Summary Report
Arizona Department of Transportation
Travel Modeling Peer Review
(ADOT)
Phoenix, Arizona
November 18, 2011
ADOT Peer Review Panel Report
ii
ADOT Peer Review Panel Report
i
Table of Contents
1. Introduction ....................................................................................................................... 1
1.1 Disclaimer .................................................................................................................... 1
1.2 Acknowledgements ...................................................................................................... 1
1.3 Report Purpose ............................................................................................................ 1
1.4 Report Organization ..................................................................................................... 1
2. ADOT Overview ................................................................................................................. 3
2.1 Regional Characteristics .............................................................................................. 3
2.2 Agency Responsibilities ............................................................................................... 4
2.3 Agency’s Goals for Peer Review .................................................................................. 5
3. Development of the Arizona Travel Demand Model (AZTDM) ........................................ 6
3.1 History of Travel Modeling at ADOT ............................................................................. 6
3.2 AZTDM Version 1 (AZTDM1) ....................................................................................... 6
3.3 Current Model (AZTDM2)............................................................................................. 6
3.4 ADOT Model Improvement Plan (AZTDM3 and AZTDM4) ........................................... 7
4. Topics of Interest to ADOT ............................................................................................... 8
4.1 Local Transit Network Abstraction in Mode Choice Model ............................................ 8
4.2 Data Needs: Statewide Cordon Count Data and Rural Household Travel Survey ........ 9
4.3 Commodity-based Freight Model ................................................................................. 9
4.4 Hybrid Statewide-Local Model Application ..................................................................10
4.5 Incorporating Advanced Modeling Techniques ............................................................10
5. Panel Discussion and Recommendations .....................................................................11
5.1 Local Transit Network Abstraction in Mode Choice Model ...........................................11
5.2 Data Needs: Statewide Cordon Count Data and Rural Household Travel Survey .......11
5.3 Commodity-based Freight Model ................................................................................12
5.4 Hybrid Statewide-Local Model Application ..................................................................13
5.5 Incorporating Advanced Modeling Techniques ............................................................13
5.6 Discussion of Other Modeling Topics ..........................................................................14
Appendix A: List of Peer Review Panel Participants ............................................................16
Appendix B: Peer Review Panel Meeting Agenda ................................................................17
Appendix C: Peer Review Panel Biographies .......................................................................18
Appendix D: Overview of AZTDM2 ........................................................................................20
Model Components ...............................................................................................................20
Model Validation ....................................................................................................................23
Data Source Summary ..........................................................................................................26
Section 1. Introduction ADOT Peer Review Panel Report
1
1. Introduction
1.1 Disclaimer
The views expressed in this document do not represent the opinions of FHWA and do not
constitute an endorsement, recommendation or specification by FHWA. The document is based
solely on the discussions that took place during the peer review sessions and supporting
technical documentation provided by the Arizona Department of Transportation (ADOT).
1.2 Acknowledgements
The FHWA wishes to acknowledge and thank the peer review panel members for volunteering
their time to participate in the peer review of the Arizona Statewide Travel Demand Model
(AZTDM) and for sharing their valuable experience.
The Peer Review Panel Members were:
• Chad Baker, Chief of Statewide Modeling, California Department of Transportation
• Jim Benson, Senior Research Engineer, Texas Transportation Institute
• Fred Ducca, Director of Transportation Policy Research Group, University of Maryland
• Karen Faussett, Statewide Model Specialist, Michigan Department of Transportation
• Greg Giaimo, Manager of Travel Demand Modeling, Ohio Department of Transportation
Brief biographies for each of the peer review panel members are presented in Appendix C.
1.3 Report Purpose
This report summarizes the results of a peer review of the AZTDM. The peer review was
supported by the Travel Model Improvement Program (TMIP), which is sponsored by FHWA.
The peer review of a travel model can serve multiple purposes, including identification of model
deficiencies, recommendations for model enhancements, and guidance on model applications.
Given the increasing complexities of travel demand forecasting practice and the growing
demands by decision-makers for information about policy alternatives, it is essential that travel
forecasting practitioners have the opportunity to share experiences and insights. The TMIP-supported
peer review provides a forum for this knowledge exchange.
1.4 Report Organization
This report is organized into the following sections:
• Overview of the AZTDM modeled region and ADOT’s roles and responsibilities for travel
demand forecasting – this section gives an introduction to the demographics, land use
and transportation characteristics of the region, ADOT’s planning responsibilities, and
their goals for the peer review.
• Overview of modeling at ADOT– this section provides a brief historical context of travel
modeling at ADOT, including past and current model versions and ADOT’s current
model improvement program.
• Discussion of the AZTDM – this section provides a summary of the topics posed by
ADOT during the peer review for which ADOT sought specific insight and guidance from
the peer review panel.
Section 1. Introduction ADOT Peer Review Panel Report
2
• Peer review panel response – this section provides the peer review panel’s comments
and recommendations to ADOT.
In addition, the report includes four appendices:
• Appendix A – list of peer review participants
• Appendix B – peer review meeting agenda
• Appendix C – biographies for each of the peer review panel members
• Appendix D – summary of the current AZTDM
Section 2. ADOT Overview ADOT Peer Review Panel Report
3
2. ADOT Overview
2.1 Regional Characteristics
This section gives a brief description of the key characteristics of the AZTDM model space
provided by ADOT for this peer review.
Socioeconomics
Socioeconomic growth within the state of Arizona is the primary driver of travel demand. The
population in Arizona is expected to nearly double in the next 40 years, from just over 6 million
in 2010 to over 12 million in 2050. The future population follows the historical trend where each
decade since 1970 has seen substantial growth.
Growth has been due primarily to natural birth and to immigration. Factors such as climate,
geographic location and a strong job market have also fostered the growth. The climate factor
has also attracted a significant seasonal senior population. This “snowbird” population travels to
Arizona during the winter months then leaves in the spring. Despite the perception of a large
senior population, Arizona has a young population with an average age below the national
average.
Most of the state’s population resides in the urban areas, a trend which is expected to continue
in the future. Water rights have been secured to support the forecasted growth in the urban
areas (rural areas have limited water rights to support growth). With growth occurring in the
urbanized areas, it is expected that the metro areas will link up creating a “megapolitan” area
containing approximately 85% of the state’s population. Much of the transportation infrastructure
for this megapolitan area has yet to be built.
0
2,000,000
4,000,000
6,000,000
8,000,000
10,000,000
12,000,000
14,000,000
Population
U.S.Census Count
2006 AZ Commerce Projection
Source: ADOT Peer Review Presentation
Section 2. ADOT Overview
Transportation Infrastructure
Arizona hosts five key interstate corridors
for intrastate and interstate travel.
40 connects California and New Mexico through t
passes through Flagstaff. I-8 and I
California to New Mexico through Yuma, Phoenix and Tucson. I
north-south corridors in Arizona. I
Tucson. I-19 completes the final north
the I-10/I-17 corridor through Phoenix and Tucson is considered one of the most important
portions of the interstate system in Arizona having and expecting to have the
the state.
Transportation corridors in the northern part of the state are limited by geographic features,
such as the Grand Canyon, national and state parks, and
2.2 Agency Responsibilities
ADOT manages the modeling program for the statewide model.
have a role in the following transportation planning studies and pro
• Statewide Long Range Transportation Plan (LRTP)
• Support to MPOs & COGs including interregional trips
• Corridor and sub-area analyses
• Air quality & emissions analyses
o CO: Phoenix & Tucson
o 8-Hour Ozone: Phoenix
ADOT Peer Review Panel Report
which serve as the backbone transportation system
I-40, I-8 and I-10 make up the primary east-connects
the north-central portion of the state and
I-10 pass through the southern part of the state connecting
I-17 and I-19 form the primary
na. I-17 begins at I-40 in Flagstaff passing through Phoenix and
north-south leg connecting Tucson with Mexico. The stretch of
ns highest
tribal lands.
The AZTDM is expected to
projects:
for nonattainment and maintenance areas
4
-west corridors. I-central
volumes in
Section 2. ADOT Overview ADOT Peer Review Panel Report
5
o PM10: 10 areas, 1 proposed
o PM2.5: Pinal County
o SO2: 6 areas
• Freight and goods movement studies
• Toll and HOV studies
• Public-private partnership projects
• Facility design and operations support
• I-10 Phoenix to California border multimodal corridor profile study
• Support Arizona state rail plan
o High speed rail to California and to Las Vegas
o Intercity Rail from northern Arizona to Mexico
o Commuter rail between Phoenix and Tucson
2.3 Agency’s Goals for Peer Review
ADOT’s overall goal and motivation for seeking a TMIP peer review is to have the peer review
panel members assist ADOT staff in identifying the best practices in statewide travel modeling
to enhance the methods employed in the AZTDM and to improve its utility for planning analyses
at state, regional, and municipal levels. To that end, the peer reviewers spent a day responding
to specific questions from ADOT and its planning partners.
ADOT would like the TMIP peer review to particularly focus on the transition from a 3-step,
highway-oriented travel demand model to a 4-step travel demand model that includes a mode
choice component. Additionally, guidance was sought on supporting data collection activities
and on methodologies for truck and freight modeling. ADOT prepared a list of specific topics for
which they sought the panel’s comments and recommendations. The list of topics is presented
in section 4 and of this report. The panel’s response on these topics is presented in section 5.
ADOT, along with its partner agencies, will critically assess the feedback from the peers when
prioritizing its model development plan. While the advice of the peers is invaluable, there are
many factors to work through when considering a model improvement strategy, and therefore
the recommendations of the peers should be regarded as recommendations for ADOT and its
partners.
Section 3. Development of the AZTDM ADOT Peer Review Panel Report
6
3. Development of the Arizona Travel Demand Model
(AZTDM)
3.1 History of Travel Modeling at ADOT
ADOT has a long history of travel modeling in the Arizona. In 1985 ADOT developed the travel
demand models for Maricopa Association of Governments (MAG) and Pima Association of
Governments (PAG) MPO’s. Responsibility for these models was transferred to the MPO’s in
1991. More recently, with the development of the 1st generation statewide model ADOT has
once again jumped into the model development world. In 2008, ADOT along with MAG and
PAG formed a model advisory committee to foster coordination and development across travel
models and across jurisdictions.
3.2 AZTDM Version 1 (AZTDM1)
The first generation Arizona Statewide Travel Demand Model (AZTDM1) was developed in 2009
as a three-step trip based model. AZTDM1 had a coarse network and zone structure (zone
structure based on Census tracts) and used rates borrowed from Indiana and the Quick
Response Freight Manual (QRFM).
The model provided estimates of general statewide performance of alternative system
improvement strategies. It was used during the visioning activities of the Building a Quality
Arizona Framework Study. Due to the aggregate structure of the first generation model,
AZTDM1 was determined to have limited suitability for both transportation planning and to
answering many of the policy questions anticipated in current statewide transportation system
planning and development activities.
3.3 Current Model (AZTDM2)
ADOT is currently using the second generation of the statewide model, AZTDM2. Development
of AZTDM2 was initiated in March 2010 and completed in May 2011. Development focused on
increasing the input data detail and on implementing improved personal and freight travel
demand model components.
Zonal detail increased approximately six-fold from the first generation model, primarily in the
urban areas where AZTDM2 uses a one‐to‐one correspondence with the zone structure from
the MPO models and in emerging areas outside MPO boundaries. The highway network also
had enhanced detail, including a direct import of the MPO networks in the urban areas.
AZTDM2 included an extended external zone system (and corresponding highway network)
covering North America allowing the model to capture important long distance person and truck
travel as well as the visitor market to Arizona.
The AZTDM2’s personal travel demand model component was calibrated using the 2009
National Household Travel Survey (NHTS) data as the primary source of travel behavior
information. The calibration/validation database consisted of approximately 7,000 household
samples, which includes an additional 4,286 samples purchased by MAG and 2,285 by PAG.
The freight and goods movement component of AZTDM2 was based on available data from
sources such as the FHWA Freight Analysis Framework (FAF3) and the Bureau of
Transportation Statistics (BTS) databases.
Section 3. Development of the AZTDM ADOT Peer Review Panel Report
7
3.4 ADOT Model Improvement Plan (AZTDM3 and AZTDM4)
In July 2010, ADOT initiated the development of the third generation model, AZTDM3. The initial
focus of this work will be on transitioning from a 3-step to a 4-step model. This will involve
incorporating a person-mode choice model component and using an abstraction of local transit
services. Non-local services (i.e., fixed-guideway and other line haul transit services) will still be
explicitly coded. AZTDM3 will be capable of providing estimates of transit use for major system
and service improvements for multimodal planning studies.
ADOT has recently acquired the Global Insight Transearch database which will provide
commodity flow data at the TAZ-level for Arizona. This will enable further refinements to the
existing truck freight modeling components and the potential addition of a rail freight component
to the model. ADOT also plans to conduct in the near future a cordon count and classification
study with a view towards possibly collecting origin-destination information for vehicles entering,
leaving, and passing through Arizona.
Other model improvements ADOT plans to include in AZTDM3 are a stratified trip distribution
model and feedback interactions with other model components (vehicle availability, trip
generation, trip distribution and network assignment).
Beyond the current model development phase, ADOT is planning further refinements to the
statewide model. These include: a population synthesis model, an activity-based model, a
dynamic traffic assignment model, an integrated land use/transportation model and an
economic model. These model improvements are considered to be part of the fourth generation
model, or AZTDM4.
The historical context of ADOT’s statewide travel model and the future development plans are
summarized in the following chart.
AZTDM Development Phasing
Source: ADOT Peer Review Presentation
1st Generation 2nd Generation 3rd Generation 4th Generation
3-Step Model
1,098 Zones
Coarse Network
Imported Trip
Generation Rates
QRFM Truck Trip
Generation
6,090 Zones &
Detailed Network
NHTS-Based Trip
Generation Rates
NHTS-Based Trip
Distribution Model
FAF3-Based Truck
Freight Model
Long-Distance Trip
Model
Improved Highway
Assignment Process
Population Geo-
Synthesis Model
Activity-Based Travel
Demand Model
Dynamic Traffic
Assignment Model
Integrated Land Use-
Transportation Model
Economic Linkage
4-Step Model
Person & Freight
Mode Choice
Commodity Flow
Model (Rail, Air &
Pipeline)
NHTS Greater AZ
Demand Model
Update
Stratified Trip
Distribution Model
Calibrated Volume-
Delay Functions
2009 2010 2012 2013+
Section 4. AZTDM Assessment and Discussion ADOT Peer Review Panel Report
8
4. Topics of Interest to ADOT
During the peer review ADOT staff and a consultant team presented an overview of the current
Arizona statewide model, AZTDM2, and of the development plans and specifications for
AZTDM3. (An overview of AZTDM2 taken from the model documentation provided by ADOT is
found in Appendix D.) While discussion occurred around aspects of both AZTDM2 and
AZTDM3, ADOT requested the panel to provide in this review insight and guidance related to
specific topics of interest for AZTDM3 and AZTDM4 development. These topics helped frame
the panel discussion and the panel made recommendations specific to these items. Specifically,
ADOT wanted the peer panel to comment on:
• Developing a mode choice component that utilizes a simplified, abstract representation
of local transit services but fully accounts for other transit services such as fixed guide-way,
park & ride and bus rapid transit
• Identifying additional data needs for model improvement, including a statewide cordon
count and classification survey and a rural household travel survey to supplement the
urban-oriented 2009 National Household Travel Survey
• Improving the existing truck freight model component through the use of recently
acquired commodity flow data and adding a freight rail component
• Creating a hybrid version of the statewide model that can be focused and applied in
metropolitan and sub-regional areas
• Incorporating advanced modeling techniques at the statewide level such as dynamic
traffic assignment, activity-based, land-use and economic modeling
4.1 Local Transit Network Abstraction in Mode Choice Model
One proposed application for the statewide model is to test interregional transit corridors, such
as might be served by a commuter rail system. These transit corridors are between MPO areas
and not fully represented by the MPO models. The MPO models do represent other transit
modes, such as local bus, express bus and light rail, and which will also be represented in the
statewide model.
At a statewide level, the coding of the various transit components could be a large undertaking.
For example, the combined transit systems in the statewide model contain 214 unique routes
(337 directional routes) in the base year. Coding this many routes, along with their supporting
link structure and park-and-ride access, can be significant, especially when considering future
scenarios.
To simplify the bus network coding, AZTDM3 proposes to employ a method where the local bus
networks are approximated or abstracted to compute in and out of vehicle travel times and
measures of accessibility by bus to access rail and intercity bus services. This method is similar
to the method applied in the California statewide travel model. The abstraction method will be
applied to the local bus mode only. Rail and intercity bus will still be explicitly coded in the transit
network.
Local bus travel times will be based on land use and highway network variables as opposed to a
local transit network. Travel times will include sensitivities to time of day and geographic
accessibility to transit (catchment area) information. The abstraction model uses:
• Transfer areas: the areas within which a person can travel
• Service areas: the areas within which transit service is provided
Section 4. AZTDM Assessment and Discussion ADOT Peer Review Panel Report
9
• Level of Service: a single number representing the quantity of local bus service
• Fare: a composite value, indicating the typical fare paid by a customer
ADOT proposes to code local bus transit networks simultaneously with the local bus abstraction
method in order to validate the abstraction method. The base year local bus network will be
available to run on projects as needed, or the model could use the abstracted local bus network.
The abstraction method of the local bus network will be the primary method used in future long
range planning.
4.2 Data Needs: Statewide Cordon Count Data and Rural Household
Travel Survey
Statewide Cordon Count Data
ADOT anticipates conducting a statewide cordon survey in spring 2012. The cordon survey is
designed to capture the external and through trip movements into and out of Arizona. The
survey includes counts, vehicle classification, trip purpose, trip frequency and the origins and
destinations of trips.
ADOT proposes to do a license plate capture survey followed by a mail-out questionnaire. The
questionnaire would be used to collect the trip origin-destination, trip purpose and the frequency
of the trip. ADOT is also exploring use of other technology, such as bluetooth tracking, for
routing and delay data.
ADOT was interested in the panel’s experience related to conducting cordon surveys, such as
improving response rates, example questionnaires, and working with neighboring states. As of
yet, Arizona has not pushed to do an intercept survey and it was uncertain if intercept surveys
have been allowed. ADOT was also researching the use of different technologies, such as GPS
or cellular.
Rural Household Travel Survey
The AZTDM2’s personal travel demand model was calibrated using the 2009 National
Household Travel Survey (NHTS) data as the primary source of travel behavior information. The
NHTS survey data were primarily focused in the urban areas. Of the 7,157 total household
surveys collected, only 89 were collected outside the MAG/PAG MPO regions.
ADOT would like to conduct a household survey for the rural areas of the state to better
understand rural trip making patterns. The survey would replicate the NHTS as close as
possible. ADOT is considering a sample size of around 1,000 households. ADOT requested the
panel’s reaction to this proposal.
4.3 Commodity-based Freight Model
The current AZTDM2 forecasts short haul and long haul truck volumes based on FHWA’s
Freight Analysis Framework version 3 (FAF3). ADOT would like to use a commodity-based
framework using the Global Insight Transearch database that would allow ADOT to consider
goods movements between different modes, such as truck and heavy rail. The model would be
applied for planning and policy testing along the existing freight infrastructure as well as to test
potential new freight corridors, such as the I-11 CANMEX corridor.
ADOT has purchased the Global Insight Transearch database that has commodity flows in
Arizona at a TAZ level and throughout the country at a more aggregate geographic level. ADOT
plans to compare the truck trips and volumes from the commodity-based freight model against
Section 4. AZTDM Assessment and Discussion ADOT Peer Review Panel Report
10
the trips from the FAF3-based model before deciding on which is the better approach to use and
would like the panel to provide comment on the proposed freight model method.
4.4 Hybrid Statewide-Local Model Application
ADOT would like to create a hybrid version of the statewide model that could be applied to
metro areas or sub-regions of the statewide model. The hybrid model would use a more refined
zone structure, highway network and socioeconomic database than currently exist in the
statewide model. The hybrid model would allow for more easy sub-area extraction from the
statewide model which could be used for more localized or focused planning.
Central Arizona Association of Governments (CAAG) would like to see ADOT use the statewide
model or hybrid statewide model in the development of their long range transportation plan.
Pinal County in the CAAG area is expected to see a four-fold increase in population by 2055
and Pinal County was the only county in Arizona that exceeded its growth projection in the 2010
Census. CAAG is looking to ADOT to help model the future growth in the development, which
ADOT is hoping to do in the spring of 2012.
ADOT would like to get from the panel insights on best approaches to sub-area model
extractions and subsequent sub-area model usage.
4.5 Incorporating Advanced Modeling Techniques
ADOT is considering applying several advanced modeling techniques as part of the statewide
model improvement program. These include dynamic traffic assignment, activity-based
modeling, integrated transportation and land-use modeling and economic modeling. ADOT cited
several examples of advanced model research projects through FHWA and Transportation
Research Board (TRB). ADOT is requesting the peer review panel’s guidance on the viability
and best practice of implementing advanced modeling techniques at the statewide level.
Section 5. Peer Review Panel Recommendations ADOT Peer Review Panel Report
11
5. Panel Discussion and Recommendations
The following text summarizes a point-by-point response to the topics of interest posed by
ADOT at the commencement of the peer review. The comments and recommendations are
provided in order of the questions posed by ADOT and the summary of this discussion follows
the panel’s final presentation to ADOT. After the topics of interest portion of this section, a
summary is included containing the comments and recommendations of the peer panel on the
other modeling topics discussed at the review.
5.1 Local Transit Network Abstraction in Mode Choice Model
The panel commented that the use of an abstraction method to estimate local transit in a
statewide model was acceptable practice since the model would be used to test regional transit
demand and not estimating local ridership or local transit route choice. Employing a transit
abstraction method would reduce network coding at a statewide scale. The panel recommended
pursuing applying the local bus abstraction method in the Arizona statewide travel models.
The panel also concurred with the practice of only using similar transit service types in an
abstraction set when doing transit abstraction. Transit services with different characteristics,
such as local bus vs. express bus, should not be combined in the same abstraction. The panel
recommended following a pre-established structure when developing the local transit
abstraction methods.
In applying the abstraction process, the panel suggested the consideration of variables, such as
employment density as a factor for out of vehicle time. For reference, the California statewide
travel model uses employment density as a parameter in the out of vehicle time function as well
as population, HOV3 distance and transit LOS. The panel also commented that there may be a
need for the representation of other services, such as dial-a-ride, which may be part of the local
system.
5.2 Data Needs: Statewide Cordon Count Data and Rural Household
Travel Survey
Statewide Cordon Count Data
Much of the discussion centered on the merits of an intercept cordon survey vs. an approach
that uses license plate capture and a mail in survey. The panel found that using a license plate
survey with a follow up questionnaire did not have high response rates and the method was
typically seen by the public as intrusive resulting in bad publicity. Also, the panel raised concern
that in a license plate survey semi trucks with trailers would have the license plate obscured.
This could prevent a mail in survey to be sent to the right address if trucks were to be included
in the response survey.
The panel had better experiences using an intercept survey to collect cordon data. Michigan
DOT notifies the public safety department to make them aware that the DOT is performing an
intercept survey but does not ask to have police present while performing the survey. This is
done to reinforce the idea that participation in the survey is voluntary. It was believed that
having a police presence would cause drivers to think the study was mandatory. Ohio DOT also
works with the public safety department in performing an intercept survey. The panel also
commented that an effectively structured survey can minimize respondent burden. For instance,
Ohio DOT has been able to survey respondents in under a minute, on average. The panel also
shared advice on administering paper-based vs. electronic survey collection methods indicating
Section 5. Peer Review Panel Recommendations ADOT Peer Review Panel Report
12
that the paper-based works just fine and may be preferred. The panel also suggested that
intercept surveys can more easily be obtained at international border crossings.
The panel recommended that if ADOT is allowed to stop vehicles then they do so. For low
volume roadways, ADOT could stop traffic in the lane. For interstate or higher volume facilities,
ADOT may want to consider only stopping a sample at a designated area such as a rest stop. If
ADOT is not allowed to stop vehicles, then the panel recommended conducting a license plate
survey. However, when conducting either an intercept or a license plate survey, the panel
strongly recommended that ADOT not conduct a mail-in follow-up survey due to the panel’s
previous experience resulting in inconsistent data and bad public relations. The panel also
recommended ADOT review potential new technologies, such as cell phone or bluetooth, as
these may provide an alternate method to collect key data if vehicles cannot be stopped.
The panel also suggested that the timing of when a cordon survey is administered will be
important to minimize seasonal bias, as the model represents an average weekday condition.
The panel also suggested that combining various data collection methods could correct for this
and other biases and validate average trip lengths as necessary.
Rural Household Travel Survey
The panel concurred that there was a need to obtain better household data in the rural areas of
the state as well as better data for long distance trips. The panel recommended that ADOT
collect this data but acknowledged that it would most likely not be available for the current
model development deadline of March.
The panel also recommended stratifying the sampling plan by geography, such as by county, as
well as by hard to reach groups, such as minorities or long distance trips. The panel suggested
that ADOT could conduct a preliminary sample design study as a low cost way of getting a
sense of the number of samples needed.
The panel also recommended ADOT look for opportunities to partner with local MPO’s to share
in their data collection efforts. Partnering with the MPO’s would provide for more efficient data
collection and greater consistency between data sources.
5.3 Commodity-based Freight Model
The panel commented that commodity-based mode choice modeling for freight can be difficult.
Typically it is driven by a need, such as for distribution through major rail yards or for looking at
economic viability of different modes. The panel recommended that ADOT begin by defining the
questions they would like to answer with a freight model, such as:
• Is the freight question just about how trucks affect highways?
• Does ADOT need to understand freight movements, such as for a potential rail mode
option?
• How sensitive to different policies does the model need to be?
The panel recommended scaling the complexity of the truck mode choice model to meet the
need based on the questions being asked of the model. For instance, would the mode choice
model be built to simply answer questions about truck volumes on highway or is the need to
answer economic questions? If the need is to simply answer questions about trucks on the
highway system, the panel suggested ADOT may want to consider implementing simpler mode
choice freight model, such as a rule-based mode choice freight model, or a simplified network
with GIS tagged rail/non-rail access links. Economic answers could require a more complex
Section 5. Peer Review Panel Recommendations ADOT Peer Review Panel Report
13
solution. The key is to understand the type of questions that need to be answered by the truck
model.
The panel also commented that ADOT should be able to take advantage of the Transearch
commodity database purchased regardless of the complexities chosen for the development of
the freight mode choice model. The panel also cautioned that in the past there has been an
issue with the TAZ level disaggregation of the Transearch data. The panel acknowledged that
the issue may have been corrected in more recent releases of the data but recommended a
check of the data to ensure usability at that scale.
5.4 Hybrid Statewide-Local Model Application
The panel thought building a hybrid statewide-local model was a good idea and strongly
recommended that ADOT pursue this development. Most of the panel members have similar
functionality in the statewide models they use or maintain. The panel concurred with ADOT’s
recommended approach of maintaining data at a more disaggregate level. The panel also
recommended ADOT look at creating a “window out” tool that could be used to perform the sub-area
extraction from the statewide model.
The panel recommended that ADOT develop sub-area models that could be used for project-level
forecasts. The panel’s experience has shown that it is best to plan ahead with design-level
results in mind as this is often the reason these sub-area models are run. The panel also
suggested considering a combination of a sub-area travel demand model and a micro-simulation
model in the solutions for these areas.
5.5 Incorporating Advanced Modeling Techniques
The panel expressed their accommodations to ADOT for the progress made by ADOT staff in
establishing ADOT’s modeling program and the development made to date on the current
statewide model. The panel encouraged ADOT to continue to build from this good place and
acknowledged that ADOT is definitely within the state of the practice in statewide modeling. The
panel did want to caution against being on the bleeding edge of model development unless
there was a specific need. They recommended that ADOT tie the development of advanced
modeling techniques to specific needs moving forward.
Of the advanced modeling specifically mentioned by ADOT in the peer review, the panel made
the following recommendations:
The panel recommended ADOT consider ties to both state and national economic models when
looking at linkages between the statewide and economic models. Ohio, Maryland, Michigan and
California statewide models have an economic component. The panel commented that ADOT
would need to decide if the economic models tied to the front or back end of the statewide
model and if/how the Transearch commodity flows would be used by the economic models.
The panel commented that true dynamic traffic assignment (DTA) implementation, which is to
drill down to operational level fidelity, is only appropriate for subarea studies and is not
computationally feasible for statewide model application. However, aspects of DTA may be
useful for dealing with long trip lengths spanning model periods. A statewide DTA application
would require development of a simplified approach that extracts the salient portions, such as
time of day. The University of Maryland is experimenting with a low fidelity DTA which does not
have signal controls but would have network performance by time of day. The panel
recommended that ADOT consider why advanced models are needed, and then develop them
according to available resources and ease of application.
Section 5. Peer Review Panel Recommendations ADOT Peer Review Panel Report
14
The panel recommended looking into dynamic traffic assignment (DTA) due to the long
distances in state travel. However, the panel commented that ADOT needed to specify the
functions that would be performed by a dynamic traffic assignment and to be clear on the
functional specifications. The panel also recommended ADOT consider collecting more detailed
highway network data, such as signal locations and timing plans, in anticipation of implementing
a dynamic traffic assignment.
The panel felt they needed more information in order to answer the activity based modeling
(ABM) question. The panel wanted to better understand the need to move to an ABM platform.
The panel wondered if there was something missing from the current models that a tour model
would address. For instance, was the need to get a better assignment or was the need to better
understand items such as transit, hot lanes or peak spreading. The panel felt these issues
needed to be addressed first. The panel recommended that ADOT consider an open
architecture to implement any ABM platform if ADOT decides to use an ABM. The panel also
commented that an activity based approach would most like also entail an investment in
resources and acceptance of longer runtime until technology caught up.
5.6 Discussion of Other Modeling Topics
Along with the topics of interest presented, ADOT invited the peer panel to comment on the
current model and the proposed model development plans. The comments made by the peer
panel are summarized below by topic.
Markets
The panel commented that non-resident travel did not seem to be fully addressed in the
statewide model. The panel recommended an assessment of the relative importance of
including non-resident, visitor or tourist trips in the model.
Trip Generation
The panel commented that home-based school (HBS) and home-based university (HBU) trip
purposes were unusual for a statewide model, though there are instances where this is the case
such as the California statewide model which has “school” as a trip/tour purpose.
Long Distance Person Travel
It was proposed that the long distance personal travel in AZTDM3 will be based in part on
county-to-county flows and employment (FHWA traveler analysis framework method). The
panel suggested that county to county flows from the latest Census may not be available in time
to meet the AZTDM3 development schedule deadline.
Freight Model
The panel liked that the AZTDM2 borrowed MAG’s short distance freight model and
recommended ADOT use MAG’s freight data to complement the FAF3 data in recalibrating their
freight models. The panel also commented that a rule of thumb threshold for long distance
trucks is about 250 miles.
Time of Day
The AZTDM3 transit model will include peak, off-peak and a separate overnight period when
limited service is provided. The panel suggested ensuring that the model is reconciled between
the highway peak periods, the peak periods when transit operators provide service, and the
peak periods when people actually use the transit system.
Section 5. Peer Review Panel Recommendations ADOT Peer Review Panel Report
15
A decision has not been yet made as whether AZTDM3 will use the midpoint of the travel time
for a trip or a trips-in-motion method for defining the trip’s period (AZTDM2 uses trips in motion).
The panel acknowledged that this is an important issue and commented that using midpoint
may not be as useful given the long duration expected in statewide model trips. The panel
further commented that a trips-in-motion method seems to make sense if dynamic traffic
assignment is being considered. The panel wondered if trips could be parsed so that they
appear in multiple time periods.
The panel also commented on the proposed peak spreading model in AZTDM3. The peak
spreading model is expected to be a multinomial logit model that breaks up the peak periods
into 30 minute intervals. The model would use a variety of household, person and trip variables
that are specific to each period. The panel questioned if local data existed to measure the shift
due to congestion and commented that ADOT may need to look for outside data sources to
support this model. The panel also commented that ADOT consider employing a measure of
congestion, such as congested travel time, as an explanatory variable. There was some
discussion regarding the use of speed versus time as the explanatory variable. Though there
was no consensus reached, the panel did recommend using time as the measure.
Mode Choice Model
AZTDM3 will use mode choice logsums in distribution. There was much discussion on whether
mode choice should come before or after distribution and how that might be implemented. The
question was asked if the mode choice model was applied at the daily level or if it was planned
to split the trip tables into periods before mode choice.
The panel offered several suggestions as to the implementation order of the time of day, mode
choice and distribution models. The panel commented that applying time of day factors before
distribution or mode choice would be needed as skims are performed by period. The panel also
suggested that time of day factoring could be split into two parts, one up front in the model for
micro-level assessments and the second at the back end similar to the adjustments made in
dynamic traffic assignment or activity based models. Alternatively, the panel suggested
beginning the modeling process with preloaded congested networks to reduce the number of
iterations.
The panel was in favor of having mode choice come after distribution; however, acknowledged
that the decision would ultimately depend on what the estimation results say about the chosen
hierarchy. Decisions more sensitive to travel conditions should be later on in lower nests of the
model. Mode is often more sensitive than destination, but not always. Poor estimation results
can indicate an incorrect ordering of model steps. Estimation results may also vary by socio-economic
category.
Socioeconomic Forecasts
The panel commented that the review did not include much discussion of the socioeconomic
forecasts being used by the statewide model. The panel suggested the need to pay attention to
the socioeconomic forecasts to ensure a certain comfort level as it pertained to reasonableness
of the data and the process by which the forecasts were derived.
Source Data
ADOT plans to use the recent release of the American Community Survey (ACS) in AZTDM3
model development. The panel commented that the 3 year data may have missing data due to
sample size suppression and recommended using both the 3 year and 5 year ACS data
sources.
Appendix A. Panel Participants ADOT Peer Review Panel Report
16
Appendix A: List of Peer Review Panel Participants
Peer Review Panel Members:
Chad Baker California DOT
Jim Benson Texas Transportation Institute
Fred Ducca University of Maryland
Karen Faussett Michigan DOT
Greg Giaimo Ohio DOT
Local Agency and Partner Agency Staff:
Floyd Roehrich, Jr. Arizona DOT
Mark Hodges Arizona DOT
Keith Killough Arizona DOT
Deng Bang Lee Arizona DOT
Baloka Belezamo Arizona DOT
Tracy Clark Arizona DOT
Beverly Chenausky Arizona DOT
Georgi Ann Jasenovec FHWA – Arizona Division
Minyan Ruan Pima Association of Governments
Aichong Sun Pima Association of Governments
Consultant Staff:
Rob Bostrom Wilbur Smith Associates
Krishnan Viswanathan Wilbur Smith Associates
Liza Amar Wilbur Smith Associates
Vijay Mahal HDR, Inc.
Michael Gorton HDR, Inc.
Brent Cain HDR, Inc.
Greg Erhardt Parsons Brinckerhoff
Sean Messner URS Corporation
Ruth Gutierrez CivTech
Supporting Staff to Peer Review Panel Members:
Sarah Sun FHWA
Chad Worthen Resource Systems Group, Inc
Appendix B. Meeting Agenda ADOT Peer Review Panel Report
17
Appendix B: Peer Review Panel Meeting Agenda
Peer Review of the ADOT Statewide Travel Demand Model
November 18, 2011
8AM – 5PM
ADOT Board Room
206 South 17th Avenue
Phoenix, AZ 85007
8:00 – 8:30 Meet at ADOT; Continental Breakfast
8:30 – 8:45 Welcome and Introductions
8:45 – 10:00 Arizona Travel Demand Modeling Overview
10:00 – 10:15 Morning Break
10:15 – 12:00 Existing Travel Forecasting Techniques
12:00 – 1:00 Lunch
1:00 – 2:45 Proposed Travel Forecasting Improvements
2:45 – 3:00 Afternoon Break
3:00 – 4:00 Peer Review Panel Internal Discussion
4:00 – 5:00 Preliminary Findings / Recommendations from Panel
Appendix C. Panel Biographies ADOT Peer Review Panel Report
18
Appendix C: Peer Review Panel Biographies
Chad Baker (California Department of Transportation)
Chad Baker has been the Statewide Model Branch Chief for Caltrans since 2009. In this
capacity, he is responsible for all aspects of the model including quality control, operation,
scenario development, post-processing and reporting. In his role as Branch Chief, he provides
technical reviews and reports for various planning efforts such as travel surveys, regional
demand modeling, freight modeling and passenger rail modeling. Prior to his current
engagement, he has worked for the Department performing design, project study, programming
and macro and microsimulation work.
Prior to working for Caltrans, Mr. Baker worked for a private engineering firm doing design,
construction and open channel flow simulation work. Mr. Baker graduated from the University of
California at Davis with both a Bachelors and a Masters degree in Civil Engineering. Mr. Baker
is an active participant with the Transportation Research Board as the Chair for NCFRP Project
38, Improving Freight System Performance in Metropolitan Areas, as well as other panels and is
a member of the technical expert panel for SHRP2 Project C10B.
Jim Benson (Texas Transportation Institute)
Dr. Benson has more than 40 years experience in transportation planning and engineering.
During his 35+ years with TTI, his research has focused in the areas of transportation planning
and travel forecasting. He has served as Principal Investigator or Study Director for numerous
projects in these areas. During the past 10 years, Dr. Benson's research and development
efforts have focused primarily on the provision of technical support and assistance in the area of
travel demand model development, travel demand model applications and travel model software
support. Through his work with the Transportation Planning and Programming Division of the
Texas Department of Transportation (TxDOT), he has been directly or indirectly involved with
the model development efforts for most of the metropolitan areas in Texas. He played a major
role in TxDOT's migration to the TransCAD software platform for travel demand modeling.
Through his work with the Houston-Galveston Area Council (H-GAC), he has provided
management and technical guidance in the development of the travel demand models for the
region for over 25 years.
Dr. Benson has served on various panels and committees including: the Peer Review Panel for
the Development of the Oahu MPO Travel Demand Models and the Texas Statewide Analysis
Model Review Panel.
Fred Ducca (University of Maryland)
Dr. Fred Ducca directs the Transportation Policy Research Group of the National Center for
Smart Growth (NCSG) at the University of Maryland. As director he supervises the development
of the Maryland Statewide Transportation Model (MSTM), a cutting edge tool which analyzes
traffic throughout the state of Maryland. The MSTM closely links with the Baltimore and
Washington MPO models, allowing the MSTM to respond to changes in land use patterns
resulting from activities in individual urban areas. In addition, Dr. Ducca leads the Maryland
Scenarios Project, funded by the Maryland Department of Transportation. This project examines
long range transportation and land use scenarios in the state of Maryland and surrounding
areas. While with the Federal Highway Administration, Dr. Ducca managed the Travel Model
Improvement Program (TMIP). The TMIP focused on improving both the state-of-the-art and
state of the practice in travel forecasting. TMIP activities ranged from the development of
advanced forecasting to integrate activity based forecasts with network simulations, to
Appendix C. Panel Biographies ADOT Peer Review Panel Report
19
improvements to current forecasting methods. TMIP also provided training on travel forecasting,
conferences and seminars on travel modeling issues, and an email list for modelers to provide
technical support to each other.
Dr. Ducca managed the Urban Land Institute’s Suburban Mobility Program, a cooperative effort
between the private sector and the public sector, local governments, to reduce traffic
congestion. The program examined a range of congestion reduction options including allowing
higher density, pedestrian friendly site design, transportation impact fees, changes to parking
policy and the imposition of carpooling requirements. While in graduate school Dr. Ducca
worked on the DRAM and EMPAL population and employment location models. He then
integrated DRAM and EMPAL with traffic analysis procedures to create an integrated package
of land use and transportation models, allowing for analyses of the interactive effects of travel
and urban development.
Karen Faussett (Michigan DOT)
Karen Faussett is the Statewide Model Specialist at the Michigan Department of Transportation
(MDOT). She is responsible for the update and maintenance of the Michigan statewide travel
demand model and leads the statewide model team.
Karen was also project manager for MDOT’s 2004-2005 and 2009 statewide household travel
surveys. Before moving to statewide modeling, Karen spent several years developing small
urban models at MDOT. Prior to MDOT, Karen worked at the Southeast Michigan Council of
Governments (SEMCOG). Karen has a Bachelor of Science in Urban Planning from Michigan
State University and a Master’s Certificate in Project Management from the George Washington
University.
Greg Giaimo (Ohio DOT)
Greg Giaimo graduated from the Ohio State University with BSCE (1989) and MS (1991)
degrees. He has worked for ODOT as a travel modeler for almost two decades and is a
registered professional engineer in Ohio. Besides day to day project and corridor analysis, he is
in charge of new model development, data collection and development of technical methods
related to the planning process. In this roll he develops methods for producing project level
forecasts from models and other inputs and creates those forecasts for complex projects in the
northwest quadrant of the state.
Mr. Giaimo estimates/calibrates new travel demand models or manages consultant contracts to
do so for the statewide model and seventeen Ohio MPO models and has actively guided Ohio’s
adoption of advanced modeling techniques focusing on activity micro-simulation, freight, land
use and integration of traffic operations models. He develops data collection protocols and
implements new technologies for household surveys, intercept surveys and travel time data
collection programs and oversees staff and consultants collecting the data. He has also
developed various other related planning processes including the statewide congestion
management system, bypass project analysis process, transportation review advisory council
scoring factors, planning level Highway Capacity Manual program and toll revenue forecasting
process.
Appendix D. Overview of ADOT ADOT Peer Review Panel Report
20
Appendix D: Overview of AZTDM2
The following text summarizes the current version of the Arizona Statewide Travel Demand
Model (AZTDM2) at the time of the review, along with data sources used in the development of
the model.
In AZTDM2, the travel market is divided by person trips and truck trips. Each is also sub-grouped
by distance. For person travel, 50 miles is the threshold of short trip versus long trip.
Truck travel is sub-grouped based on the judgment if the truck trip crosses FAF3 zone
boundaries.
• Short Distance Person Travel (<=50miles)
• Long Distance Person Travel (>50 miles)
• Short Distance Truck Travel (within FAF3 zone)
• Long Distance Truck Travel (crossing FAF3 boundaries)
Model Components
The AZTDM2 model structure includes separate components for passenger travel and truck
trips as shown in the following flow chart:
Source: ADOT Peer Review Presentation
AZTDM2 has five primary model components as described in the current model documentation:
Appendix D. Overview of ADOT ADOT Peer Review Panel Report
21
• Setup/Trip generation
• Skimming
• Person Travel
• Truck/Long Distance Travel
• Assignment
Setup/Trip Generation
In this stage, trip generation is conducted for short distance person trip only. Truck and long
distance person trips are processed separately in other stages of the model.
Trip generation rates for short distance person trip were generated based on the 2009 National
Household Travel Survey (NHTS). For each county, rates were calculated for five trip purposes:
• Home based work (HBW)
• Home based university (HBU)
• Home based school (HBS)
• Home based other (HBO)
• Non home based (NHB)
Person trip generation rates are stratified by the area type. Area type definitions were calculated
based on an accessibility measure. Area types used by AZTDM2 are:
• Central Business District (CBD)
• Urban
• Suburban
• Rural
• Small Town Central Business District
Skimming
AZTDM2 creates toll/non-toll skims using a generalized cost that is based on travel time, toll
and distance for the following four vehicle classes:
• drive alone
• shared ride 2
• shared ride 3+
• truck
Person Travel
In this stage, AZTDM2 performs trip distribution for short distance person travel using a
destination choice logit model. After distribution, transit trips are factored off by purpose and
area type. A multinomial logit model is then used to predict auto occupancy. Shares were
derived from NHTS and then smoothed to ensure logical relationship among modes.
Appendix D. Overview of ADOT ADOT Peer Review Panel Report
22
Truck & Long Distance Person Travel
In this stage, the model separately processes short & long distance truck travel and long
distance person travel. Short distance truck model is a three-step model without mode choice.
Its trip generation is segmented by twelve land use categories:
• Employer (start and end point of any truck trip)
• Retail
• Construction
• Farming
• Mining
• Households
• Governments
• Warehousing
• Transportation
• Office
• Industrial/Manufacturing
A gravity model is applied to distribute short distance truck trips. Friction factors between zone
pairs are calculated dynamically based on congested travel time.
Long distance person trips are mainly processed by a Java script, which reads and expands the
2002 NHTS long distance data to a state-to-state trip table then disaggregated to TAZ using
household data, employment and a weighting scheme. A 10% sample of ticked air travelers by
BTS was also used. After missing NHTS records are synthesized and the NHTS data are
expanded, trips are disaggregated to the AZTDM zones based on population and employment.
The model also uses state parks as a special attraction.
Long distance truck trips are also processed by a Java program but uses FAF3 data to create
FAF-district to FAF-district commodity flow matrix, which are then disaggregated to TAZ based
on employment. Long distance commodity flows are converted to truck trips using payload
factors for single-unit and multi-unit trucks. An empty truck rate is used to factor the truck trips
for returning empty trucks. Capacity and volume/delay function curve parameters were obtained
from MAG. Passenger car equivalent vales were obtained from the Highway Capacity Manual.
Assignment
Highway assignment in AZTDM2 combines the long and short passenger and truck trip tables
and assigns them onto the network by four time periods:
• AM Peak (6AM - 9 AM)
• Mid Day (9 AM - 3 PM)
• PM Peak (3 AM - 6 PM)
• Night (6 PM - 6 AM)
The model performs a feedback loop from trip generation to assignment. In first feedback loop
iteration, long distance trips (person and truck) are loaded onto network using an all-or-nothing
assignment. Then the short distance persons and trucks are loaded to the network with a user
Appendix D. Overview of ADOT ADOT Peer Review Panel Report
23
equilibrium traffic assignment. Congested travel times are calculated using a BPR-type volume-delay
function. Only the AM and MD travel times are fed back. Convergence is reached when
the percent RMSE for the AM and the MD periods are both less than 1%. On the final model
iteration, the model assigns PM and NT trips to highway network.
Model Validation
Model calibration focused on the state highway system. Traffic counts were used to validate
AZTDM2.
Aggregate volume to count comparisons showed that the R-Square for the total flow was
approximately 0.97, and the percent RMSE of total flow was 30%.
Source: ADOT Peer Review Presentation
Appendix D. Overview of ADOT ADOT Peer Review Panel Report
24
Source: ADOT Peer Review Presentation
Screenline validations were also performed. The percent error of volume on 9 of 10 screenlines
was within 16%. Variances on the one screenline outlier in northeast AZ were associated with
tribal reservations and parks. State line crossing screenlines had the total volume percent error
within15% at each border crossing.
Appendix D. Overview of ADOT ADOT Peer Review Panel Report
25
Source: ADOT Peer Review Presentation
Source: ADOT Peer Review Presentation
Screenline Totals on Links with ATR Counts
Description
SCREE
NLINE
Number
of Counts ATR Model Difference
%
Difference
Maximum
Desirable
Deviation
Within
Target?
I-8 & I-10 West 1 6 35,862 34,189 -1,673 -5% 38% YES
I-40 Mid 2 4 24,728 25,568 840 3% 46% YES
I-40 East 3 4 21,400 23,722 2,322 11% 46% YES
I-10 East 4 3 36,875 24,293 -12,582 -34% 38% YES
MAG-Flagstaff 5 3 42,382 40,791 -1,591 -4% 36% YES
MAG-CAAG 6 6 123,717 107,901 -15,816 -13% 22% YES
CAAG-PAG 7 3 52,233 59,854 7,621 15% 32% YES
I-40 West 8 3 14,986 16,036 1,050 7% 55% YES
Northeast 9 3 8 ,676 14,416 5,740 66% 61% NO
I-10 East--North Split 4 1 4 9 ,354 9 ,569 215 2% 61% YES
Total of Screenlines 3 9 370,213 356,339 -13,874 -4% 17% YES
MAG Cordon MAG 14 209,524 183,067 -26,457 -13% 17% YES
PAG Cordon PAG 10 92,462 97,563 5,101 6% 25% YES
Yuma Cordon YUMA 4 28,711 22,731 -5,980 -21% 43% YES
Flagstaff Cordon FMPO 8 54,766 66,941 12,175 22% 32% YES
Total of Cordons 3 6 385,463 370,302 -15,161 -4% 17% YES
Appendix D. Overview of ADOT ADOT Peer Review Panel Report
26
Data Source Summary
The following are the various sources for model development, calibration and validation used in
the AZTDM2 model (source: ADOT Peer Review Presentation):
• Transportation Analysis Zone & Transportation Network attribute data from MAG, PAG,
FMPO, YMPO, CYMPO
• U.S. Decennial Census & Census Transportation Planning Package
• Quarterly Census of Employment & Wages (QCEW)
• 2009 National Household Travel Survey (NHTS)
o Including Add-Ons purchased by MAG & PAG
• Traffic Counts
o Automated traffic recorders (ATRs)
143 locations, largely inter-city
Break-out by vehicle type
Continuous monitoring, highly reliable
o Department of Public Safety (DPS) counts
35 locations on Phoenix area freeways
Total volumes from speed monitoring system
o ADOT Port-of-Entry (POE) estimates
41 state line crossings
Auto versus truck classifications
o Bureau of Transportation Statistics (BTS) border crossing data
8 border crossings
Auto versus truck classifications
o Highway performance monitoring system (HPMS)
All HPMS links
Used for broad area comparisons, rather than individual link comparison
• FHWA Freight Analysis Framework (FAF3)
• IHS Global Insight Transearch
FHWA-HEP-12-026
NOTICE
This document is disseminated under the sponsorship of the U.S. Department of
Transportation in the interest of information exchange. The United State Government
assumes no liability for its contents or use thereof.
The United States Government does not endorse manufacturers or products. Trade names
appear in the document only because they are essential to the content of the report.
The opinions expressed in this report belong to the authors and do not constitute an
endorsement or recommendation by FHWA.
This report is being distributed through the Travel Model Improvement Program (TMIP).
