2 Transportation Planning and Modeling

CHAPTER OVERVIEW

This chapter provides a brief overview of the entire transportation project development process, including a historical snapshot of transportation planning in the United States since the 1940s. Part A presents the first step in project development – Network Planning – which requires layers of decision-making organizations coordinating the long-range vision for the transportation network, such as the Metropolitan Transportation Plan (MTP). The different agencies that contribute to the transportation planning and programming process and the resulting products are introduced. Conventional transportation planning, presented in Part B, often uses forecast modeling, known as Travel Demand Modeling (TDM). The Four-Step Model (FSM) is one type of TDM used to analyze the existing system and alternatives for proposed projects to be included in the long-range transportation plan. Environmental factors and other urban transportation challenges to FSM are discussed, noting the limitations of traditional trip-based models. A brief overview of the new modeling paradigm, activity-based modeling (ABM), is then provided.

CHAPTER TOPICS

1. Evolution of Transportation Planning in the United States
2. Transportation Planning: Strategic Direction
3. Contributors and Products of the Transportation Planning Process
4. Transportation Modeling: Analysis
5. The Four-Step Model Process
6. New Paradigm: Activity-based Models
7. Conclusion
8. Quiz
9. Glossary
10. Acronyms

INTRODUCTION

Overview of Transportation Project Development

The development of transportation projects, from concept to funding to construction to operation and maintenance, is complex and lengthy. Figure 2.1 schematically illustrates the process into its three major phases: network planning, programming, and project evaluation. The figure serves as a topical guide for this chapter’s content on transportation planning and modeling and for the next chapter, which covers the basics of transportation programming and evaluation.

Transportation is a vital community facility crucial for economic growth, development, and sustainability. The overarching goal of transportation systems is to streamline travel, enhance mobility, and improve accessibility to opportunities across various transportation modes in a cost-effective, environmentally responsible, and socially equitable manner. Transportation planners develop a long-term vision for the desired transportation system and the strategies for achieving it that translate into short-term project lists and implementation plans to achieve this vision (Federal Highway Administration & Federal Transit Administration, 2018). Ultimately, the transportation planning process helps decision-makers understand and select the most cost-effective, sustainable, and equitable transportation programs and facilities for their communities.

The typical steps in transportation planning are shown in Figure 2.2. Similar to Figure 2.1, this diagram also illustrates the continuum between the planning and programming phases of project development. This chapter focuses on Network Planning, aligning with the first four steps in Figure 2.2, from “Regional Vision and Goals” to “Development of Transportation Plan.” The accompanying YouTube video further discusses Figure 2.2 and provides a practical example of the transportation project development process covered in this and the next chapter. The video also emphasizes the importance of planning for transportation equity, which is discussed in Chapter Four.

Media 2.1 FHWA & FTA (2023, January 2023). Federal transportation planning process. [Video]. YouTube. https://youtu.be/T2BCt39Ub1k?feature=shared

Evolution of Transportation Planning in the United States

Examining transportation planning in the U.S. post-World War II era is crucial due to the significant transformations and developments that shaped today’s transportation infrastructure. After WW II, there was a significant rise in automobile ownership, which transformed transportation habits and infrastructure needs. The widespread availability and affordability of cars made personal vehicle travel the dominant mode of transportation. Likewise, there was a boom in suburban development, also known as suburbanization. People moved out of cities and into suburbs, necessitating extensive road networks to connect these new residential areas to urban and employment centers. This shift had a profound impact on transportation planning and infrastructure.

The U.S. government made substantial investments in transportation infrastructure, most notably through the Federal-Aid Highway Act of 1956, which funded the creation of the Interstate Highway System. These investments required coordinated planning and development at an unprecedented scale.

The post-war period marked the formalization and institutionalization of transportation planning as a professional field. The Federal-Aid Highway Act of 1962 mandated comprehensive transportation planning in urban areas, leading to the development of standardized practices and methodologies. To manage the complexities of urban and regional transportation planning, Metropolitan Planning Organizations (MPOs) were established for urban areas with populations over 50,000. These organizations facilitated coordinated planning efforts across different jurisdictions, ensuring more efficient and effective transportation networks. As a result, regional data-driven transportation planning facilitated through MPOs has become a standard practice.

In the late 1960s, opposition to planning focused on vehicular mobility and highway extensions grew due to externalities such as peak-time congestion, urban sprawl, and pollution. Increasing awareness of environmental issues led to significant legislation, such as the National Environmental Policy Act (NEPA) of 1969, which required environmental assessments for transportation projects. This shift integrated environmental considerations into transportation planning. In 1975, the U.S. Department of Transportation (US DOT) required all MPOs to develop short-term transportation management plans using low-cost strategies such as limiting parking, adding carpooling lanes, and metering ramps to manage peak-time travel demand. For the first time, managing demand rather than increasing road supply became a strategy for transportation planning and management.

Initially, the focus was on expanding the road network to accommodate the growth in passenger and freight vehicles and increase system capacity. However, starting in the 1980s and accelerating in the 2000s, there was a shift towards managing demand, promoting public transit, and integrating multimodal transportation options to address issues like congestion, pollution, and sustainability. Since then, numerous technological advancements in transportation have continued to evolve alongside the vision of a more sustainable transportation system. These advancements include improved road construction techniques, traffic management systems, and advances in computer modeling for travel demand forecasting and operations management, such as transportation systems management and operations (TSMO), introduced in Chapter One. Today, for instance, recognizing that the transportation sector is the largest source of greenhouse gas (GHG) emissions in the U.S., a 2023 blueprint joint initiative of the U.S. Departments of Transportation (US DOT), Energy (DOE), Housing and Urban Development (HUD) and the Environmental Protection Agency (EPA), for decarbonizing the transportation sector by 2050 has been launched. This bold initiative aims to provide a comprehensive new vision for the entire transportation system across all passenger and freight travel modes and fuels. The blueprint outlines three strategies to achieve the goal:

• “Increase convenience by supporting community design and land-use planning at the local and regional levels that ensure that job centers, shopping, schools, entertainment, and essential services are strategically located near where people live to reduce commute burdens, improve walkability and bikeability, and improve quality of life.
• Improve efficiency by expanding affordable, accessible, efficient, and reliable options like public transportation and rail, and improving the efficiency of all vehicles.
• Transition to clean options by deploying zero-emission vehicles and fuels for cars, commercial trucks, transit, boats, airplanes, and more” (US DOT, 2023, p. 4).

While the first two strategies have been central in land-use and transportation planning for some time, the third one is new and expected to be the major driver of GHG reductions. Though not the topic of this chapter, the blueprint illustrates a major shift in vision and strategy with future ramifications for the transportation planning and modeling practiced by State DOTs and MPOs, and other transportation agencies, the focus of this chapter.

PART A: TRANSPORTATION PLANNING: STRATEGIC DIRECTION

Network Planning: Where do we want to go?

Transportation planning and analysis is the first step in the overall transportation development process. Transportation planning involves two major activities – strategic direction and analysis – and is the formal response to the question, “Where do we want to go?”. Each activity includes many incremental and iterative subtasks as previously introduced in Figure 2.1. It is the process of envisioning the future of the transportation network, analyzing options, and selecting projects for inclusion in the long-term transportation plan with a horizon of 20 to 25 years. For example, at the regional MPO level, key components of the long-range plan, also known as the Metropolitan Transportation Plan (MTP), include a graphic representation of the network system map with conceptualized facilities, document outcomes of the public input process, and specify goals and objectives with associated performance targets. Additionally, the long-range plan is required to be created with fiscal constraint, meaning that the vision document must acknowledge the costs to design, plan, engineer, construct, operate, and maintain the transportation improvement. Modeling is one tool of financial planning as various project alternatives assist the public as well as decision-makers to make informed selections to include in the plan. In this sense, the plan is a strategy to direct future transportation improvements.

Vision

The strategic direction or vision is typically adopted in the long-range transportation plan and includes formulating future policies and goals with measurable performance outcomes. Acknowledging its collaborative nature, transportation planning engages various stakeholders in a cooperative effort to address the multifaceted challenges of long-range planning. Therefore, transportation planning establishes the vision for the future transportation network, coordinating the state, regional, or community systems (Federal Highway Administration & Federal Transit Administration, 2007).

Transportation Performance Management (TPM)

Federal legislation has established a strong link between the envisioned national transportation network and its anticipated performance. The Federal Highway Administration (FHWA) (2021) defines TPM as “a strategic approach that uses system information to make investment and policy decisions to achieve national performance goals” (FHWA, 2020, n.p.). Transportation performance, involving goals, measures, and targets, is integral to the development of transportation plans and programs at both metropolitan and statewide levels. TPM uses data-driven analysis and helps agencies align resources and actions with planning outcomes. For instance, 23 U.S.C Section 150 specifies seven (7) performance goals for the federal highway system outlined below:

1. Safety: Reduce traffic fatalities and injuries on public roads.
2. Infrastructure Condition: Maintain highway infrastructure in good condition.
3. Congestion Reduction: Reduce congestion on the National Highway System.
4. System Reliability: Improve the efficiency of the surface transportation system.
5. Freight Movement and Economic Vitality: Improve the national freight network, strengthen the ability of rural communities to access national and international trade markets, and support regional economic development.
6. Environmental Sustainability: Enhance the performance of the transportation system while protecting and enhancing the natural environment.
7. Reduce Project Delivery Delays: Reduce project costs, promote jobs and the economy, and expedite the movement of people and goods by accelerating project completion through eliminating delays in the project development and delivery process, including reducing regulatory burdens and improving agencies’ work practices (FHWA, 2013, n.p.).

Additional mandates about national performance goals, measures and targets can be found in the United States Code (U.S.C.) as provided on the US DOT Transportation Performance website. These codes specify the overall purpose and legal requirements for establishing performance-based planning and programming. Selected TPM statues are listed in the tables below (click TPM Statutes for the full list). These statutes about national goals, measures, plans, and reports are directives for federal (USDOT), State (DOTs), local regional transportation organizations (MPOs), and recipients of transportation federal funds. The federal- and state-level National Goals and Measures define the performance framework that States, MPOs, and federal funding recipients must comply with in their Targets, Plans, and Reports for achieving the national goals. Accountability and transparency TPM Statutes direct federal and state DOTs to evaluate, monitor, and report progress towards attaining the national goals. As can be observed, performance-based planning and the overall transportation planning process are federally driven and strongly tied to federal funding.

Table 2.1 Federal statutes addressing transportation performance management by category.

Statutory Federal TPM Mandates	Federal Statue
Requirement	Statute Link
National goals for Federal-Aid Highway Program.	23 USC 150(b)
General policy and purposes of public transportation program.	49 USC 5301
Goal of the National Public Transportation Safety Plan.	49 USC 5329(b)(1)
National freight policy goals.	23 USC 167(b)
Consideration of the Federal-aid highway national goals and public transportation general purposes in the scope of the performance-based planning process.	23 USC 134(h)(2)(A) 23 USC 135(d)(2)(A) 49 USC 5303(h)(2)(A) 49 USC 5304(d)(2)(A)
Funding eligibility considerations for the NHPP as they relate to the Federal-aid highway national goals	23 USC 119(d)(1)(A)
Consideration of Federal-aid highway national goals in State Asset Management Plans.	23 USC 119(e)(2)
TPM Measures	Federal Code
Requirement	Statute Link
Requirements for USDOT to establish national performance measures to assess performance/condition and used to carry out several Federal-aid highway programs.	23 USC 150(c)
Requirements for USDOT to establish performance measures based on state of good repair standards for transit assets.	49 USC 5326(c)(1)
Requirement for States to include highway safety measures in State Highway Safety Plans.	23 USC 402(k)(4)
Performance Targets	Federal Code
Requirement	Statute Link
Requirement for MPOs to establish performance targets for Federal-aid highway measures and public transportation established by USDOT.	23 USC 134(h)(2) 49 USC 5303(h)(2) 49 USC 5304(d)(2)
Requirements for States to establish performance targets for Federal-aid highway measures and public transportation established by USDOT.	USC 135(d)(2) 49 USC 5304(d)(2) 23 USC 150(d)
Requirements for public transportation Federal fund recipients to establish targets for measures established by USDOT based on the state of good repair standards.	49 USC 5326(c)(2)
Requirements for public transportation Federal fund recipients (or the State) to include targets based on the safety performance criteria and state of good repair standards established by USDOT.	49 USC 5329(d)(1)(E)
Requirements for states to establish targets for the performance measures required to be included in the State Highway Safety Plan.	23 USC 402(k)(3)(A)(ii)
Note: From “Transportation performance management,” by FHWA, 2017. Retrieved from https://www.fhwa.dot.gov/tpm/about/statutes.cfm#national. In the public domain.

Under TPM statutes, the U.S. Department of Transportation (USDOT) is responsible for identifying performance measures related to national highway and transit performance goals. These measures are used by States and MPOs to set their performance targets. Additionally, while using national goals as a baseline, States and MPOs can identify further performance measures and targets that reflect their local communities’ specific visions and goals. Furthermore, States and MPOs are required to set performance targets for measures that align with their respective statewide, nonmetropolitan, and metropolitan transportation planning processes.

Each of the factors in Box 2.1 responds to the question, “Where do we want to go?” and guides the crafting of the goals and objectives of the State plan that is typically focused on safety, performance, stewardship, and maintenance. Then, each goal is aligned with a measure, and a target metric is set to be met within the 20–25-year horizon of the plan. Approximately every four years, plans are regularly assessed and updated to address the plan area’s and stakeholders’ changing needs. The graphic below is from the 2050 Texas statewide long-range plan, known as the “Texas Transportation Plan 2050” (TTP 2050), and demonstrates only a few of the many goals, measures, and targets specified in the plan. For example, the goal for safety is measured by the statewide fatality rate with a performance target of zero fatalities on the transportation network by 2050. Based on the “Vision Zero” program that began in Sweden in the 1970s, the FHWA Highway Safety Programs includes resources for transportation agencies to incorporate the “Safe System Approach” into their long-range plans.

Contributors and Products of the Transportation Planning Process

There are different contributors to the planning process of the transportation system; each plays an essential role. The efforts and activities of these groups often overlap, including the imperative to include the thoughts and ideas of all stakeholders at all levels to ensure that the transportation planning process delivers the most efficient and inclusive outcome. Figure 2.5 depicts different contributors to the transportation planning process (PlanRVA.org, 2019). Historically, as has been earlier highlighted in Chapter One, the federal government plays a very strong role in transportation planning and funding. The next section briefly discusses the roles of the federal, state, regional, local, and other agencies.

Contributors

Federal

United States Department of Transportation (US DOT)

Chapter One briefly presented the U.S. government’s role in the transportation planning process, including legislation, funding bills, and executive orders. The USDOT is the umbrella organization for several transportation agencies, including the Federal Aviation Administration (FAA), the Federal Highway Administration (FWHA), the Federal Railroad Administration (FRA), and the Federal Transit Administration (FTA).

As discussed, transportation planning is a multi-faceted process as directed by overarching federal acts and mandates. Under the umbrella of the federal law, state, regional, local, and tribal government agencies are also important transportation planning contributors with specific roles in specific areas.

The next section highlights the primary government agencies at the state, regional and local levels involved in guiding the process in conformity to federally mandated structure.

State, Regional, and Local

State Departments of Transportation (DOTs)

State Departments of Transportation are agencies responsible for transportation planning, programming, and project execution at the state level. DOTs exist in all 50 states, Puerto Rico, and the District of Colombia. Furthermore, state DOTs oversee the planning, building, operation, and maintenance of state transportation facilities (highways, transit, air, and water) across all modes of transportation. Additionally, tolling authorities, ports, municipal agencies, and special districts collaborate with the state DOTs to guarantee that varied transportation needs are met. As a result, state DOTs must create, adopt, and regularly update a long-range strategy, known as the Statewide Long-Range Transportation Plan (SLRTP) (FHWA & FTA, 2007).

The major responsibilities of state DOTs are to:

• Ensure implementation of the continuing, cooperative, and comprehensive process (3C process).
• Certify that the plans and programs conform to federal goals and objectives.
• Provide platforms for discussing transportation-related issues among related agencies and operators and plan for transportation improvements.
• Oversee the planning procedures of the state MPOs (Federal Highway Administration & Federal Transit Administration, 2007).

Metropolitan Planning Organizations (MPOs)

The MPO is the decision-making entity in charge of the regional transportation planning process. MPOs have several important roles centered around ensuring that current and future federal financing for transportation projects and services is based on a 3C process defined as a “continuous, cooperative, and comprehensive planning process” (Federal Highway Administration, 2020, n.p.) in coordination with other transportation operators at the federal, state, and local levels. MPOs may also be found as part of Regional Planning Organizations (RPOs) and Councils of Governments (COGs) (Federal Highway Administration & Federal Transit Administration, 2007).

MPOs perform several functions within the entire transportation project development process:

• Transportation planning functions (Chapter Two) include:
  • Creating and regularly updating the long-range transportation plan.
  • Setting performance measure objectives that align community goals with state and federal goals.
  • Overseeing financial plans.
  • Analyzing transportation improvement options, and
  • Planning and documenting public participation.
• Transportation programming functions (Chapter Three), including:
  • Developing a short-range plan for the implementation of transportation improvements.
  • Monitoring the performance of completed projects in meeting targets
  • Gathering meaningful public input (Federal Highway Administration & Federal Transit Administration, 2007).

Table 2.2 Sample of Texas MPOs.

Texas Metropolitan Planning Organizations (MPOs)	Texas Department of Transportation District(s)	Census Urbanized Area(s)
North Central Texas Council of Governments (NCTCOG)	Dallas, Fort Worth, Paris	Dallas, Fort Worth, Arlington, Denton-Lewisville, McKinney
Capital Area MPO (CAMPO)	Austin	Austin, San Marcos
Houston-Galveston Area Council (H-GAC)	Houston	Houston, Conroe-The Woodlands, Lake Jackson, Galveston-Texas City

Regional Transportation Planning Organizations (RTPOs)

States may assemble a group of nonmetropolitan local leaders and transportation system operators to voluntarily serve on a Regional Transportation Planning Organization (RTPO) board or committee. RTPOs assist in the statewide and nonmetropolitan transportation planning process. While RTPOs are primarily focused on nonmetropolitan areas of the state; they often include members from the state transportation agency, private enterprises, transportation service providers, economic development practitioners, and the general public (Federal Highway Administration & Federal Transit Administration, 2007). Like MPOs, RTPOs are responsible for identifying local transportation needs and requirements, conducting planning activities, assisting local governments with the implementation of transportation plans, and supporting the statewide transportation planning process. As a result, RTPOs often assist policymakers in incorporating rural transportation demands into the statewide transportation planning process for areas with a population of fewer than 50,000 people (USDOT/FHA, 2021).

Public Transportation Agencies

In addition to other transportation-related agencies, smaller public transportation operators and governmentally chartered authorities are responsible for addressing the transit needs of the public. Therefore, in cooperation with states and MPOs, public transit operators help to fulfill the transportation planning process needs and requirements set by the federal government. To receive federal funding for projects performed by public transportation operators, MPOs and states must include these projects in their transportation plans and improvement programs (Federal Highway Administration & Federal Transit Administration, 2007).

Products

As part of the transportation planning process, transportation organizations must craft and regularly update several types of documentation.   Required planning and programming documents include:

• Public Participation Plan / Community Participation Plan
• Transportation Plan
• Transportation Improvement Program
• Unified Planning Work Program

Public Participation Plan (PPP) and Community Participation Plan

Before transportation long-range plans and programming documents can be considered and adopted by a transportation agency, they must follow an adopted Public Participation Plan (PPP). Public Participation Plans were mandated to receive federal funding with ISTEA. A 2001 article in the FHWA online “Public Roads” magazine states that public participation is a legacy of ISTEA, “bringing new players to the table when decisions were being made and increasing collaboration among old players” (FHWA, 2001, n.p.). The plan for public outreach documents specific strategies for gathering public input and includes a mandatory 45-day public review and comment period.  Then, in accordance with federal requirements and the adopted PPP, the transportation planning organization revises and updates the plan according to the input, schedules the plan for consideration at a public meeting, and adopts the federal and state-required planning document. The Community Participation Plan (CPP) elaborates and updates mandated public input in the US DOT guide, “Promising Practices for Meaningful Public Involvement in Transportation Decision-making”, published in October 2022. The guide for meaningful public involvement identifies tools to address public involvement gaps and increase capacity. These involvement strategies continue to meet the requirements of important federal acts, such as Title VI of the Civil Rights Act of 1964 and the National Environmental Policy Act of 1969, as well as recent Executive Orders discussed in Chapter Four.

The Metropolitan Transportation Plan (MTP)

Transportation plans include the Metropolitan Transportation Plan (MTP) developed by MPOs, which aligns with the SLRTP, prepared by the state DOTs. The MTP lays out the existing and future system network in metropolitan regions. Stakeholders and the general public work closely together to prepare MTPs, considering various criteria.

The MTP is a long-term strategy that spans 25 years and is modified every five years. The MTP depicts the influence of components such as highways, transit, nonmotorized transportation, and intermodal links on the multimodal transportation system’s operational performance. The MTP also includes performance measurements and objectives and explanations of achieving the performance measures and reaching the targets. Projected demand for transportation services over the next 20 years, policies, strategies, and projects that the MPO proposes for the future, cost projections, and reasonably accessible finance sources are some of the important items contained in MTPs (Federal Highway Administration & Federal Transit Administration, 2007).

Transportation Improvement Program (TIP)

Transportation Improvement Programs (TIPs) consist of Metropolitan TIPs from MPOs and Statewide TIPs from states. The TIP outlines how agencies will invest in the transportation system, including a prioritized list of local initiatives for the next four years. It is updated every two years, with adjustments as needed. Revisions are reviewed and voted on by MPO members, with public comments during the review process. MPOs create TIPs to detail which transportation projects will be completed within four years and the techniques to achieve this. Chapter Three provides examples of transportation programming. The TIP reflects the investment objectives of MTPs and indicates strategies and initiatives to meet MPO performance objectives. All federally funded initiatives must be included in the TIP, which must adhere to specific guidelines, such as covering at least four years of investment, being updated every four years, and undergoing audits.

The Unified Planning Work Program (UPWP)

UPWPs are often developed by MPOs and State Planning and Research Work Programs by state DOTs. The program provides MPO staff and member agencies with a list of the transportation studies and tasks they must pursue to support the metropolitan transportation planning process. Therefore, UPWP identifies and evaluates the funding source for each project. It also plans how these funds should be spent, what actions should be taken, and finally, which agencies are responsible for each task or study (Federal Highway Administration & Federal Transit Administration, 2007).

Table 2.3 Examples of transportation planning products in Texas.

Area	Agency	Planning Product
State	Texas Department of Transportation
	Statewide Transportation Plan	Texas Transportation Plan 2050
Region	Regional Planning: North Central Texas Council of Governments (NCTCOG – MPO)
	Metropolitan Transportation Plan (MTP)	Mobility 2045
	NCTCOG 2025-2028 Transportation Improvement Program (TIP)	2025-2028 TIP
	Public Participation Plan (PPP)	2022 PPP
	Unified Planning Work Program (UPWP)	FY 2024 and FY 2025 UPWP
Local	City of Dallas and City of Fort Worth
	City of Dallas:
	Thoroughfare Plan document	1993 Thoroughfare Plan
	Online GIS Thoroughfare Plan	CBD/Thoroughfare Plan
	Strategic Mobility Plan	2021 Connect Dallas
	City of Fort Worth:
	Master Thoroughfare Plan (document)	2020 Master Thoroughfare Plan
	Online GIS Thoroughfare Plan	Fort Worth Zoning map (select MTP layer)

Traditional Planning Inputs/Outputs

Planning a transportation system can be conceptualized as inputs, outputs, and outcomes, each carrying significant social, economic, and environmental implications.

Inputs

Figure 2.6 comprehensively illustrates transportation inputs, outputs, and outcomes. The items in the figure’s upper left are standard inputs related to infrastructure, such as roadways, bridges, and transit. However, other crucial inputs such as labor, energy, and vehicles are required to produce and operate transportation systems, and transportation networks require land. Additionally, the input of “information, operations, and management” was briefly introduced in Chapter One with the discussion of transportation demand management (TDM). Chapter Eight discusses transportation technologies, including information and communication technology (ICT) and smart cities. Finally, person trips, travelers’ time, and effort are critical components of travel demand discussed briefly in a following section and at length in the OERtransport book, “Transportation Land-Use Modeling and Policy.”

Outputs

Transportation systems provide numerous benefits, as illustrated at the bottom of Figure 2.6. They facilitate passenger mobility and accessibility to daily activities and services, such as work, school, shopping, and healthcare. Additionally, they enable freight travel, essential for economic development. Transportation is also crucial in emergencies, aiding in accident response and evacuations during natural hazards. Enhanced transportation options and technologies can improve accessibility and quality of life.

Outcomes

However, transportation also has negative effects, such as congestion, delays, and greenhouse gas emissions, impacting health, the environment, and climate change. The interaction between transportation and land use in car-centric urban areas affects accessibility, influencing who can access city opportunities based on socio-economic status or physical ability.

The factors shown in the upper right corner of Figure 2.6 represent transportation’s adverse outcomes or negative externalities. In addition to health and environmental impacts, they include injuries, fatalities, noise pollution, and reduced street safety, all affecting quality of life and property values. Chapter Four further explores how these adverse effects have historically burdened low-income communities of color. Due to these externalities, transportation planning has shifted from focusing solely on mobility and road capacity to prioritizing accessibility, multimodal planning, and equity. Now, planning and funding emphasize community involvement and improving access to opportunities over merely expanding infrastructure.

This section has highlighted the strong role that the federal government has played in transportation planning since the 1960s establishing the current metropolitan transportation planning process through the designation of MPOs and transportation performance management mandates. MPOs are charged with preparing a (20-year) metropolitan long-rage transportation plan and a short-range Transportation Improvement Program that includes projects drawn from the long-range plan. The next section, Part B, delves into transportation modeling, an integral component of the MPO planning process.

PART B: ANALYSIS: TRANSPORTATION MODELING

Overview of Transportation Modeling

Transportation models are mathematical and statistical simulations of human travel behavior in response to changes in local infrastructure, transit service or new federal or state policies. They aim to forecast how these changes will affect future travel demand, aiding agencies in selecting the best way to meet the travel demand equitably, environmentally and within funding capabilities. However, models make numerous assumptions about complex travel behavior, significantly simplifying reality. Their results only account for the factors included in the model’s equations and they need to be rigorously calibrated against travel surveys and data. Conventional travel forecasting models typically focus on vehicular travel and exclude other trip modes, such as pedestrian and bicycle trips.

Travel forecasting models are typically commercial software such as TransCAD or PTV Vissim or customized specialized programs for State DOTs or MPOs like TRANSIMS (TRansportation ANalysis SIMulation System) funded by the US DOT and tested in the Dallas-Fort Worth region. The program has evolved into open-source software available to the transportation community (tfresource.org 2024b; TCHRP, 2010). Models vary in complexity depending on their sophistication. However, all models are as accurate as their data and thus, up-to- date, accurate, and complete data is a critical requirement of any modeling approach.

Modeling is a technical, data-intensive, analytical activity performed by transportation planners and engineers to support the transportation planning process. Models are typically used to plan for the future using travel forecasts. Forecasts can be about future traffic conditions, such as congestion; they can be used to evaluate alternative transportation scenarios or proposed transportation systems and policies. They provide decision-makers with information to allocate funding and resources effectively and equitably. And they help transportation planners and officials meet federal criteria for prioritizing performance-based planning and policy setting discussed in Part A.

The Significance and Need for Models in Transportation Planning

As discussed in Part A, the MPO long-range (20-year) transportation plans are federally mandated. They require the ability to forecast future land use and travel patterns. Figure 2.10 outlines the basics of MPO transportation modeling and its integral role in the transportation planning process and acknowledges its limitations. As shown in the figure, “modeling is a tool for projecting the impacts of alternate transportation scenarios, such as new highways, bus route changes, or parking restrictions on future travel demand.” This allows planners to determine which scenario facilities or projects to include in the long-range transportation plan and decision makers to prioritize transportation investments.

Transportation models can assist in planning decisions (Beimborn, 2006; TCHRP, 2010) related to:

• Land use planning, including:
  • Testing traffic implications of land use policies, e.g., land-use regulation and growth management.
  • New development/redevelopment activity’s traffic impacts
  • Accessibility: simulating the interaction between land-use patterns and travel.
• Environmental policy, including:
  • Air quality modeling,
  • Fuel reduction measures, and
  • Environmental compliance issues.
• Congestion and travel demand management policy, including:
  • Congestion pricing and tolls,
  • High-occupancy (HOV) lanes,
  • Parking regulations, and
  • Telecommuting.
• Modal and Intermodal improvements, including:
  • Improved linkages between modes and
  • Multimodal planning – complete streets.
• Freight and commercial movement issues, such as assessing freight’s contribution to traffic congestion.
• Statewide planning, including providing macroeconomic forecasts of growth and demographic change.

Transportation Forecasting Overview

While traditional travel trip-based forecasting techniques like the four-step model (FSM) have been in use since the last half of the 20th century, by the 21st century, dissatisfaction with trip-based modeling prompted a growing number of agencies in the U.S. to shift to “advanced practices in travel forecasting” that went beyond the traditional four-step travel demand modeling approach (NCHRP, 2010). This section outlines the most salient features and limitations of the FSM and highlights the benefits of activity-based models (ABM)—one of the most widely adopted innovations in travel forecasting.

The Four-Step Model (FSM)

The Four-Step Model (FSM) consisting of trip generation, trip distribution, modal split, and trip assignment, is a widely used framework in transportation demand forecasting. The following discussion draws from more extensive treatments of the subject by Beimborn (2006), Levinson et al., (2014), and NCHRP (2010). For further details the reader is also encouraged to visit a companion to this book: Transportation Land-Use Modeling and Policy.

Assumptions and Data Elements

• Travel Analysis Zones: The process first requires that the urban area be divided into travel analysis zones (TAZs) of about one quarter to one square mile in size. The zones are assumed to represent or contain urban characteristics such as resident population and employment destinations. They are also assumed to be the location of a trip origin and destination. Typically, a planning study will encompass 500 to 2000 TAZs and should include nearly all (no less than 90%) of the trips beginning and ending in the urban area (Beinborn 2006).
• Transportation network: Highway and transit systems consist of “links“ (segments) of highways or streets and transit lines and “nodes” representing intersections. GIS attribute data for links include travel times, average speed, direction, capacity, etc. Node attributes may include data on intersections related to delays (Beimborn 2006).

The FSM Process

The FSM process involves the following steps:

• Trip generation estimates the number of trips entering or leaving a zone (e.g., trips entering Zone A or B). To calculate the number of trips originating from and arriving at different zones in the study area, it considers factors such as land use, population, and employment.
• Trip distribution estimates the number of trips leaving a specific zone and entering another zone (e.g., trips from zone A to zone B). In determining where trips will go or be distributed across zones, it estimates the number of trips between each origin and destination pair. It typically uses a gravity model based on the assumption that trip-making is proportional to the population size and inversely proportional to the distance between zones.
• Modal split estimates the number of trips from a specific origin to a specific destination made by a particular mode (e.g., trips from zone A to zone B by using mode T). It splits trips into different modes of transportation (e.g., car, bus, carpooling) based on factors such as travel time, cost, and convenience to determine the proportion of trips using each mode.
• Trip assignment determines the number of trips from one zone to another while using a specific mode and taking a particular route (e.g., trips from zone A to zone B using mode T on route R). It assigns the trips to specific routes within the transportation network. It uses algorithms to predict which paths travelers will take, considering congestion and travel times to estimate the distribution of traffic across the network.

Trip Generation

This step involves predicting the number of trips that start from or end at a specific location within a traffic analysis zone (TAZ) based on the types of land use identified in the local or regional future land use plan. Since each trip has an origin and a destination, it is important to identify these points to determine the number of trips that begin in one zone and end in another. Intrazonal trips, which begin and end within the same zone, are not included in the forecast.

For modeling purposes, land use is categorized into two main types: residential and non-residential. In residential areas, factors related to households, such as social and economic attributes, are considered for trip generation. Residential land use is seen as the origin of trips, whereas non-residential land use is seen as attracting trips. It is important to differentiate between “production and attraction” and “origins and destinations.” For example, even when households return from non-residential zones to residential zones, they are still considered to be producing trips, with the non-residential zone as the origin and the residential zone as the destination. Additionally, the purpose of a trip and the type of activity involved are factored into trip generation forecasts. Common home-based trip purposes include trips to work or school, shopping, dining out, or socializing, while less frequent home-based trips, such as visits to the doctor or the bank, are categorized as “other.”

Trip Generation Limitations

• Trip purpose is a simplified number of four to eight trip purposes results in simplified trip patterns. Shopping trips are all treated the same. The home-based “other” category includes a large variety of trip purposes (medical, family or friends’ visits, banking, etc.) influenced by more factors than those used in the model.
• Trip chaining is the combination of more than one trip purpose (e.g., stopping for groceries or mailing a package in the same trip) is not considered.

Trip Distribution

Trip distribution, also known as destination choice, identifies the distribution of generated trips from origins to destinations across different zones and provides an “OD trip table.” This table shows the number of trips starting from each origin and ending at each destination in a matrix format.

The most common approach for trip distribution is the gravity model. This technique distributes the trips produced in one zone to other zones based on their trip attraction size and distance. A large trip attraction zone, such as a shopping center, will attract more trips than a smaller one. However, the number of trips attracted will be inversely proportional to the distance from the origins. In other words, a nearby destination is expected to attract more trips than one located farther away.

Trip Distribution Limitations

• Automobile travel times are used to represent the distance between zones, which leads to a wider, more spread-out area of trip distribution. This limits the ability to represent travel patterns of other modes such as transit.
• Travel time assumptions used by the model assume that the average trip lengths (measured in travel time) will remain constant. However, travel times depend on network congestion levels, which are unknown at this stage and will be determined later in the forecasting process. Therefore, travel times are initially assumed, and if they differ from actual values, adjustments will need to be made, and the forecast will need to be rerun (Beimborn 2006).

Modal Split

Trips between an origin and a destination are split into trips using transit and trips using an automobile. More complex forecasts split trips into more modal categories (e.g., single occupancy vehicle (SOV), two or more-person carpool, vanpool, bus, express bus, light rail, etc.). The modal split or share for that origin-destination pair is computed on the basis of “disutility” representing a combination of travel time, cost, and convenience of each mode between an origin and the destination. Travel time is differentiated between time in vehicle and out of vehicle (e.g., walking between transit stops, waiting time). Out-of-vehicle time represents “convenience” and is weighted by the importance of the trip’s purpose. The relative differences between disutilities for mode choices between an origin and a destination are used to split trips among modes. A large difference corresponds to a large share for that mode. Model-generated splits are compared against actual travel survey data (Beimborn, 2006, p.15)

Modal Split Limitations

• Time and cost assumptions: To predict changes in travel demand, the model assumes that travelers choose between modes (car, transit, or carpooling) solely on costs of travel or time reflected in disutility, including in-vehicle time, out-of-vehicle time, or the cost of the car or transit (Beimborn, 2006).
  • The model does not include auto ownership costs such as insurance, maintenance, permits, etc.
  • A bus system and a rail system with the same travel time and cost will have the same disutility scores.
  • The importance of trip purpose is assumed to remain constant in terms of time, cost, and convenience.
• Omitted factors: The model gives no consideration to factors beyond travel time and cost that can influence mode choice, including:
  • Built environment factors like ease of walking or quality of transit amenities can affect travelers’ mode preferences.

Trip Assignment

This step assigns (highway or transit) trips to specific travel paths along the network from their origin to their destination. It is a computer-intensive iterative process that seeks to achieve equilibrium between the demand for travel along network paths (e.g., links and nodes) and the network capacity (supply) to accommodate travel aiming to avoid congestion at peak-traffic times.

Trip assignment limitations

The zones and network system are highly simplified as outlined below:

• All trips are assumed to begin and end at the centroid of the zones (TAZs) and occur in the network links in the model.
• Delays are assumed to occur on links, with highly simplified traffic assumptions at intersections.
• Intersection capacity and traffic control intelligent transportation systems are not analyzed in conventional trip assignment procedures.
• Capacities are simplified based on road type and number of lanes.
• The model cannot account for how travelers decide when to take their trips in response to traffic congestion (Beimborn, 2006).

Shortcomings of Traditional Trip-Based Models

As highlighted, the numerous limitations of conventional trip-based models, like the FSM, challenge MPOs’ ability to address federally mandated policies such as estimating motor vehicle emissions, evaluating alternative land use policies, or estimating nonmotorized trips. In 2007, the Transportation Research Board (TRB) stated that these models could not adequately represent “travelers’ responses to the complex range of policies typically of interest to today’s planners and politicians” (TRB, 2007, p. 3). They cannot capture the dynamic nature of transportation systems and overly simplify highway and transit network congestion as averages. TRB (2007, pp. 3-5) summarized the major shortcomings of trip-based models as follows:

• Time chosen for travel: The model is unable to capture the choices travelers make in response to congestion and other system performance issues. They cannot provide information on variables that depend on travel by time of day, such as vehicle emissions, response to congestion or road pricing, variable work schedules, etc.

• Travel behavior: The model simplistically represents travel behavior at the TAZ level in a highly aggregate manner. It is unable to represent travelers’ responses to policies like road pricing, telecommuting, transit vouchers, and changes in land use. Also, the models cannot account for trip-chaining involving several interconnected trips in the same journey.

• Nonmotorized travel: The model is unable to capture walking and bicycle trips and land use effects on these trips because the models do not include TAZ intrazonal travel. They cannot evaluate the impacts of changes in the built environment, such as transit-oriented development or smart growth zoning.

• Time-specific traffic volumes and speeds: The model inaccurately disaggregates estimates of time-specific volumes on specific routes. These estimates are indispensable to evaluate improvements in traffic operations, mode of access to transit stations, travelers’ time shifting of travel for coping with congested networks, calculating air quality emissions, and dealing with freight movement policies.

New Paradigm: Activity-Based Models

Activity-Based Models (ABM)

In response to the limitations of trip-based models, activity-based models (ABMs) have emerged as a more accurate representation of individual travel behavior. Table 2.4 by the Caliper Corporation compares the two types of models. Several advantages of ABMs are summarized below:

• Tours versus Trips: Rather than trips, ABMs are based on tours that reflect household and individual travel patterns.
• Trip Interdependence: ABMs recognize the scheduling and organization of trips within tours.
• Personal Attributes: Each traveler’s unique characteristics inform their travel choices providing spatial, temporal, and modal trip information during the day and within the same tour.
• Motivation for Travel: ABMs consider activity participation, allowing for travel and non-travel substitutions.
• Accessibility Effects: ABM takes into account the impact of accessibility (related to land use patterns, opportunities, and congestion) on travel generation.
• Individual Schedules: ABM simulates the activity-travel decisions and schedules of individual households and persons (tfresource.org, 2024).

Several MPOs, like Portland, San Francisco, New York, Dallas, Sacramento, Denver, Seattle, the Bay Area, San Diego, Atlanta, Los Angeles, and Phoenix, have developed versions of ABMs specific for transportation planning and modeling to their contexts. These ABMs, like SCAG’s in Southern California, allow for better methodological rigor and more flexibility in supporting planning and policy decisions.

Table 2.4 Comparison of Trip-Based and Activity-Based Models.

blank cell	TRIP-BASED MODELS	ACTIVITY-BASED MODELS (ABMs)
Model Type	Aggregate (at TAZs)	Full population (individuals & households)
Model unit	Trips	Activities served by tours
Demographic data	Aggregated to traffic analysis zones (TAZ): average HH size, HH auto ownership, HH income, etc.	Household- and person-specific variables such as age, gender, income, etc.
Trip generation	Based on trip rates applied uniformly across all “average” persons in each segment.	Based on choice models that can capture the individual behavior observed in the survey.
Trip distribution	Gravity models that assign destinations that attenuate with impedance. Cannot easily and flexibly capture special attractors, etc. Friction factors are used to calibrate trip length distributions. These may fit the base case but could break in scenario analysis	Destination choice models capture every location choice specific to the constraints and demographics of each person/ household. Variables specific to each destination can be incorporated, with behavioral responses adapting to scenario changes.
Mode choice	Predominantly based on aggregate Logit models that cannot incorporate person- or household-specific variables such as gender, driver’s license, ownership, number of kids, number of seniors, etc.	Based on disaggregate Logit models that can flexibly include any relevant person and household variables. Choices can be made individually for each person.
Tour consistency	Consistency between tour legs cannot be enforced in general.	Choice models are executed at the tour level for easy enforcement of various constraints.
Household/person constraints	Cannot be handled.	Explicitly handled at the level of individuals and households
Outputs	Aggregate and at the level of zones, OD pairs, and trips. The time periods equal the peak and off-peak periods used by trip generation onwards. Results at a finer resolution cannot be obtained. Results at the tour level are also not available.	Results are available at the person, household, tour, and trip levels. These may be aggregated to any desired resolution. The time resolution is nearly continuous, with activity and trip start times and durations simulated by the minute. Peak period analysis can still be performed by aggregating the results to the trip-based model’s period definitions.
Note: From “The Central Coast Supra-Regional Activity-Based Model” by Caliper (2020) p. 3. https://www.ambag.org/sites/default/files/2021-03/CCABM_ProjectOverview_PDFA.pdf CC AMB

CONCLUSION

Post-World-War-II transportation planning in the US focused on improving mobility and expanding capacity to deal with congestion, overlooking several associated factors such as environmental quality, equity, and sprawl. Federal legislation established the role of the MPO in regional transportation planning and the performance goals of the national transportation system, which over the years have evolved in response to economic, environmental, and equity concerns. Through transportation performance management (TPM) statutes, the federal government ensures that state, regional, and local transportation agencies set performance targets and align their respective state, metropolitan, and non-metropolitan transportation planning processes with national goals. Emphasizing collaboration with stakeholders and public participation, MPOs are required to prepare long-range (20-25 years) Metropolitan Transportation plans and short-rage (4 years) Transportation Improvement Plans. The former plans set the strategic vision and the latter detail the projects that will be completed towards achieving the vision.

Modeling has been used in the decision-making process of long-range transportation plans. The conventional modeling technique, known as trip-based models, involves four main steps: trip generation, trip distribution, mode choice, and trip assignment. Newer transportation planning modeling techniques, such as activity-based models, aim to provide a more realistic and reliable representation of transportation supply and demand. Transportation planning is an ongoing process, and modeling is an analytical tool used by transportation planners and engineers to forecast travel demand and changes in travel demand associated with proposed improvements to the transportation system. Chapter Three continues the discussion of the process of transportation project development, focusing on short-range transportation planning, known as programming, and a discussion of project evaluation.

QUIZ

GLOSSARY

Acronyms

3C process is the transportation process which stands for “continuing, comprehensive, and cooperative” and was first specified in the Federal-Aid Highway Act of 1962. Its purpose is to be inclusive, focused on public input, and to prioritize regional planning of transportation projects.

Activity-based modeling (ABM) is a type of forecasting model that takes individual-level data as input and simulates the activity pattern for each individual.

Externalities are impacts not accounted for in market transactions. They can be negative (harmful effects on others) or positive (benefits). Motor vehicle air pollutants are an example of externalities.

Disutility of mode choice: In trip-based forecasting, “disutility” refers to the perceived negative aspects or costs associated with a particular mode of transportation. Disutility in mode choice quantifies the overall inconvenience or undesirability of each travel option. Components of disutility may include travel time, cost, comfort, convenience, and reliability.

Gravity Model is a model that postulates that the number of trips between each pair of zones is dependent on the relative attractiveness of destination. This attractiveness is directly related to the number of opportunities in the destination and inversely related to the distance between them.

Meaningful public involvement is defined as a process of intentionally programmed outreach to representatives of the entire community and inclusion of the community’s needs and vision into the transportation planning and programming documents (US DOT, 2022).

Metropolitan planning organization (MPOs) is an organization responsible for carrying out transportation planning process for urban areas with over 50,000 population and tries to integrate practices from multiple jurisdictions in the area (Federal Highway Administration, 2017).

Mode: The means used for travel (e.g., walking, driving your car, riding as a passenger on a bus).

Modal split: The share of travelers using each mode of travel.

Model: A set of mathematical relationships to forecast travel patterns and flows between origins and destinations.

Multimodal is a transportation network quality that includes various models such as rail, bus, ferry, bicycle, etc. which allows users to choose their mode of transport by providing convenient access (tn.gov)

Performance target is “a quantifiable level of performance or condition, expressed as a value for the measure, to be achieved within a time period required by FHWA” (FHWA, 2018, p. 75).

Person trip is “a one-way trip made by a person by any mode from an origin to a destination, usually assumed to be without stops. In many models, person trips are the units used in all model steps through mode choice. Person trips are the usual units in transit assignment, but person trips are converted to vehicle trips for highway assignment” (NCHRP, 2012, p. 6).

Safe Systems Approach is a program of the Federal Highway Administration (FHWA) aimed to meet one of the federal transportation planning goals, safety. The approach is defined as “the aim to eliminate fatal & serious injuries for all road users. It does so through a holistic view of the road system that first anticipates human mistakes and second keeps impact energy on the human body at tolerable levels. Safety is an ethical imperative of the designers and owners of the transportation system” (FHWA, 2022, p. 1)

Special districts are transportation agencies responsible for unique facilities within or distinct segments of the transportation network (Transportation Planning Capacity Building Program, 2022).

Suburbanization is the process of urban expansion beyond the borders of central area and population and services flee toward low-density areas where land and space re more abundant.

Tours is a travel diary that contains a chain of trips with multiple stops and same beginning and ending point such as home.

Traffic analysis zone or travel analysis zone (TAZ): An area delineated by state and local transportation officials for tabulating traffic data for travel demand analysis. A traffic zone usually consists of one or more census blocks, block groups, or census tracts.

Transportation or Travel demand model (TDM) is a mathematical representation of individual trips and travel demand, allowing transportation planners and engineers to study the potential impacts of different transportation scenarios when creating regional and state long-range transportation plans.

Transportation systems: The infrastructure and logistics for transporting people and goods incorporating all forms of transport, from private vehicles, rail, and buses to boats, ships, and air travel.

Trip: A one-way movement from an origin to a destination.

Trip-based modeling uses “the individual person’s trip as the fundamental unit of analysis. Trip-based models are widely used in practice to support regional, subregional, and project-level trans­portation analysis and decision making. Trip-based models are often referred to as “4-step” models because they commonly include four primary components. The first trip genera­tion components estimate the numbers of trips produced by and attracted to each zone (these zones collectively represent the geography of the modeled area). The second trip distribution step connects where trips are produced and where they are attracted to. The third mode choice step determines the travel mode, such as automobile or transit, used for each trip, while the fourth assignment step predicts the specific network facilities or routes used for each trip” (Castiglione et al, 2015, p. 6).

Trip chaining is a travel behavior that involves grouping some activities together into a one trip to save travel time and miles.

Trip origin and destination: The location where a trip begins and the location where the trip ends.

Trip purpose: The traveler’s primary goals for making a trip.

Trip table or Origin-Destination (O-D) matrix: A matrix that shows the number of trips between each pair of zones in travel demand analysis.

Vehicle miles traveled (VMT) is an aggregate measure for transportation demand in a region and is represented by total number of miles of all travelers within a certain time frame in a region.

Vision: A statement summarizing the purpose of the plan based on public input and the community’s needs using goals and objectives to promote implementation.

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