot.state.mn.us/traffic/data/tma.html
Draft AADT can be viewed in the Traffic Mapping Application as it becomes available in the fall of the
year it is counted. These values are considered DRAFT ONLY, so they have the potential of changing
before the official product is released in the spring.
• Vehicle Class site maps – located on the TDA website: http://www.dot.state.mn.us/traffic/data/data-
products.html
All vehicle class and manual counts can be obtained by contacting the Traffic Forecast Unit. The districts
collect copies of the raw vehicle class counts and store in their office.
• ATR and WIM data – can be found on the TDA website: http://www.dot.state.mn.us/traffic/data/data-
products.html

• Special Requests for Vehicle Class Counts – If a forecaster knows of a particular project in their district
that does not have recent data, they can request to have it counted as a special count for the upcoming
summer season.

• Previous forecasts – eDOCS:

http://edms/cyberdocs/Libraries/Default_Library/Groups/MNDOT_USERS/frameset.asp

If you have any questions, comments or would like further information please feel free to contact our office:
Christy Prentice (Volume Data): Christy.Prentice@state.mn.us
John Hackett (Vehicle Class Data): John.Hackett@state.mn.us
Ian Vaagenes (WIM and ATR Data): Ian.Vaagenes@state.mn.us

For additional resources, forecasters may want to contact the State Demographic Office, the Minnesota Department
of Employment and Economic Security, Metropolitan Planning Organizations, Area Transportation Partnerships,
Regional Development Commissions, and City or County Traffic Engineers. City and county engineers can
provide information about land use developments, and future projects that may cause detours and changes in traffic
patterns. The State Demographic Office can provide information on population, household, labor force, and
income data by county and city. The Minnesota Department of Economic Security has useful information on
employment by industry and region.
AXLE CORRECTION FACTORS
The axle correction factor (ACF) adjusts tube counts to correct AADT by accounting for trucks.

Axle Correction Factor

Vehicle Total number of Number of Total Axles
Vehicles Axles
Cars 1000 X 2 = 2000
2 AX SU 100 X 2 = 200
3+ AX SU 50 X 3 = 150
3 AX SEMI 25 X 3 = 75
4 AX SEMI 25 X 4 = 100
5+ AX SEMI 300 X 5 = 1500
TT/BUS 50 X 4 = 200
TWINS 50 X 5 = 250
Total 1600 4475

If we assume that there are 2 axles per vehicle, then 4475 / 2 = 2238 instead of 1600 vehicles. To
correct this assumption, take 1600 / 2238 = 0.71. Therefore, 0.71 is the axle correction factor.
The axle correction factor is shown on the Vehicle Class Count Expansion Worksheets (VC 1-4) and the Vehicle
Class Count Averages Worksheet (VC Avg) in the MnESAL.

DESIGN LANE FACTOR

Design Lane Factor (DLF) is used to estimate traffic volume and truck components on the heaviest traveled lanes
for the purposes of ESAL estimation. The design lane factor is shown on the Cumulative ESAL worksheet(s).
Forecasts are performed for the design lane only. For example, if we are forecasting at a 4 lane, two-way road. We
assume that there will be 45% of the total vehicles in the driving lane for each direction, and 5% in the passing lane
for each direction.
ADJUSTMENT FACTORS
The forecasting process assumes that the raw data taken on a typical weekday can be expanded to represent
average annual daily traffic (AADT) by using adjustment factors derived from ATR and WIM data.

24 Hour Adjustment Factors

The factors are categorized into urban and rural areas. For estimating equivalent single axle loads (ESALS), the
eight vehicle types need to be adjusted for the month of the year and the effects of weekend traffic. These factors
are applied to the raw counts in the MnESAL to produce an estimate of AADT by vehicle type.

2013 24 Hour Seasonal Adjustment Factors for Urban Areas in MNESAL

Body Type Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
CARS+PICKUP 1.08 1.04 1.04 0.97 0.97 0.96 0.91 0.90 0.93 0.88 0.97 1
2ASU 0.96 0.88 0.92 0.90 0.89 0.86 0.80 0.76 0.83 0.76 0.79 0.84
3+ASU 1.23 1.16 1.21 0.86 0.75 0.67 0.59 0.54 0.64 0.64 0.80 1.09
3A SEMI 1.24 1.18 1.02 0.88 0.86 0.80 0.74 0.70 0.72 0.71 0.87 1.17
4A SEMI 1.24 1.18 1.02 0.88 0.86 0.80 0.74 0.70 0.72 0.71 0.87 1.17
5+A SEMI 1.02 0.99 1.00 0.79 0.75 0.71 0.69 0.65 0.70 0.76 0.76 0.99
TT/BUS 1.51 1.31 1.19 1.03 0.92 0.82 0.76 0.71 0.74 0.77 0.94 1.07
TWINS 1.07 1.02 1.02 0.84 0.78 0.74 0.69 0.65 0.67 0.77 0.93 1.09

2013 24 Hour Seasonal Adjustment Factors for Rural Areas in MNESAL

Body Type Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
CARS+PICKUP 1.31 1.23 1.19 1.06 0.98 0.92 0.84 0.88 0.91 0.95 1.08 1.12
2ASU 1.02 0.93 0.96 0.89 0.85 0.87 0.83 0.83 0.76 0.77 0.88 1.00
3+ASU 1.24 1.17 1.12 0.89 0.76 0.71 0.70 0.66 0.65 0.64 0.86 1.09
3A SEMI 1.25 1.15 1.11 0.97 0.84 0.77 0.72 0.72 0.72 0.83 1.07 1.25
4A SEMI 1.25 1.15 1.11 0.97 0.84 0.77 0.72 0.72 0.72 0.83 1.07 1.25
5+A SEMI 0.93 0.86 0.87 0.82 0.79 0.79 0.82 0.78 0.80 0.73 0.87 0.90
TT/BUS 1.60 1.44 1.31 0.99 0.81 0.75 0.67 0.68 0.70 0.68 0.96 1.40
TWINS 0.95 0.86 0.92 0.86 0.86 0.75 0.80 0.76 0.75 0.70 0.82 0.76

16 Hour Adjustment Factors

These factors are used to adjust 16 hour counts to 24 hours for each vehicle types. The 16 hour traffic volume is
the summation of each vehicle type counted from 6:00 AM to 10:00 PM. The summation of 24 hour volumes are
divided by the 16 hour volumes for each vehicle type to obtain the adjustment factors. The raw 16 hour volume
data is multiplied by the adjustment factors to obtain the 24 hour volumes for each vehicle type. The table below
shows the 16 hours as a percent of 24 hours and the factors using all vehicle class sites from 1998-2016.
Vehicle Class 16 Hour 16 of 24
Sums (6:00am – 10:00pm) 24 Hour Percentages Factor
Passenger vehicles 25244083 27503057 91.79% 1.09
2 Ax Single Unit 848142 913110 92.88% 1.08
3+ Ax Single Unit 320733 343950 93.25% 1.07
3 Ax Semi 273895 301059 90.98% 1.10
4 Ax Semi 66498 70432 94.42% 1.10
5+ Ax Semi 1109569 1292011 85.88% 1.17
Bus and HTWT 218106 239739 90.98% 1.09
Twins 42655 56922 74.94% 1.30
Total Vehicles 28123681 30820280 91.25%
Analysis of a 16 Hour Count
Typically, a 16 hour count from 6:00am-10:00pm is roughly 90% of the 24 hour total. This statement holds true
for both 24 hour total vehicles and 24 hour total passenger vehicles (motorcycles, cars, pickup trucks, and vans)
due to the large amount of passenger vehicles compared to heavy commercial traffic. The graph below shows a
typical week day traffic pattern between vehicle classes.

16 of 24 Hour Percentages (All Vehicle Sites 1998-2016)

10.00%
Percentages

8.00%
6.00%
4.00%
2.00%
0.00%
12:00:00 AM
1:00:00 AM
2:00:00 AM
3:00:00 AM
4:00:00 AM
5:00:00 AM
6:00:00 AM
7:00:00 AM
8:00:00 AM
9:00:00 AM
10:00:00 AM
11:00:00 AM
12:00:00 PM
1:00:00 PM
2:00:00 PM
3:00:00 PM
4:00:00 PM
5:00:00 PM
6:00:00 PM
7:00:00 PM
8:00:00 PM
9:00:00 PM
10:00:00 PM
11:00:00 PM
Hours
Tot Veh Pas Veh 2axsu 3+axsu 3ax semi
4ax semi 5ax semi TT/BUS Twins

Typically, passenger vehicles have an AM peak around 7:00am and a PM peak between 4:00-5:00pm. Trucks
display a bell shaped traffic pattern between 8:00am-3:00pm. Many larger semis travel between 12:00am-5:00am to
avoid general car flow. Delivery trucks (2 and 3 axle single units) operate mid-day between the AM and PM peaks.

Traffic Behavior of 16 Hour Volume Counts

In general, disregarding seasonal variations, a 16 hour volume count from 6:00am to 10:00pm is:
• About 90% of the 24 hour volume total, consisting of about 92% of the cars.
• About the same volume as the HCAADT for the year at that site.
• Growing faster on higher volume routes than on lower volume routes for both rural and urban areas.
o Note: when going from a rural area into a town on a trunk highway, trucks increase by about 2-7%.
A small increase (2%) means there are very few 5 axle semis. A larger increase (7%) means there
are significantly more 5 axle semis.

HOURLY DISTRIBUTIONS OF TRAFFIC BY VEHICLE TYPE

An analysis of hourly tube counts from the vehicle class program has revealed certain hourly trends. Excluding
short count and manual count analysis, it is helpful to have guidelines of hourly distribution of traffic when nothing
else is known. We can estimate the hourly distribution of truck type by factoring the hour(s) compared to AADT or
other 24 hour tube counts.
The tables below shows a statistical average of trend data from the vehicle class tube counts taken between 1998
and 2016. For an example, say you have 20 5+ axle semis from 8:00am-9:00am. The forecaster could use the
8:00am factor (16.78) and multiple it by 20 to get 336 5+ axle semis in a typically 24 hour volume count. This is
strictly another analysis tool, and should not be used in project level analysis.
Hourly Expanding
We can use the hourly traffic distributions above to calculate the estimated 24 hour volume by vehicle type. For an
example, say we have a tube count from 11:00am-12:00pm grouped by vehicle type. The one hour volume is
multiplied by the percentages above to get the daily (24 hour) volume by vehicle type used for forecasting. This
data could then be added to the MnESAL Vehicle Class Expansion Worksheet.

This method may be used on streets or roadways where vehicle class data is unavailable. A minimum of four hours
that covers the morning or afternoon peak is recommended for project level forecasts. In this example, the forecast
should request a special count to obtain more data.
DESIGN HOURLY VOLUME (DHV)
The design hourly volume is derived from the 30th highest hour in the year. The design hourly volume is similar to
the peak hour volumes used primarily in the Metro area. In Greater Minnesota, we refer to the peak hour volumes
as DHV or the 30th highest hour.
ATR and WIM sites are the only source from which we can obtain DHV. The data can be found at
http://www.dot.state.mn.us/traffic/data/data-products.html under Volume listed as ATR/WIM Highest Volume
Report. The design hourly volume is available by direction, but frequently requested for both directions. There is a
DHV summary and AADT at the bottom of the report. The data is also available by month and hour.
A study of historical ATR data revealed that the average DHV is from 8% in town, and 10-13% out of town. The
average 30th highest hour on a rural trunk highway is about 10% of the AADT. If the AADT is 3000, and you
determine that DHV both directions is 10%. Then the DHV is 300, which is the maximum vehicles on the roadway
per hour in both directions.

ESAL CONCEPT
An ESAL measures the amount of damage being done on a roadway over time. One ESAL is defined as an 18,000
pound load on a single axle with dual tires.
Below is a table of the ESAL factors for single and tandem axles by gross axle weight in pounds (lbs.). Using the
ESAL factors below, consider a 5 axle semi-truck that has a 12,000 pound single axle (0.189) in the front and two
34,000 pound tandem axles (1.095). The ESAL factor for the 80,000 pound 5 axle semi is 2.39.

In this example, we considered that 50 fully loaded (80,000 pound) 5+ axle semis per day over the 20 year period
of a bituminous roadway produces 876,960 ESALs for flexible pavement.
ESAL EQUIVALENCE FACTORS FOR FLEXIBLE PAVEMENT
18- Kip Axle Equivalence Factors Flexible Pavement
Gross Axle Single Axles Tandem Gross Axle Single Axles Tandem
Load (lbs.) Axles Load (lbs.) Axles
1,000 0.00002 41,000 23.27 2.29
2,000 0.00018 42,000 25.64 2.51
3,000 0.00072 43,000 28.22 2.75
4,000 0.00209 44,000 31 3
5,000 0.005 45,000 34 3.27
6,000 0.01043 46,000 37.24 3.55
7,000 0.0196 47,000 40.74 3.85
8,000 0.0343 48,000 44.5 4.17
9,000 0.0562 49,000 48.54 4.51
10,000 0.0877 0.00688 50,000 52.88 4.86
11,000 0.1311 0.01008 51,000 5.23
12,000 0.189 0.0144 52,000 5.63
13,000 0.264 0.0199 53,000 6.04
14,000 0.36 0.027 54,000 6.47
15,000 0.478 0.036 55,000 6.93
16,000 0.623 0.0472 56,000 7.41
17,000 0.796 0.0608 57,000 7.92
18,000 1 0.0773 58,000 8.45
19,000 1.24 0.0971 59,000 9.01
20,000 1.51 0.1206 60,000 9.59
21,000 1.83 0.148 61,000 10.2
22,000 2.18 0.18 62,000 10.84
23,000 2.58 0.217 63,000 11.52
24,000 3.03 0.26 64,000 12.22
25,000 3.53 0.308 65,000 12.96
26,000 4.09 0.364 66,000 13.73
27,000 4.71 0.426 67,000 14.54
28,000 5.39 0.495 68,000 15.38
29,000 6.14 0.572 69,000 16.26
30,000 6.97 0.658 70,000 17.19
31,000 7.88 0.753 71,000 18.15
32,000 8.8 0.857 72,000 19.16
33,000 9.98 0.971 73,000 20.22
34,000 11.18 1.095 74,000 21.32
35,000 12.5 1.23 75,000 22.47
36,000 13.93 1.38 76,000 23.66
37,000 15.5 1.53 77,000 24.91
38,000 17.2 1.7 78,000 26.22
39,000 19.06 1.89 79,000 27.58
40,000 21.08 2.08 80,000 28.99
TRUCK WEIGHTS AND AXLE CONFIGURATIONS
The table below is the standard ESAL factors in the MnESAL.

Sometimes it is necessary to change the ESAL factors for various heavy trunk movement when information
becomes available. In the two examples below, the ESAL default is 0.58. However, both examples have a higher
ESAL factor than the default. Therefore, the forecaster could change the ESAL factor in the MnESAL, but should
only if they have information of heavier trucks on the roadway.
Examples of Configurations:
• A typical loaded 4 axle single unit gravel truck

• A heavy 3 axle single unit gravel truck

Example of Modifying Default ESAL Values for Heavy Trucks

The information below are averages derived from the State Patrol and can be used to determine the weight for 2, 3,
and 4 axle single unit gravel dump trucks loaded. The numbers include gross vehicle weight (GVW), front axle
and rear group (tandem or tridem). Assume there are 100 unloaded trucks and 200 heavy loaded gravel trucks.
1. 2-axle dump truck – 33,000 GVW. Up to 13,000 steering axle and 20,000 drive axle
 2. 3-axle dump truck – 45,000 GVW. Up to 13,000 steering axle and 34,000 tandem

3. 4-axle dump truck – 57,000 GVW. 14,000+ on steering axle and 43,000 tridem

All of the ESAL examples above have been for flexible ESALs. The rigid ESAL is the concrete equivalent to the
bituminous number. The rigid ESALs are always higher than the flexible ESALs. The flexible and rigid ESALs do
not relate to one another. They are results of the formula used in the process that develops the factors. The
summation of total vehicle volumes by class are equal. The only difference is in the results of the formula.

Transit, Bus, and ESAL Information

Recent research has shown that in many cases
ESALS have been underestimated for buses,
especially heavy loaded regular and
articulated Metropolitan Transport
Corporation (MTC) buses. A regular MTC
bus is 40 feet. It weighs about 29,000 pounds
empty and about 35,000 pounds full (150
pound person with 43 seats). An articulated
MTC bus has 3 axles and is 60 feet long. It
weighs about 41,500 pounds empty and
51,000 pounds full (150 pound person with 65
seats).

Our current ESAL factors for buses (which

we lump in with truck trailers) is 0.51 for
flexible and 0.53 for rigid. Therefore, if a
forecaster knows their route is a bus lane
facility and contains MTC buses, they should
increase the ESAL factors on the A and B
ESAL worksheet(s) in the MnESAL.
Sugar Beet Routes
The data below was taken on a sugar beet hauling route. These routes show additional 4 axle semis and 5 axle
semis that should be added to the Vehicle Type Breakdown for ESAL Calc. Trucks are underestimated when the
data is not taken during the sugar beet hauling season, therefore, trucks have to be added to the data. These
additional trucks are assumed to be spread out over the entire year. It is important to accurately estimate the
number of heavy trucks because they have the largest impact on ESALs. Below is the bottom portion of tube data
taken on a sugar beet hauling route. In this example, the raw data that is entered in the MnESAL on the expansion
worksheet would be (51 + 56) = 107 for 4 axle semis and (34 + 66) = 100 for 5+ axle semis.

ESAL THRESHOLDS
Forecasters should show more concern of forecasts that are at or near a threshold.

County Road Thresholds

Category ESALs
Low Less than 250,000
Medium 250,000 – 600,000
High 600,000 – 1,000,000

Truck Highway Thresholds

Category ESALs
Very Low Less than 300,000
Low 300,000 – 1,000,000
Medium 1,000,000 – 7,000,000
High (Choice of Bituminous or Concrete) 7,000,000 – 10,000,000
Very High (Concrete) 10,000,000 and Greater
PAVEMENT SECTION PROCESS AND ESALS
(From Technical Memorandum No. 04-06-MAR-01)
There are three pavement section process categories:
1. District Process – where short projects meet the following criteria:
• Two-Lane Roadways – Projects less than 2 miles long
• Projects less than 30,000 square yards

The projects length/size listed above are determined using only the driving lanes, no turn lanes, parking
lanes or auxiliary lanes.

2. Informal Process - involves determining the pavement type based on the amount of traffic, as measured by
the length-weighted Bituminous Equivalent Standard Axle Loads (BESALs), and the sub grade soil
strength.
• Informal Flexible: Projects where the 20-year design lane BESALS (flexible /bituminous) are 7
million or less and the design sub grade R-value is greater than 40. Projects in this category will be
constructed with bituminous.
• Informal Rigid: Projects where the 20-year design lane BESALS exceed 10 million. Projects in this
category will be constructed with concrete.

3. Formal Process – All projects not meeting the Informal criteria listed above. The pavement type will be
determined by a detailed cost estimate

MNPAVE
A program called MnPAVE is being used for flexible pavement design purposes. An ESAL combined with an R-
value determines structural design. The MnPAVE model inputs such as climate, road structure, and load spectra
may be used to determine potential pavement designs. Thus, in the future, ESALs might no longer be produced,
rather, we will be providing designers with traffic inputs necessary to use the new American Association of State
Highway Officials (AASHTO) pavement design software.
ADDITONAL PRODUCTS

Planning Tool
Every year it is a federal requirement that the Traffic Data & Analysis section produces a 20 year forecasted
AADT and HCAADT on every segment of roadway in Minnesota. The planning tool uses least squares linear
regression to calculate the 20 year projections and an annual growth rate for both AADT and HCAADT. The
segments are identified by sequence number. Additional fields include county, district, route system, route number,
location description, route identification, beginning and ending true miles, beginning and ending reference points,
vehicle class site, historical AADT and heavy commercial as a percent of AADT.
Other than actual historical data, the 20 year forecasted volumes are only to be used for system wide or district
planning purposes. They are not to be used for project specific analysis or project level forecasting. Contact the
Traffic Forecast & Analysis section to receive information from the Planning Tool.

ESAL Forecasting Tool

Annually, a historical record is updated with the new expanded historical vehicle class data by site. This
spreadsheet contains the same expanded vehicle class data derived from the MnESAL process. This data is the
output from the expansion of raw counts that shows up on the Vehicle Class Count Averages Worksheet. Using the
expanded data, the ESAL Forecasting Tool calculates the 10, 15, 20, 25, 30, and 35 year flexible and rigid ESALs
from the entered base year. The spreadsheet also shows the yearly actual and estimated HCAADT. Additional
fields include district, county, location description, route, axle correction factor (ACF), HC%, number of lanes,
design lane factor (DLF), annual growth rate, beginning and ending true miles, and beginning and ending reference
points.

The ESAL Forecasting Tool is to be used for preliminary ESAL planning for resurfacing and reconditioning
projects. Contact the Traffic Forecast & Analyst section to receive information and data regarding this tool.

ESAL Calculator
This tool was created by State Aid and is used to estimate the 20 and 35 year flexible and rigid ESALs on low
AADT roadways. Inputs are project information, base year, number of lanes, and four years of historical AADT
data. The ESAL default factors are used to calculate the forecasted ESALs. The ESAL calculator can be found at
this link under Pavement Design Tools: http://www.dot.state.mn.us/stateaid/pavement.html.

Contact State Aid Pavement Engineer, Joel Ulring at Joel.Ulring@state.mn.us if you have any questions regarding
this tool.
Roundabout Tool
When forecasting a roundabout, the forecaster needs to know
the AADT and vehicle class data on all four legs on the
roundabout. The urban or rural vehicle type defaults should
be used on the legs that do not contains vehicle class data. To
the right is an example of a roundabout at MN 3 and CSAH
26/70th Street in Inver Grove Heights.

The forecaster should first input the data of all four legs into the MnESAL. Then copy the AADT and vehicle class
volumes for base year and future year from the ESAL worksheets into the roundabout tool (shown in red below).

Once the data is in the roundabout tool for all four legs, then the roundabout data will show in the gray box on the
right side (shown below). There is data for the average of all four legs and the leg with the highest volume. The
forecaster should use the highest volume because the legs with volumes lower than the average will be
underestimated. It is always better to overestimate ESALs so the design of the road will last longer. Next, copy the
highest volume vehicle class data and percentages into the ESAL worksheet of the MnESAL for the roundabout
(shown in green below).
Now the forecaster has the ESALs for all four legs of the roundabout and the actual roundabout itself.
ADDITIONAL FORECAST KNOWLEDGE
Obtaining Data from a 3 Legged Intersection
Below are formulas to calculate the unknown volume of a leg if the volume of the other two legs are known

Traffic Forecasting from Proposed (Non-Existent) Roadways

This section is designed to outline the procedures for completing traffic and load forecasts on new roadways such
as bypasses, new alignments, or new routes for which there is no existing route serving a similar trip purpose.
The forecaster must use their best judgment as to which and how many vehicle class sites should be used to
represent all or a portion of the new roadways or new alignment. The forecaster may use an average of two or
more vehicle class site percentages to represent the movement on a particular roadway. It is important to
distinguish where the truck movements originate from and where it is headed. This will ultimately help determine
the vehicle type percentages affecting any particular roadway.

Bypass
A bypass is generally constructed around a city for the purpose
of removing through traffic from a local street. The bypass
example below was recently constructed on a portion of TH 65
around the east side of the city of Cambridge in Isanti County.
The designers needed to know the projected traffic volumes for
the base year, the forecasted 20 year, and forecasted 35 year
cumulative ESALS to construct the bypass properly.
The traffic that currently uses TH 65 is the maximum number
of vehicles that could be assigned to the new bypass. However,
not all traffic is through traffic. The schematic diagram below
shows the general layout for the bypass.
How to determine the percent of through traffic?
In general, the larger the town or city the fewer the number of through trips it will have. Practice has shown that
small towns that have a population less than 5000 will usually have from 70 to 85% through trips. The only
reliable way to determine the through trip percentage is to perform an Origin/Destination (O-D) study.
Origin and destination studies can be accomplished by a license plate matching study, a driver interview, or by
following vehicles to find their destinations. A license plate matching study is performed by recording the license
plates of vehicles entering and leaving the study area and at relevant locations within the study area. In the
example above, license plates should be recorded for both directions of traffic at points A, B, C and D. Ideally, the
study should run from 6 AM – 9 AM, 10 AM – 2 PM and 3 PM – 6PM. Unfortunately, you may not be able to
collect data for that length of time. At minimum, data should be collected during either the AM or PM peak period
and for 2 hours during the off-peak period of 10 AM – 2 PM.
Once the data has been collected, vehicles that travel from points A to C through D or through B within a specified
amount of time, can be assigned to the bypass. Once the percentages of through trips and destinations in town trips
have been calculated they can be applied to the base and design year AADTs projected using least squares
regression analysis.
For the above example, let’s assume that at point A we collected license plate data from 1000 southbound vehicles
and 1000 northbound vehicles in the 10 hours arranged above. Assume that the AADT at this location is 4000. The
data collected yielded the following matches: A-B or B-A = 500, A-C or C-A = 1300, A-D or D-A = 1960. The
next step would be to double all of the point-to-point movements, thus bringing the 2000 counted vehicles up to
the 4000 AADT.
All of the vehicles that travel from points A to C or C to A can be assigned to the entire length of the bypass.
Vehicles that travel through points A-B or B-A can be assigned to the A to B portion of the bypass. Similarly,
vehicles traveling from points B-C or C-B can be assigned to the C to B portion of the bypass. Some portion of
the vehicles that pass through points A-D and C-D that turn east at D can be assigned to the appropriate portion of
the bypass if their destinations were near the bypass. Also, vehicles that appeared at A or C and passed through D
but not C or A may be assigned to portions of the bypass depending on the destinations, the access and the
decrease in trip time caused by using the faster bypass.
The only other vehicles that should be considered for assignment to the bypass are the additional trips that will be
generated by new construction of businesses and residential developments that are located near the bypass after it
is built. To answer these questions, the forecaster has to get information from the city regarding land development
plans. The additional vehicle trips generated from new development can be calculated using the Institution of
Transportation Engineers’ (ITE) manual on Trip Generation. The ITE manual is organized by development type of
the average number of trips generated by square footage, the number of residential houses, or the number of
employees at new businesses.

New Alignment
The second type of forecast where the road does not currently exist is a new alignment. When forecasting future
traffic and loadings for a new alignment the forecaster must know if the in place alignment will remain or if it will
be closed. The other issue to consider is whether or not the access points remain the same. If the access points
change vehicles must be reassigned to the appropriate road segments. If the current alignment is going to be
closed, all traffic that is currently using the route can be reassigned to the new alignment. The forecaster should
produce this type of forecast in the same manner as any other major construction project. If the old alignment is
going to remain open to traffic, an Origin/Destination (O-D) study is necessary and the forecasting method for a
bypass should be used.

New Route
The last type of new road construction is a new route with no existing route serving the same trip purpose. In this
case, all of the traffic must be assigned by using trip generation information from the Institution of Transportation
Engineers’ (ITE) manual. The volume and heavy commercial vehicle types, using the appropriate defaults, plus the
addition of trucks based on the proposed developments are used to forecast.
TRAFFIC TERMINOLOGY AND DEFINITIONS
Annual Average Daily Traffic (AADT) – the estimate of daily traffic on a road segment represented by the total
traffic on a segment that occurs in a one year period divided by 365.
Average Daily Traffic (ADT) – a 24-hour traffic volume that should be stated with a time period. (Ex: MADT –
monthly average daily traffic, or ADT for 6/21/2011-6/23/2011)
Average Summer Weekday Traffic (ASWDT) – the average Monday through Friday traffic volume on a road
segment from June through August.
Vehicle Classification – the classification of traffic by vehicle types. (Ex: cars, trucks, single unit trucks, semis with
single or twin trailers, etc.)
Vehicle Type Breakdown – a specific vehicle with the following differences; motorcycles, cars, pickups, 2 axle
single units, 3 or more axle single units, 3 axle semis, 4 axle semis, 5 or more axle semis, buses, trucks with
trailers, and twin trailer semis.
Heavy commercial vehicle – all vehicles with at least two axles and six tires.
Heavy Commercial Annual Average Daily Traffic (HCAADT) – The estimate of daily heavy commercial traffic on
a road segment represented by the total heavy commercial traffic on a segment that occurs in a one year period
divided by 365.
Equivalent Single Axle Load (ESAL) factor – a numeric factor that represents the average effect of each vehicle
type on the pavement based on the equivalent load concept. The concept relates the effect that the axles have on
pavement performance compared to the effect of a single 18,000 pound axle.
Average Daily Load (ADL) – the estimate of a daily load on a roadway segment calculated from the daily total
vehicle type multiplied by their appropriate ESAL factors.
Axle Load – the total load transmitted by all wheels in a single, tandem, or tridem axle configuration extending
across the full width of the vehicle.
Maximum Loaded Vehicle – a heavy commercial vehicle that is usually loaded to the legal gross weight limit. (Ex:
tank truck, dump truck, grain truck, and stake loaded truck)
Annual Design Lane ESAL – the estimate of the total ESAL in the design lane of a roadway segment for a period
of one year.

Design Hour Volume (DHV) – the traffic for a selected hour of the day - usually the 30th highest hour of the year
for Greater Minnesota and the peak hour for the Metro Area.
Design Lane Factor (DLF) – the factor to estimate traffic volume and truck components on the heaviest traveled
lanes.
Directional Distribution (DD) – the split of traffic by direction for a selected period of time, usually the design
hour. (Ex: 50/50, where north or east direction is the first number and south or west is the second number)
Tube Counters – The portable devices used to count axles and vehicle class based on their axle spacing.
Automatic Traffic Recorders (ATR) – Devices with loops in the pavement that continuously collect traffic volume
and sometimes vehicle classification and/or speed data.
Weigh in Motion (WIM) – a permanent device that continually collects and stores volume, axle spacing, length,
speed, vehicle type, and weight data.
APPENDIX

1980-2010 Seasonal Adjustment Factors

The following tables show the historical 24 hour seasonal adjustment factors for MnDOT’s eight vehicle type
categories in urban and rural areas.

Seasonal adjustment factors were first developed in the 1980’s. The factors were developed averaging the five
weigh in motion (WIM) sites we had at that time. This resulted in adjustment factors for each vehicle type by
month for Monday through Friday counts. In 2007, we revisited the adjustment factors based on 15 continuous
classification counter (ATR) sites. The adjustment factors were updated in 2008, and 2009. In 2010, 7 WIMs and
16 ATR sites were used to update the adjustment factors.

1980’s Seasonal Adjustment Factors

Body Type Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
CARS+PICKUP 1.14 1.06 1.04 0.99 0.94 0.87 0.87 0.83 0.92 0.96 0.99 1.02
2ASU 1.19 1.07 1.06 0.92 0.74 0.72 0.80 0.78 0.65 0.72 0.87 1.00
3+ASU 1.09 1.05 1.29 1.15 0.72 0.60 0.70 0.65 0.61 0.63 0.84 1.06
3A SEMI 1.18 1.13 1.31 0.94 0.66 0.68 0.75 0.73 0.72 0.86 0.93 1.27
4A SEMI 1.04 1.00 1.09 0.94 0.71 0.66 0.71 0.63 0.76 0.75 0.85 1.03
5+A SEMI 1.00 0.94 0.94 0.87 0.75 0.69 0.80 0.69 0.70 0.74 0.78 0.91
TT/BUS 1.19 1.07 1.06 0.92 0.74 0.72 0.80 0.78 0.65 0.72 0.87 1.00
TWINS 1.00 0.94 0.94 0.87 0.75 0.69 0.80 0.69 0.70 0.74 0.78 0.91

2007 24 Hour Seasonal Adjustment Factors for Urban Areas

Body Type Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
CARS+PICKUP 1.10 1.04 1.02 0.98 0.98 0.95 0.90 0.89 0.85 0.98 1.05 1.13
2ASU 0.90 0.92 0.88 0.84 0.80 0.91 0.80 0.75 0.67 0.81 0.88 0.95
3+ASU 1.19 1.20 1.15 0.88 0.79 0.84 0.68 0.67 0.58 0.61 0.74 1.00
3A SEMI 1.12 1.10 1.03 0.90 0.84 0.86 0.79 0.67 0.67 0.89 0.83 1.08
4A SEMI 1.12 1.10 1.03 0.90 0.84 0.86 0.79 0.67 0.67 0.89 0.83 1.08
5+A SEMI 0.87 0.88 0.86 0.81 0.79 0.83 0.71 0.71 0.66 0.75 0.90 0.94
TT/BUS 1.41 1.33 1.16 1.03 0.93 0.86 0.77 0.62 0.59 0.78 0.88 1.17
TWINS 0.89 0.85 0.82 0.75 0.78 0.91 0.83 0.72 0.70 0.75 0.89 0.88

2007 24 Hour Seasonal Adjustment Factors for Rural Areas

Body Type Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
CARS+PICKUP 1.31 1.26 1.22 1.13 0.97 0.88 0.81 0.84 0.95 1.03 1.13 1.20
2ASU 1.04 1.08 1.07 0.97 0.88 0.85 0.85 0.83 0.81 0.83 0.93 0.96
3+ASU 1.34 1.44 1.28 0.93 0.81 0.61 0.71 0.69 0.70 0.70 0.85 1.25
3A SEMI 1.57 1.54 1.49 1.22 0.90 0.82 0.73 0.68 0.74 0.88 1.10 1.27
4A SEMI 1.57 1.54 1.49 1.22 0.90 0.82 0.73 0.68 0.74 0.88 1.10 1.27
5+A SEMI 0.98 0.90 0.86 0.82 0.78 0.72 0.77 0.75 0.76 0.74 0.88 0.93
TT/BUS 2.05 2.06 1.55 1.11 0.87 0.74 0.71 0.67 0.70 0.79 1.01 1.58
TWINS 1.42 0.95 0.94 0.94 0.86 0.87 0.83 0.66 0.69 0.61 0.76 0.89
 2008 24 Hour Seasonal Adjustment Factors for Urban Areas

Body Type Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
CARS+PICKUP 1.13 1.07 1.07 1.02 0.95 1.00 0.91 0.88 0.95 0.94 0.98 1.06
2ASU 0.99 0.88 0.93 0.91 0.80 0.85 0.81 0.80 0.78 0.78 0.81 0.94
3+ASU 1.14 1.05 1.14 0.98 0.72 0.70 0.64 0.69 0.64 0.66 0.78 1.14
3A SEMI 1.29 1.11 1.21 1.04 0.78 0.80 0.71 0.65 0.75 0.79 0.99 1.45
4A SEMI 1.29 1.11 1.21 1.04 0.78 0.80 0.71 0.65 0.75 0.79 0.99 1.45
5+A SEMI 0.93 1.00 0.93 0.90 0.74 0.77 0.69 0.75 0.71 0.75 0.81 1.02
TT/BUS 1.26 0.99 0.97 0.97 0.72 0.73 0.68 0.72 0.72 0.75 0.98 1.56
TWINS 0.86 0.86 0.86 0.86 0.78 0.81 0.77 0.77 0.77 0.75 0.80 0.96

2008 24 Hour Seasonal Adjustment Factors for Rural Areas

Body Type Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
CARS+PICKUP 1.18 1.13 1.15 1.19 0.95 0.92 0.85 0.85 0.94 0.97 1.06 1.18
2ASU 0.90 0.89 0.92 0.91 0.72 0.83 0.77 0.82 0.89 0.94 0.92 1.02
3+ASU 1.19 1.20 1.06 1.12 0.81 0.70 0.81 0.74 0.63 0.60 0.73 1.03
3A SEMI 1.05 1.08 1.16 0.97 0.71 0.79 0.69 0.90 1.04 1.26 1.58 1.77
4A SEMI 1.05 1.08 1.16 0.97 0.71 0.79 0.69 0.90 1.04 1.26 1.58 1.77
5+A SEMI 0.85 0.84 0.84 0.86 0.74 0.80 0.85 0.76 0.70 0.76 0.80 0.91
TT/BUS 1.50 1.40 1.39 1.05 0.64 0.67 0.66 0.67 0.72 0.82 1.13 1.83
TWINS 0.86 0.97 0.94 0.80 0.68 0.73 0.74 0.79 0.70 0.93 0.79 0.96

2009 24 Hour Seasonal Adjustment Factors for Urban Areas

Body Type Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
CARS+PICKUP 1.10 1.10 1.08 0.97 0.92 0.90 0.88 0.86 0.97 0.95 0.96 1.09
2ASU 1.03 0.96 0.97 0.84 0.78 0.79 0.79 0.76 0.84 0.76 0.81 0.87
3+ASU 1.08 1.22 1.16 0.89 0.69 0.64 0.64 0.60 0.64 0.69 0.79 0.99
3A SEMI 1.47 1.27 1.31 0.96 0.83 0.80 0.76 0.70 0.70 0.76 0.80 1.12
4A SEMI 1.47 1.27 1.31 0.96 0.83 0.80 0.76 0.70 0.70 0.76 0.80 1.12
5+A SEMI 0.99 0.98 0.95 0.82 0.72 0.67 0.66 0.65 0.74 0.75 0.83 1.00
TT/BUS 1.25 1.26 1.17 0.89 0.74 0.68 0.65 0.62 0.66 0.74 0.89 1.33
TWINS 1.04 1.03 1.05 0.82 0.76 0.77 0.69 0.67 0.74 0.86 0.88 0.99

2009 24 Hour Seasonal Adjustment Factors for Rural Areas

Body Type Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
CARS+PICKUP 1.19 1.18 1.16 1.01 0.87 0.87 0.80 0.85 0.88 0.93 0.98 1.22
2ASU 1.18 1.11 1.03 0.94 0.83 0.85 0.82 0.82 0.90 0.89 1.01 1.05
3+ASU 1.36 1.30 1.17 1.03 0.75 0.74 0.76 0.69 0.62 0.68 0.86 1.03
3A SEMI 1.42 1.42 1.37 1.19 0.73 0.71 0.70 0.76 0.78 0.98 1.12 1.36
4A SEMI 1.42 1.42 1.37 1.19 0.73 0.71 0.70 0.76 0.78 0.98 1.12 1.36
5+A SEMI 0.84 0.81 0.89 0.85 0.84 0.83 0.77 0.83 0.70 0.77 0.79 0.89
TT/BUS 1.86 1.70 1.44 1.05 0.67 0.76 0.61 0.76 0.79 0.95 1.11 1.57
TWINS 1.12 0.93 1.06 0.91 0.83 0.72 0.64 0.79 0.74 0.86 0.85 0.93
 2010 24 Hour Seasonal Adjustment Factors for Urban Areas
Body Type Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
CARS+PICKUP 1.11 1.07 1.05 0.99 0.95 0.95 0.90 0.87 0.92 0.95 1.00 1.09
2ASU 0.97 0.92 0.92 0.87 0.79 0.85 0.80 0.77 0.77 0.78 0.83 0.92
3+ASU 1.14 1.16 1.15 0.92 0.73 0.73 0.65 0.65 0.62 0.65 0.77 1.04
3A SEMI 1.29 1.16 1.18 0.97 0.82 0.82 0.75 0.67 0.70 0.81 0.87 1.22
4A SEMI 1.29 1.16 1.18 0.97 0.82 0.82 0.75 0.67 0.70 0.81 0.87 1.22
5+A SEMI 0.93 0.95 0.92 0.84 0.75 0.76 0.69 0.70 0.70 0.75 0.85 0.98
TT/BUS 1.31 1.19 1.10 0.96 0.80 0.76 0.70 0.66 0.66 0.76 0.92 1.35
TWINS 0.93 0.91 0.91 0.81 0.77 0.83 0.76 0.72 0.73 0.79 0.86 0.95

2010 24 Hour Seasonal Adjustment Factors for Rural Areas

Body Type Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
CARS+PICKUP 1.23 1.19 1.18 1.11 0.93 0.89 0.82 0.84 0.92 0.98 1.05 1.20
2ASU 1.04 1.03 1.01 0.94 0.81 0.84 0.81 0.83 0.87 0.88 0.96 1.01
3+ASU 1.30 1.31 1.17 1.03 0.79 0.68 0.76 0.71 0.65 0.66 0.82 1.10
3A SEMI 1.35 1.35 1.34 1.13 0.78 0.77 0.71 0.78 0.86 1.04 1.27 1.47
4A SEMI 1.35 1.35 1.34 1.13 0.78 0.77 0.71 0.78 0.86 1.04 1.27 1.47
5+A SEMI 0.89 0.85 0.86 0.84 0.79 0.78 0.80 0.78 0.72 0.75 0.82 0.91
TT/BUS 1.80 1.72 1.46 1.07 0.73 0.72 0.66 0.70 0.74 0.85 1.08 1.66
TWINS 1.13 0.95 0.98 0.88 0.79 0.77 0.74 0.75 0.71 0.80 0.80 0.93

Rural and Urban defaults by AADT Range

The defaults used in the MnESAL were developed primarily for use in the Seven County Metropolitan Area. The
chart below show the default percentages by AADT range. These percentages should only be used in special
projects off of the truck highway system.
Double Tube Data
Below is an example of double tube count data. Tube counts are taken for 48 hours each direction. The counts are
collected hourly. The first page shows the vehicles traveling east (not shown) and the second page shows the
vehicles traveling west. The 13 vehicle class breakdown is listed on the top of the table. Note that some counts
have bus and heavy truck with trail separated.

At the bottom of the second page, is the average daily (24 hour) vehicle type breakdown. Notice that the 13 vehicle
classes are joined into the 8 classes used for forecasting.
Breakdown of the 8 Vehicle Types for Forecasting
Type 1: Passenger Vehicles (motorcycles, pickups, and cars) – 2 axle 4 tire single unit vehicle pulling recreational
or other trailers.
Type 2: Two Axle Single Unit Trucks – 2 axle 6 tire trucks. This includes all vehicles on a single frame, having 2
axles and dual rear wheels.
Type 3: Three Plus Axle Single Unit Trucks – 3 or more axle single unit trucks. This includes all vehicles on a
single frame having 3 or 4+ axles.
Type 4: Three Axle Semis – 3 axles consisting of two units, one of which is the tractor and the other is a trailer.
Type 5: Four Axle Semis – 4 axles consisting of two units, one of which is the tractor and the other is a trailer
Type 6: Five Plus Axle Semis – 5 or more axles consisting of two units, one of which is a tractor and the other is a
trailer.
Type 7: Heavy Truck with Trailer / Bus – A heavy truck with trailer can have 3 or more axles.
Type 8: Twins Semis – 5 or more axles with two separate trailers.

Example of Heavy 5+ Axle Semi Types

Traffic Counting Schedule
A given County will have both the Truck Highways and Local System Roads counted in the designated “cycle”.
This same County will have only its Truck Highways counted in the “off-cycle.” For an example, Aitkin is in cycle
3. Therefore, in 2016 both Truck Highways and Local System were counted. Then in 2018, only the Truck
Highways in Aitkin are counted.
Comparing Interstates and Non-Interstates Hourly Factor Distribution by Rural and Urban
The following two charts show the percent of passenger vehicles, single unit trucks, and combo trucks by hour on
interstates and non-interstates (US and MN Trunk Highways) in rural and urban areas. On average, rural areas have
a lower AADT, which usually produces a higher percent of trucks. There is a greater number of passenger vehicles
than trucks on interstates in urban areas.

Interstate Hourly Factor Distribution Comparison

0.100
0.090
0.080
0.070
0.060
0.050
0.040
0.030
0.020
0.010
0.000
12:00:00 AM
1:00:00 AM
2:00:00 AM
3:00:00 AM
4:00:00 AM
5:00:00 AM
6:00:00 AM
7:00:00 AM
8:00:00 AM
9:00:00 AM
10:00:00 AM
11:00:00 AM
12:00:00 PM
1:00:00 PM
2:00:00 PM
3:00:00 PM
4:00:00 PM
5:00:00 PM
6:00:00 PM
7:00:00 PM
8:00:00 PM
9:00:00 PM
10:00:00 PM
11:00:00 PM
Rural Urban
Passenger SU COMBO Passenger SU COMBO

However, the percent of passenger vehicles, single unit trucks, and combo trucks are very similar in both rural and
urban areas on non-interstates.

Non-Interstate Hourly Factor Distribution Comparison

0.100
0.090
0.080
0.070
0.060
0.050
0.040
0.030
0.020
0.010
0.000
12:00:00 AM
1:00:00 AM
2:00:00 AM
3:00:00 AM
4:00:00 AM
5:00:00 AM
6:00:00 AM
7:00:00 AM
8:00:00 AM
9:00:00 AM
10:00:00 AM
11:00:00 AM
12:00:00 PM
1:00:00 PM
2:00:00 PM
3:00:00 PM
4:00:00 PM
5:00:00 PM
6:00:00 PM
7:00:00 PM
8:00:00 PM
9:00:00 PM
10:00:00 PM
11:00:00 PM

Rural Urban
Passenger SU COMBO Passenger SU COMBO

Contacts Regarding this Manual

If you have any questions or comments about this Traffic Forecasting Manual, please contact:
Elizabeth Keene, Elizabeth.Keene@state.mn.us
John Hackett, John.Hackett@state.mn.us
Gene Hicks, Gene.Hicks@state.mn.us