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The Travel Model Improvement Program Newsletter

Issue 21, Fall 2004 (PDF format PDF files require the use of a PDF reader. You may download a free copy of Adobe Acrobat Reader to view these files. If you already have the Adobe Acrobat Reader installed on your computer it should automatically open to view the files when you click on the link to the document. )

The Travel Model Improvement Program is sponsored by:
U.S. Department of Transportation
Federal Highway Administration
Federal Transit Administration

Table of Contents
FHWA’s "Model Vision"
Model Citizen
TMA Certification to include Checklist for Travel Forecasting Methods
TMIP Panel Suggests Topics for Peer Exchanges
Hot Topics: Speed Flow Curves
Upcoming Events

FHWA’s "Model Vision"

By Cynthia J. Burbank Associate Administrator for Planning, Environment and Realty, Federal Highway Administration

Does the Federal Highway Administration (FHWA) see a compelling need to advance the state of the art and the state of the practice of Travel Demand Modeling?

The answer is a resounding YES! We need better modeling to support effective transportation decision-making, better transportation investments, better operating decisions, improved air quality analysis, and much more. Improved modeling will help all levels of government meet large transportation challenges with limited budgets.

Modeling plays an important role in emerging priorities such as road pricing, operations, freight, land use-transportation integration, homeland security, safety, and suppressed travel. Modeling can increase the power of scenario planning, visualization, and communication of results to the public and elected officials.

Here’s how modeling can help respond to policy issues:

Pricing — With resources for transportation stretched and congestion on the rise, transportation agencies are looking at innovative funding and management strategies, such as pricing. Models need to predict travel behavior under various pricing options.

Freight — An ongoing focus of the transportation planning process, freight requires good models, sensitive to carrier and shipper decisions.

Land Use-Transportation Integration — There is an increased need for MPOs and DOTs to coordinate transportation and land use planning decision making processes at the system, corridor and project levels.

Homeland Security — MPOs, cities and states must develop homeland security plans based in part on travel models.

Safety — Models can help safety planners analyze system-wide safety impacts in their long-range transportation plans and hone in on the most effective strategies to increase safety.

Suppressed Travel — Perhaps one of the most polarizing issues today, suppressed (or "induced") demand must be reflected in travel models to predict impacts on congestion, air quality, and the environment.

And accurate modeling is needed to increase the power of other planning tools:

Scenario Planning — Travel demand and land use forecasts can help create regional visions of urban growth and form. They can be used to screen alternatives and formulate policy initiatives to achieve the desired vision. However, more work is needed to further develop and apply integrated transportation/land use models. Also, for the purposes of public and decision maker involvement in scenario planning, simplified models may be needed for quicker turnaround of policy impact evaluation.

Visualization and Communication of Results — Planners need better technical tools and techniques to communicate travel data and results to decision makers and the public. Visualization technologies may be one innovative tool, but perhaps more simply, planners should strive to present data and information in a clearer, more thoughtful manner.

Microsimulation — As management and operations initiatives are planned, there is a need to evaluate these strategies along with other types of alternatives. Increasing the sensitivity of models to better show the impacts of operational improvements, and to better estimate emissions, will likely mean more reliance on micro-simulation.

Activity and Tour Based Modeling — The nascent development of these models is a result of recent research into travel demand forecasting procedures and advances in computing technology, which enable more detailed and disaggregate travel demand analysis.

Models also need to be more responsive to non-motorized transportation. Current health concerns, developing pedestrian friendly environments and reducing congestion and pollution through reductions in auto travel all impact policy issues. Data collection methods and models need to be more sensitive to non-motorized alternatives to better estimate the impacts of these facilities on travel behavior and air quality.

To meet the needs for better modeling, FHWA is ramping up our outreach and training to the modeling community, research on models and model quality assurance. We are currently conducting a research needs assessment that aims to bridge the gaps between decision makers, practitioners, and academia.

In light of the myriad issues stated above and unforeseen issues that will arise in the future, FHWA calls on state DOTs (Departments of Transportation) and MPOs (Metropolitan Planning Organizations) to place a higher priority on high quality modeling. We will help transportation agencies build their modeling capacity through the methods above. We will also use the planning certification process to identify opportunities to raise the state of the practice in modeling.

FHWA is funding a National Academies of Science synthesis of the state of current practice in modeling. The synthesis will serve as a baseline for agencies to evaluate their own modeling practice. To further the state of the practice FHWA will collect information on modeling "hot topics" such as pricing, microsimulation, peak spreading and others, and will improve technology transfer to the user community through technical roundtables and a more robust clearinghouse.

Finally, I want to highlight that under our SAFETEA (Safe, Accountable, Flexible and Efficient Transportation Equity Act) proposal, Metropolitan Planning (PL) funds would increase approximately 52% and State planning and research (SPR) funds would increase approximately 37%, with the bulk of the increase in SPR funds dedicated to improved data collection activities. We remain hopeful that congress will enact legislation at these levels, because the increased funding can be used by states and MPOs to improve their modeling and data collection activities and thereby better inform transportation decisions.

Table of Contents

Model Citizen

The Environmental Protection Agency (EPA) on April 15, 2004, designated new ozone non-attainment areas based on the new eight-hour ozone national ambient air quality standard (NAAQS). The nonattainment designations were effective on June 15, 2004. These areas will need to perform transportation conformity determinations one year after the effective date of the nonattainment designations. A vital part of the conformity process is to estimate mobile source emissions. The estimation results will demonstrate if your Long Range Transportation Plan, Transportation Improvement Program and your transportation projects conform to a State Implementation Plan (SIP). What determines the mobile source estimation outcome is your data, the assumptions and methodologies utilized. Thus, it is critical that agencies performing conformity demonstration employ the most current analysis techniques available.

In July 2004, the National Highway Institute (NHI) offered the "Estimating Regional Mobile Source Emissions" course in Knoxville, TN. This course covered the best practice analysis techniques on estimating mobile source emissions. It conveyed a wide range of topics such as:

Some of the issues discussed in this course are especially important to the agencies that are about to do conformity analyses for the first time.

Being active and involved in your SIP process—It is extremely important for conformity determination agencies to take an active role in the SIP development process. The attainment demonstration SIP sets your motor vehicle emissions budget (MVEB), which is the foundation of conformity determination. It is your responsibility to make sure that the latest transportation planning assumptions are used in the mobile source emissions inventories so that you will not end up with an unachievable budget.

Obtaining pre-analysis consensus—The Conformity rule requires that the underlying assumptions and methodologies used in conformity determination be reviewed through interagency consultation. It is in your best interest to review with your partners all assumptions and proposed methodologies and be persistent about having a pre-analysis consensus.

Knowing your data-providing agencies—It is not only important to know which agencies provide what data, but it is also critical to know the right staff person.

Being aware of your data limitations—This is easier said than done, but always insist on getting the documentation with the data and ask lots of questions.

Reconciling your data at the beginning of the analysis process—It is imperative to know the compatibility of the data utilized in your analysis.

All these issues and much more are talked about in the Estimating Regional Mobile Source Emissions course. This is a good complementary course to "Introduction to Transportation/Air Quality Conformity". It is unique because the course comprehensively covers the technical aspect of conformity demonstrations.

At the same time, the course could be further enhanced. For the lesson on TDF, the majority of the time could be spent on identifying the critical issues as far as conformity analyses are concerned and gloss over the TDF structure, since NHI offers "Introduction to Urban Travel Demand Forecasting" course. The same goes for the MOBILE6 section, the course could skim over the model structure and concentrate on pros and cons of using local data, as FHWA already has a course on "MOBILE6 Emission Factor Modeling". Last but not least, the course could employ only one or two case studies in lieu of some of the existing exercises. The case study or studies could serve as the thread that connects together the concepts, issues and analysis techniques discussed in the course.

H. Sarah Sun, Memphis MPO
Sarah Sun is a principal planner for Memphis Metropolitan Planning Organization (Memphis MPO). Memphis MPO serves Shelby County, TN, and portions of Fayette County, TN and DeSoto County, MS. Sun has been responsible for running the Memphis MPO Travel Demand Model since 1993 and performing conformity determination since 1997. Sun served as the project manager for the 1998 Memphis MPO household travel survey, and is the project manager for the development of the new travel demand model, which is to be completed in early 2006. Sun has earned a Master of Arts in Sociology with a Concentration on Population Studies and a Master’s degree in City and Regional Planning with Concentration on Transportation Planning.

Table of Contents

TMA Certification to include Checklist for Travel Forecasting Methods

By Bruce Spear, FHWA

23 CFR 450.334 specifies that the Federal Highway Administration (FHWA) and the Federal Transit Administration (FTA) jointly will review and evaluate the transportation planning process for each Transportation Management Area (TMA) to determine if the process meets federal transportation planning requirements.

Recently, it was determined that including a review of the TMA’s travel forecasting methods would ensure that they adequately support the applications for which they are being used. These applications can vary considerably from one Metropolitan Planning Organization (MPO) to another, depending on such factors as non-attainment status, regional population and economic growth, and the types of strategies/investments being considered in the transportation plan.

To assist both FHWA/FTA field planners and MPOs in this review, FHWA has prepared a "checklist" of key questions associated with travel forecasting methods and their applications.

The questions included in the checklist are designed to provide the certification review team with an overview of the travel forecasting methods being used by an MPO, the suitability of those methods for intended applications, and the technical capabilities of the local planning staff in applying the methods. Currently, the checklist is not being used to identify "correctible actions" in the Certification Review. In cases where responses to the checklist questions raise serious concerns on the adequacy of the forecasting methods, the certification review team should request a more in-depth review by FHWA Resource Center or FHWA/FTA Headquarters travel model experts.

The checklist questions are excerpted here. The complete text of the guidance can be found online at: http://www.fhwa.dot.gov/planning/certcheck.htm.

Questions Regarding Risk

Is the metropolitan area a designated serious, severe or extreme ozone or serious carbon monoxide non-attainment area?

Is the metropolitan area a designated non-attainment or maintenance area, and has the MPO used travel demand models previously?

Does the metropolitan area plan to apply for an FTA transit new start grant?

Does the transportation plan include any major projects that will significantly increase highway capacity?
Regionally significant highway projects (e.g., new highways or additional lanes on existing highways) have been consistently targeted by national environmental advocacy groups as contributing to "urban sprawl" and "induced demand." These projects are particularly susceptible to legal challenges in which the plaintiffs hire their own travel model experts to dissect the forecasting methods used to derive forecasts of future traffic. Is the metropolitan area proposing any transportation projects where there is strong and coordinated opposition by local advocacy groups?

Is the metropolitan area proposing any transportation projects where there is strong and coordinated opposition by local advocacy groups?
Local groups with sufficient resources, or in coordination with national organizations, may also hire their own travel model experts to challenge controversial projects on methodological grounds.

Has the MPO been a defendant in, or threatened with, legal action in which the adequacy of their travel forecasting methods was challenged?
If so, what was outcome of this action? MPOs whose travel forecasting methods have been challenged in the past may be vulnerable to future challenges. However, if the challenge was summarily dismissed, or if the travel forecasting methods were upgraded in response to identified deficiencies, the MPO may actually be immunized against future challenges.

Questions Regarding Agency Technical Capabilities

Who is responsible for travel forecasting at the MPO?
Technical staff with expertise and experience in travel demand models is needed to develop, maintain and interpret the output from travel forecasting methods used in metropolitan transportation planning applications. This expertise may be provided by MPO in-house staff, by technical staff from another agency (e.g., another MPO or the state DOT), or by outside contractors.

If another governmental agency provides required modeling technical expertise:

If contractors perform all travel model development:

If in-house staff actively participate in model development and application:

Does the MPO organizational structure include a technical committee to review planning assumptions and forecasting methods?

Does the MPO have a strategic plan and a guaranteed minimum level of funding in its Unified Planning Work Program (UPWP) for maintenance and improvements to its travel forecasting methods?

Has the MPO convened a peer review or other independent assessment of their travel forecasting methods?

Documentation

The Certification Review Team should request and obtain readily available written, technical documentation from the MPO covering the following subject areas:

  1. Inventory of Current Conditions—should include information on (1) the local transportation system, (2) current population and employment, (3) measures of transportation system performance (e.g., VMT, transit mode share and congestion), local land use patterns, and special considerations (e.g., major port facilities, tourist areas).
  2. Planning Assumptions—should, at a minimum, address expected changes in (1) study area population and employment, (2) the geographic distribution of population, employment and land use within the study area, (3) and anticipated demographic or travel behavior trends that may influence future transportation needs.
  3. Forecasting Methods—should provide basic technical information on the forecasting methods, including calibration data sources, model specifications and calibration parameters, model validation results, and future plans for model updates and enhancements.

Table of Contents

TMIP Panel Suggests Topics for Peer Exchanges

A topic of discussion at the March 2004 TMIP Panel meeting was potential subjects for future focus. The panel members discussed many possible topics and conceived of the future study of those topics in a variety of forms, from workshops to agglomerations of information at ready disposal. Since that meeting, the topics have been conceptualized as peer exchanges, preliminarily defined and the panel members have each had opportunity to assign a value of importance to the topics.

These exchanges would denote a point of departure for further study. They are briefly described here with the hope that they will be conducted as schedules and funding allow.

Pricing and Tolling Analysis

Planning agencies face the challenge of incorporating pricing and tolling strategies into their traditional technical planning analyses in order to evaluate potential impacts to the transportation system. This exchange is to identify the state of the practice in pricing analysis, identify knowledge gaps, share best practices, and prioritize research. The USDOT Office of the Secretary will conduct this peer exchange sometime in the next calendar year.

Time of day, peak spreading and over-capacity links

Many urban areas are experiencing increasingly severe congestion and more prominent peak spreading. While over-capacity links may initially meter traffic, systemic congestion will result in changes in travel behaviors that include changed departure times, linked trips, and perhaps deferral of travel. Credible travel models in urban areas must reflect peak spreading phenomena. This exchange will discuss model formulations and approaches that incorporate time-of day choice and peak spreading with traditional models and tour based models with consideration for dynamic assignment methodologies.

Transportation Impacts on Development/Land Use

Land use impacts of transportation plans or projects are an area of significant debate. Although legal challenges to transportation agencies regarding plans or projects have focused on the issue of "sprawl inducing" transportation investments, implementing agencies often do not include project or plan specific land use scenarios in their impact assessments or plan updates. This exchange will review methods being used to estimate land use impacts of transportation plans or projects.

Communication and Use of Travel Models in Decision Making

Planning agencies spend considerable resources each year to collect data, build models, forecast land use and travel demand, and deliver information to assess the likely future utilization of existing and proposed transportation facilities and services. The intent is to help communities and their decision-makers make better transportation investment choices. This exchange will address how information produced from models is used by decision-makers and will explore ways to improve not only communication of model results but also institutional relationships in communication between technical staff and decision-makers.

Issues in Data Collection and Maintenance

As the field of transportation broadens to focus on new issues, and as planning analysis methods become more complex (and thus data hungry), agencies are challenged by data acquisition and management. While the broad adoption of GIS technologies have made some data management easier, the increasing demands for more data and analysis point to the need for sharing best practices in data collection and management. This exchange will focus on sharing best practices in planning analysis data collection and management strategies.

Freight/light duty commercial vehicles

However, a significant number of trips, made by commercial vehicles, including package and freight deliveries, tradesmen, taxis, rental cars, school buses, emergency services, etc., are not fully addressed by household-based travel models. This peer exchange will help identify different methods to incorporate freight and commercial vehicle travel into travel forecasting models.

Table of Contents

Hot Topics: Speed Flow Curves

By Madhav Pai, Dowling Associates, and Penelope Weinberger, TMIP

A general question was posed to the TMIP e-mail list in May 2004, regarding Speed Flow Curves. On behalf of the Southern California Association of Governments, a consultant sought innovative information on concepts, coefficients, and experimentation with speed flow relationships. Atlanta Regional Council (ARC) said that the result of extensive research resulted in unique volume delay functions for each time of day (see graphic). This led to response conjecturing on the various reasons why there are different curves for different times of day as it seemed counter-intuitive to the responder. ARC replied with more methodology by way of an answer and brought up the mid-day peak phenomenon occurring in large metropolitan areas. "Time of day models are the way to go it seems nowadays, especially in the context of large metro areas with complex and spread-out travel patterns, as encountered and observed in Atlanta," said Guy Rosseau, modeling manager with ARC. Next was the suggestion that an effect is the "non-local" nature of congestion; a result of measuring delay at a link different from the congested one. Of course, this led to a discussion of types of congestion and how they impact speed and volume. The discussion raised yet more questions and responses and even the comment that speed flow curves are irrelevant to what happens on urban arterial streets.

Summary of Speed Flow Curves used around the Nation

Methodologies used by different public agencies to model arterials in a travel-forecasting model were reviewed. The agencies were chosen based on geographical location (across the country) and sophistication of modeling methodology.

List of the agencies:

  • Metropolitan Transportation Commission (MTC), San Francisco Bay Area, CA
  • North Central Texas Council of Governments (NCTCOG), Dallas Fort Worth, TX
  • Sacramento Council of Governments (SACOG), Sacramento, CA
  • Denver Regional Council of Governments (DRCOG), Denver, CO
  • Atlanta Regional Council (ARC), Atlanta, GA
  • Metro, Portland, OR
  • San Diego Association of Governments (SANDAG), San Diego, CA

The initial intention was to plot all the speed flow relationships in a single graph. The approach and the parameters used by different agencies vary a great deal. For example the SACOG model uses a conical delay function, which adds an additional dimension to the graphical display. Hence we decided to present the mathematical form of the speed flow relationships.

Summary of Arterial Speed Flow Curves

Agency Location Form Type Mathematical Form Where
MTC San Francisco, CA Akcelik T is a function of the flow period, the degree of saturation, and the delay parameter. Tf = flow period (typically one hour)
x = degree of saturation (v/cu), and
JA = the delay parameter
NCT Dallas - Ft. Worth, TX Exponential Delay is a function of the hourly volume and the hourly capacity. Daily:
Freeway: A = 0.015, B = 6.20, C = 60.00.
Non-Freeway: A = 0.05, B = 4.00, C = 60.00.
Hourly:
Freeway: A = 0.015, B = 8.20, C = 60.00.
Non-Freeway: A = 0.05, B = 6.00, C = 60.00.
SACOG Sacramento, CA conical delay Congested travel time is a function of free flow travel time, a user-specified coefficient, the degree of saturation, and a VC ratio factor. TC =congested travel time
T0 = free flow travel time
x = degree of saturation (n/cu), and
a = a user-specified coefficient; and
b = (2a - 1)/(2a - 2)
e = 2 - b
r = VC ratio factor, adjusted so that TC = +/- 1.5 when VC = 1.0
max(Tc) = µ + n(VC)
DRCOG Denver, CO Form depends on value of Beta Generalized cost (GC) is a function of the value of time, free flow travel time, two calibrated parameters, the V over C ratio, the value of distance, distance, and fixed penalties. gc = Generalized Cost (Dollars)
VOT = Value of Time (Dollars per minute)
TFF = Free-Flow Travel Time (Minutes)
a = A Calibrated Parameter
V = Volume (Vehicles per Hour)
C = Capacity (Vehicles per Hour)
B = A Calibrated Parameter
VOD = Value of Distance (Cents per Mile)
D = Distance (Miles)
K = Fixed Penalties (Dollars)
ARC Atlanta, GA Different Curves by Time of Day ** See Figure 1  
Metro Portland, OR Intersection Delay + Midblock Delay F sub D is a function of the variables a, b, c, and x. Intersection:
a = 0.034807783 b = 0.22996809
c = 35.210296 d = 2.3015579
d = 2.3015579 x = volume/capacity
Mid Block:
a = 0.9999895 b= 0.70062753
c = 1.633602 d = 7.0559061
x = volume/capacity
SANDAG San Diego, CA Intersection Delay + Midblock Delay The volume capacity function is a function of time, c one, c two, c three, and c four. The delay function is a function of time, p one, p two, p three, and p four. f(x)=volume capacity function
c1 = 0.9526,
c2 = 1,
c3 = 3,
c4 = 3
p1 = 0.09,
p2 = 350,
p3 = 3.5,
p4 = 2.3
NOTE: Click on individual equations for their larger versions.

Figure 1. Atlanta Regional Commission Volume-Delay Functions for Freeway/Expressway/Principal Arterial by Time of Day.
Figure 1.

For the full discussion go to http://tmip.fhwa.dot.gov/email_list/ and join the list or peruse the archives.

Table of Contents

Upcoming Events

Conferences

January 9-13, 2005
84th TRB Annual Meeting
Washington D.C.
http://trb.org/meeting/

February 4-8, 2005
NARC 2005 Washington Policy Conference
Washington D.C.
http://www.narc.org/

March 19-23, 2005
APA National Planning Conference
San Francisco, CA

Courses

March 7-9, 2005 — Tampa, FL
Multimodal Travel Forecasting

Contact: http://www.ntionline.com/index.asp
732-932-1700

Additional offerings may become available; consult the TMIP website http://tmip.fhwa.dot.gov/ for the latest training information.

If you are interested in hosting a seminar or workshop in your area, please contact Penelope Weinberger (202) 366-4054.

Table of Contents

To subscribe to this free newsletter send an e-mail to TMIP@tamu.edu or contact Gary Thomas at (ph.) (979) 458-3263, (fax) (979) 845-6001, (mail) Gilchrist, Room 112, Texas Transportation Institute, Texas A&M University System, 3135 TAMU, College Station, TX 77843-3135