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Congestion Management Process Guidebook

Chapter 2 - Process Model

The Process Model that follows is built upon activities or "actions" that are common to successful CMPs, and at a basic level must be implemented to comply with federal regulations. The actions, however, may be integrated into the MPO planning process in many different ways, providing a flexible framework from which MPOs can develop an individualized CMP approach. This guidebook also provides suggestions of good practices and examples of effective approaches associated with each of these actions.

The elements of a successful CMP defined in the Process Model that follows serve as a guide for the actions to be taken in developing a CMP. Whereas the Interim Guidebook referred to "steps" in the CMP, they are referred to here as "actions", recognizing that while the CMP includes a general sequence of activities, the cyclical nature of the metropolitan planning process means that there are iterations within the sequence, and MPOs may have some variations to this approach. These eight actions - and related questions - include:

  1. Develop Regional Objectives for Congestion Management - First, it is important to consider, "What is the desired outcome?" and "What do we want to achieve?" It may not be feasible or desirable to try to eliminate all congestion, and so it is important to define objectives for congestion management that achieve the desired outcome. Some MPOs also define congestion management principles, which shape how congestion is addressed from a policy perspective.
  2. Define CMP Network - This action involves answering the question, "What components of the transportation system are the focus?", and involves defining both the geographic scope and system elements (e.g., freeways, major arterials, transit routes) that will be analyzed in the CMP.
  3. Develop Multimodal Performance Measures - The CMP should address, "How do we define and measure congestion?" This action involves developing performance measures that will be used to measure congestion on both a regional and local scale. These performance measures should relate to, and support, regional objectives.
  4. Collect Data/Monitor System Performance - After performance measures are defined, data should be collected and analyzed to determine, "How does the transportation system perform?" Data collection may be on-going and involve a wide range of data sources and partners.
  5. Analyze Congestion Problems and Needs - Using data and analysis techniques, the CMP should address the questions, "What congestion problems are present in the region, or are anticipated?" and "What are the sources of unacceptable congestion?"
  6. Identify and Assess Strategies - Working together with partners, the CMP should address the question, "What strategies are appropriate to mitigate congestion?" This action involves both identifying and assessing potential strategies, and may include efforts conducted as part of the MTP, corridor studies, or project studies.
  7. Program and Implement Strategies - This action involves answering the question, "How and when will solutions be implemented?" It typically involves including strategies in the MTP, determining funding sources, prioritizing strategies, allocating funding in the TIP, and ultimately, implementing these strategies.
  8. Evaluate Strategy Effectiveness - Finally, efforts should be undertaken to assess, "What have we learned about implemented strategies?" This action may be tied closely to monitoring system performance under Action 4, and is designed to inform future decision making about the effectiveness of transportation strategies.

The graphic that follows illustrates these actions, and highlights the cyclical nature of the process. While these actions are presented in a linear form, it is important to recognize that within the cycles of transportation planning, some of these actions may be revisited, or occur on an on-going basis, while others may not. For instance, in updating the MTP, the MPO may revisit or develop new congestion management objectives, which may lead to development of new performance measures; but the MPO might not redefine other aspects of its CMP at the same time. The CMP network might not be updated with each update of the MTP, and data collection activities may occur on an annual basis or some other cycle. Consequently, the Process Model is not intended to serve as a step-by-step approach, but is intended to convey the general flow of the approach, building on regional objectives to implementation of strategies, and evaluation of their effectiveness.

Figure 2. Elements of the Congestion Management Process

Elements of the Congestion Management Process. Click for more information.

The process model actions are discussed with illustrated examples from current MPO practices in the following text.

2.1 - Action 1: Develop Regional Objectives for Congestion Management

What do we want to achieve?

Congestion management objectives define what the region wants to achieve in regard to congestion management. Eliminating traffic congestion may not be possible, particularly in fast growing regions. Moreover, eliminating congestion may not actually be desired if it comes at the expense of economic vitality, community livability, or bicycle/pedestrian access. Therefore, it is important to define what is considered "unacceptable congestion" and set appropriate objectives for congestion management that support regional goals.

Federal regulation (23 CFR 450.320 (c) 2) requires congestion management objectives as part of the CMP.

The starting point for the CMP is the development of regional objectives for congestion management. These objectives should draw from the regional vision and goals that are articulated in the MPO’s MTP. Congestion management objectives also may be developed for the CMP as part of the long-range transportation planning process and incorporated directly into the MTP. In some cases, MPOs develop objectives specifically for the CMP; in other cases, congestion management objectives from other sources (e.g. the MTP or a regional vision document) are used to guide the CMP.

The Role of Congestion Management Objectives

Congestion management objectives define what the region wants to achieve regarding congestion management, and are an essential part of an objectives-driven, performance-based approach to planning for operations. Congestion management objectives should serve as one of the primary points of connection between the CMP and the MTP, and will serve as a basis for defining the direction of the CMP and performance measures that are used.

Historically, the development of congestion management objectives has often been missing from the CMP, particularly if the process was primarily envisioned as a data collection and analysis exercise. However, to effectively address congestion, it is vital to specify objectives that the region would like to achieve. In developing objectives for congestion management, it is important for MPOs to consider how to define these objectives such that they support a range of regional goals. Looking at the role of congestion management in the context of livability, economic vitality, safety, and multimodal access helps to ensure an efficient use of resources and ultimately will lead to strategies that help to achieve the regional vision. These objectives are typically developed by the policy board of the MPO or a designated subcommittee of elected officials, with technical input from staff, often with the involvement of the public and stakeholders.

The congestion management objectives should reflect the priorities of the MPO, and should serve as a valuable tool for the MPO to assess how well its actions and policies are helping to achieve its goals. Objectives are not designed to measure the "success" or "failure" of specific programs, activities, or projects - they are meant to address regional priorities to help guide the direction of future decision making. Objectives should be derived from the vision and goals articulated in the MTP and other plans of the region. The vision and goals will likely be developed early in the planning process, but the development of congestion management objectives may help sharpen and focus the goals.

Understanding What the Public Wants

The development of congestion management objectives should rely heavily on stakeholder participation and an understanding of the needs and desires of the public related to congestion. This may be identified through the public involvement aspects of the long-range transportation planning process, as well as through what stakeholders articulate at the local level, such as through corridor studies and project-related efforts. Some regions have also used public opinion surveys to understand the priorities of the public, and stakeholder work groups as a basis for developing objectives.

Traditionally, the CMP has often focused on capacity issues, and used engineering measures focused on motor vehicles, such as volume-to-capacity ratios. In defining appropriate congestion management objectives, planners and decision-makers should consider the following questions:

Answering these questions may lead to objectives that are quite different from a traditional approach focusing on addressing level of service (LOS) deficiencies or easing vehicle traffic congestion. For instance, some regions have found that focusing on the aspects of congestion that stakeholders and the public care about most can lead to a focus on issues such as:

In other words, the objectives that guide the CMP are not limited to the traditional measures such as level of service - a CMP can also address other issues that are affected by or have an effect on congestion.

Characteristics of Congestion Management Objectives

Regional objectives should ideally focus on outcomes - such as hours of delay, system reliability, and access to traveler information. However, they may also be written using output measures - such as incident clearance time or number of traffic signals retimed annually. In all cases, objectives should be stated in a way that meaningful performance measures can be derived from the objectives.

Objectives are specific, measurable statements developed in collaboration with a broad range of regional partners. They are regional or multi-jurisdictional in nature. The objectives should be defined in a manner that allows practitioners to focus on specific aspects of congestion and to advance a timeframe within which the objectives can be attained. Objectives generally lead directly to a performance measure that can be used to assess whether or not the objective has subsequently been achieved. They can be tracked and/or monitored on a regional level and inform cyclical investment decisions.

An ideal objective should have "SMART" characteristics as defined here:

Specific - The objective provides sufficient specificity to guide formulation of viable approaches to achieve the objective without dictating the approach.

Measurable - The objective facilitates quantitative evaluation, saying how many or how much should be accomplished. Tracking progress against the objective enables an assessment of effectiveness of actions.

Agreed - Planners, operators, and relevant planning participants come to a consensus on a common objective. This is most effective when the planning process involves a wide-range of stakeholders to facilitate regional collaboration and coordination.

Realistic - The objective can reasonably be accomplished within the limitations of resources and other demands. The objective may require substantial coordination, collaboration, and investment to achieve. Factors such as population growth, economic development, and land use may also have an impact on the feasibility of the objective and should be taken into account. Based on data on system performance and analysis, the objective may need to be adjusted to be achievable.

Time-bound - The objective identifies a timeframe within which it will be achieved (e.g., "by 2012").

Examples of SMART Objectives

Examples of "SMART" objectives include the following:

In practice, objectives may start out somewhat general (e.g., improve system reliability), but then through the actions that follow - including defining performance measures, collecting data, etc. - the objectives may be revisited and defined to be more specific, measurable, and time-bound (e.g., reduce the person hours of total delay on highways and major arterials associated with traffic incidents by "X" percent over "Y" years.). A typical progression may occur as follows:

Developing SMART operations objectives may be challenging to some MPOs since it may be difficult to develop consensus on specific target numbers, and staff and decision-makers may be concerned about what happens if specific targets are not achieved. On the other hand, the process of developing regional congestion management objectives may be a catalyst for getting decision-makers from across a region to work together with a common focus, resulting in progress on issues that constituents care about, such as multimodal accessibility, reliability, and access to accurate traveler information.

Congestion Management Principles

In addition to developing objectives, this early stage of the CMP may also involve development of congestion management principles that shape how congestion is addressed from a policy perspective. Principles are different from objectives since they do not focus on outcomes or outputs that can be measured and tracked over time. Rather, they are statements of priority from a policy perspective. For instance, congestion management principles may:

The Capital District Transportation Committee (CDTC) in Albany, New York has established congestion management principles as part of its CMP, and these principles are included in the MTP. CDTC believes that what the residents of the region want - as articulated in the regional vision and as expressed though their involvement in corridor and project-level studies - must help to define the way in which congestion management is applied in the region.

Through surveys and public involvement activities, CDTC has learned a key public opinion: that the public wants more bicycle, pedestrian, and other improvements, and that travel time reliability is the most important congestion issue for travelers in the region. CDTC has defined congestion management principles that focus on demand management and operations improvements before constructing new capacity (see text box).2

Case Study: Congestion Management Goals and Principles at the Capital District Transportation Committee (CDTC)

The CMP of CDTC in Albany, New York, contains two goals, developed by CDTC and approved by the MPO Board:

  • Support growth in economic activity and maintain the quality of life in the Capital District by limiting the amount of "excess" delay encountered in the movement of people, goods, and services.
  • Make contributions to the avoidance and mitigation of congestion on all modes by implementing demand management programs first, before performing capacity expansions. Reducing single-occupant vehicle travel can be accomplished by encouraging telecommuting and programs that reduce the need for travel, balancing travel demand by time of day, encouraging the use of transit, ridesharing, pedestrian and bicycle modes, improving operational efficiencies and achieving complementary transportation and land use systems.

In addition, a set of congestion management principles are included in CDTC's New Visions Plan, and are designed as principles to help guide the selection of actions. The congestion management principles include:

  • Management of demand is preferable to accommodation of single-occupant vehicle demand growth.
  • Cost-effective operational actions are preferable to physical highway capacity expansion.
  • Capital projects designed to provide significant physical highway capacity expansion are appropriate congestion management actions only under certain circumstances.
  • Significant physical highway capacity additions carried-out in the context of major infrastructure renewal are appropriate only under certain circumstances.
  • Incident management is essential to effective congestion management.
  • Any major highway expansion considered by CDTC will include a management approach.
  • In project development and design, other performance measures, such as pedestrian, bicycle, and transit access, community quality of life, and safety will be considered along with congestion measures.
  • The New York State Department of Transportation guidelines for roundabouts will be used for all CDTC federal aid projects that involve intersection improvements.

Source: CDTC, "The Metropolitan Congestion Management Process," May 2007, www.cdtcmpo.org

2.2 - Action 2: Define CMP Network

What components of the transportation system are we analyzing?

The CMP should involve analysis within a specific geographic area and network of surface transportation facilities. The action of defining the CMP network for analysis will likely not need to be revisited on a regular basis, unlike other elements of the CMP. However, as travel patterns and development in a region change, and as new data sources become available, it may be useful to revisit the system components being analyzed as part of the CMP.

Defining the CMP network involves defining two aspects of the system that will be examined as part of the planning process:

The travel demand model represents a primary analysis tool in regional planning, and therefore the model roadway network typically provides the baseline for establishing a CMP roadway network. If the model contains a transit network as well as a highway network, the CMP network may consider how these two modes interact. In areas where multimodal analysis is done off-model, the highway network may provide the basis for selecting a CMP network, although transit services, and bicycle and pedestrian infrastructure may also be incorporated into the CMP network analysis. It is important to note that this does not mean the model must be the primary source of information for the CMP, just that this is a logical baseline many MPOs use for defining the set of roads and multimodal facilities that will be studied in the CMP.

Geographic Area of Application

For many regions the CMP network will correspond to the full planning area network; however there are exceptions. In areas where there are significant traffic generators in the rural area outside the MPO boundary, it may be important to capture the connecting roads in the CMP network to monitor congestion. Neighboring MPOs may choose to partner in the development of a joint CMP, extending the network beyond their individual planning boundaries.

System Components

In regions where the planning area highway network is very dense, a subset of roads may be identified for the CMP in order to limit data collection and analysis to the most congested facilities. Some MPOs have adopted a corridor-based planning approach-in these areas, selected corridors will make up the CMP network. In each instance, the CMP network must include those areas that meet the regionally identified definition of ‘congested’ and represent the area for data collection and monitoring activities.

There are several methods by which MPOs define their CMP networks.

Multimodal transportation elements are important factors for addressing congestion in any urban area. Elements of a multimodal network may include:

Although the CMP has traditionally focused primarily on the road network, the CMP network should consider the transit, bicycle, and pedestrian networks as well as their interface with the highway network. Doing so can help take advantage of strategies that rely upon the other modes to reduce single occupancy vehicle (SOV) travel. Typically, collectors and local roadways are not included in the roadway analysis of the CMP since it would be time-consuming to address these roadways and they generally have relatively low traffic volumes and congestion levels; however, these facilities should still be considered as potential bicycle, pedestrian, or transit corridors. The CMP analysis network will often include major intersections along arterials, given that intersections are often points where travel delay occurs.

Case Study: CMP Network Definition at the Delaware Valley Regional Planning Commission (DVRPC) and Wilmington Area Planning Council (WILMAPCO)

Following data collection/gathering, DVRPC, the MPO for the Philadelphia region, uses analysis of its identified evaluation criteria to identify congested corridors and divide them into logical subcorridors. There are usually around 15 corridors identified in each state (PA and NJ), with over 100 subcorridors defined. DVRPC uses GIS layers for its network and does most of its analysis using GIS.

WILMAPCO, the MPO for Wilmington, Delaware, has a two-tiered CMP network. The first tier, for data collection, includes all roads within the MPO area that are functionally classified as minor arterials or a higher class. The second tier of the CMP network is a set of congested corridors for which detailed congestion management strategies are developed—these corridors are identified following the collection and analysis of data.

Sources: DVRPC, "Overview of the CMP," 2009, www.dvrpc.org/CongestionManagement; WILMAPCO, "2009 WILMAPCO Congestion Management System Summary," July 2009 www.wilmapco.org/cms

2.3 - Action 3: Develop Multimodal Performance Measures

How do we define and measure congestion?

Performance measures are a critical component of the CMP. According to Federal regulation, the CMP must include "appropriate performance measures to assess the extent of congestion and support the evaluation of the effectiveness of congestion reduction and mobility enhancement strategies for the movement of people and goods. Since levels of acceptable system performance may vary among local communities, performance measures should be tailored to the specific needs of the area and established cooperatively by the State(s), affected MPO(s), and local officials in consultation with the operators of major modes of transportation in the coverage area."

23 CFR 450.320 (c) 2

Developing performance measures to identify, assess, and communicate to others about congestion is a critical element of the CMP. One key to the effectiveness of the CMP is the ability of the MPO staff to adequately assess system performance in order to identify problem areas and communicate this information to the public and decision-makers, thereby affecting on-the-ground projects.

Roles of Performance Measures

The overarching purpose of using performance measures in the CMP is to characterize current and future conditions on the multimodal transportation system in the region. However, performance measures serve multiple purposes that intersect and overlap in the context of the CMP, including:

Performance measures are used at two levels:

At the regional level, performance measures can be used to compare plan alternatives in the development of the MTP, to determine which alternatives are more successful in achieving a balance between different objectives (including those identified in Action 1), maximizing the overall benefit. They also can be used as part of transportation system monitoring to track progress toward the achievement of the objectives. To accomplish these functions, performance measures must be developed that directly correspond to CMP objectives. For example, if one of the CMP objectives is to "Reduce hours of delay per capita by 15 percent by year 2030," then one of the performance measures used should be the hours of delay per capita. As part of the CMP, data for this performance measure and others would be collected and analyzed to determine whether or not adequate progress is being made in the region toward reaching the CMP objectives.

Characteristics of good performance measures

  • Relate to goals and objectives
  • Clearly communicate results to audiences
  • Include multiple modes of travel
  • Have consistency and accuracy
  • Illustrate the effect of improvements
  • Be applicable to existing and future conditions
  • Use person- or goods-movement terms
  • Allow for economical data collection or estimation
  • Developed collaboratively

Source: NCHRP Report 618, Cost Effective Performance Measures for Travel Time Delay, Variation, and Reliability, TRB, Washington, DC, 2008.

At the local level, performance measures are used to identify locations currently experiencing or anticipated to experience congestion problems in the future. They also are used to support assessment and selection of congestion mitigation strategies and evaluation of implemented strategies. The smaller scale application of performance measures in this context often means that the performance measures selected for monitoring system-level congestion and tracking regional objectives must be tailored to be applicable at a segment, link, or intersection scale.

A threshold or definition of "unacceptable congestion" may be developed for performance measures applied at a local level. For instance, the region may define excess delay as the average travel time in excess of a free flow travel time, and then identify road segments that exceed a certain threshold of delay as "congested". It is important for these local (e.g., segment, intersection) measures of congestion to be linked to regional performance measures so that measures used to pinpoint congestion problems and evaluate solutions have a connection to the attainment of regional objectives.

Performance Measures May Be Adapted and Adjusted Over Time

The action of developing performance measures is a highly iterative component of the CMP, and typically consists of three major activities:

Through the selection of the performance measures and identification of data needs, the MPO and its planning partners come to a greater understanding of the feasibility of objectives that have been developed. If the effort required to obtain the data to track specific objectives is deemed too great for the region, the MPO and its partners may revise the objectives so that they can be better tracked or they may identify surrogate performance measures that are thought to be strong indicators of the performance measures directly linked to the objectives. Each activity is described briefly below.

Selecting Multimodal Performance Measures

There are a wide range of measures that can be considered for use in the CMP. The following text describes several types of measures, addressing different components of congestion and aspects related to congestion that may be addressed in the CMP.

Components of Congestion. Traditionally in regional long-range transportation planning, MPOs have used volume-to-capacity (V/C) ratios or level of service (LOS) indicators as their primary metrics for analyzing existing and forecasted congestion on roadways and at intersections. However, there are several components of the concept of congestion that cannot be captured by V/C ratios and LOS.

The concept of congestion deals with the quality of use of the system as well as the quantity of use: in concept, "congestion" happens when there are too many people and/or vehicles at the same general place at the same general time, causing the user’s experience to decline in quality. Congestion also deals with two dimensions, spatial and temporal - the where (location, such as an intersection, roadway segment, or transit route) and the when (time of day or year). Further, there is a systemic aspect in that transportation facilities do not operate in isolation and actions that take place in one part of the transportation system can affect (positively or negatively) congestion on other nearby facilities. There is also a relative aspect in that observations of congestion may be qualitatively perceived as being more or less severe than observations at the same location at a different time, or at a different location.

Four major dimensions of congestion include the following:

Figure 3, from the Atlanta Regional Commission CMP, provides a graphical representation of some of these components of congestion, which are analyzed as part of their CMP process.

The four components of congestion discussed here are not, however, all-inclusive of the range of issues that could be considered in selecting performance measures for the CMP. A wide variety of potential CMP performance measures, including multimodal measures, are presented in the following text.

Figure 3. Three Dimensions of Congestion

Three Dimensions of Congestion. Click for more information.

Source: Atlanta Regional Commission, Congestion Management Process, 2006

Volume-to-Capacity-Based Measures. Measures relying on volume-to-capacity ratios traditionally have been used because: (a) data on traffic volumes are usually relatively easy to obtain and often already exist, (b) travel demand models are designed to estimate future volumes on the transportation network, and (c) estimates of capacity can be derived using documents such as the Highway Capacity Manual (HCM). LOS indicators with a simple standardized "A" through "F" grading system are sometimes assigned. Sometimes these measures are converted to travel time through a series of theoretical relationships, and derivative indicators that address travel time—such as excess delay—are sometimes calculated from volume-based measures. The advantage of these measures is that data are generally available from travel models, and there is a large existing body of experience in defining and applying these measures. On the other hand, they are limited in that they traditionally focused on the movement of vehicles, rather than people or goods (this is being addressed in part by the 2010 version of the HCM, which is in its final stage of development). Another limitation of volume-to-capacity measures is that they may not be readily understood by the public without a citizen education effort.

Travel Time Measures. Travel time measures focus on the time needed to travel along a selected portion of the transportation system. Common variations of travel time metrics include:

These measures can be translated, using various assumptions, into other measures such as user costs, and can be used in the process of validating travel demand forecasting models.

Variability of Congestion / Reliability. The variability or change in congestion on a day-to-day basis provides a measure of reliability. Recurring congestion is generally predicable, regularly occurring, and typically caused by excess demand compared to the capacity of the system. On the other hand, non-recurring congestion causes unreliable travel times and is caused by transient events such as traffic incidents, weather conditions, work zones, or special events. Non-recurring congestion, and unreliable travel times that result, are often the most frustrating form of congestion to travelers. Moreover, FHWA estimates that non-recurring sources of congestion are responsible for over half of all delay experienced by travelers.3 Since the transportation planning models used in metropolitan transportation planning are designed to address recurring congestion issues, many regions have found it challenging to incorporate measures of non-recurring congestion as part of their CMP. Some MPOs have used crash data as a surrogate measure for non-recurring congestion under the premise that traffic incidents are directly linked to non-recurring congestion. Others have begun to gather archived real-time traffic data from operating agencies to examine the variability in traffic volumes, speeds, and/or travel times on a daily basis.

Measures Addressing Transit System Congestion and/or Reliability. Transit performance measures provide information on the conditions experienced by transit travelers. Aspects of transit travel conditions include:

In most areas, passenger overcrowding is not a major transit issue, but schedule adherence is generally an important aspect of transit conditions. The Puget Sound Regional Council (PSRC), the MPO for the Seattle region, identified five performance measures to characterize the types of congestion relevant to transit operators:4

Measures Addressing Multimodal (Transit, Bicycle, Pedestrian Infrastructure) Availability. In many areas, MPOs are incorporating measures beyond those focused on the automobile to include multimodal options, such as buses, trains, pedestrians, bicycles, and ferries. The non-automobile transportation modes support the CMP by providing the potential to reduce highway congestion. These measures provide an indication of the extent to which travelers are able to choose an alternative mode of travel to single-occupancy vehicles. Measures include the extent of the bicycle, pedestrian, or transit network, and quality of the network or comfort to users. Measures may also include actual use of facilities, such as park-and-ride lots, buses, and bicycle lanes. For example, by measuring the total number of transit riders in a corridor, it is possible to identify corridors with high ridership, where improvements not only to transit service frequency but also physical improvements such as sidewalks to improve accessibility and signal pre-emption to improve transit service reliability would be most helpful.

Freight Performance Measures. Measures that focus on goods movement generally utilize other types of performance measures identified above, such as volume-to-capacity ratios or travel time measures, but focus on roadways with a high volume of trucks or designated freight corridors. The purpose of these measures is to highlight congestion that affects freight since consideration of solutions specifically-targeted to freight traffic issues may be needed.

Accessibility Measures. This broad set of measures describes the ability of the public to reach employment sites, retail centers, activity centers, and other land uses that produce or attract travel demand. Accessibility measures frame travel as a means to access desired goods, services, and activities that is affected by multiple factors, including proximity to places and mobility of people. Measuring accessibility can involve calculating the number or share of population that can access desired destinations within a specific amount of time and by different travel modes - e.g., percentage of the labor force with a commute of 30 minutes or less; percent of households within 40 minutes of downtown; or the percentage of employment in the region within a five-minute walk of transit service.

Land Use Measures. Land use and transportation are very closely connected, and these measures look at some of the ways in which this interconnection occurs. Among these are measures of the mix of land uses in a given area, and the pattern of development and how supportive it is of transit, bicycle, and pedestrian transportation - e.g., a connectivity index (based on how many intersections vs. dead ends are within a local street system) or a measure of the percentages of land used for different types of development (residential, commercial, mixed use, etc.) within a corridor or area.

Case Study: Performance Measure Selection at WILMAPCO

WILMAPCO uses three standard performance measures in its CMP every year, with an additional fourth performance measure that has varied over the years. The three standard measures are daily roadway volume-to-capacity ratio, peak-hour intersection level of service, and peak-hour observed speed as a percentage of posted speed. These measures were selected for several reasons, including the fact that they are user-friendly and relatively easy for the average citizen to understand. These measures also create a consistent scale of measurement that allows comparisons of data from year to year, and are all based on standard technically-defensible measures in common use around the country.

The fourth CMP performance measure, which has varied over time (including years when no fourth measure was included), has generally measured one of two things: crashes or transit usage. Crash rates have been the more prominent of these, and are intended to identify areas with higher-than-average instances of incident-caused non-recurring congestion. WILMAPCO worked with DelDOT to get their crash data in a format that would be usable for the CMP—DelDOT now provides an annual GIS file containing the point locations of all crashes within the state. WILMAPCO uses standards of two-times and three-times the average crash rate within the region to determine high crash locations for the CMP. For the other performance measure, transit load factors, there has been disagreement within the MPO over whether high transit load factors (indicating high transit usage, close to vehicle capacity) are indicative of a positive or negative outcome. After considerable debate, the MPO decided to focus on transit in the strategy identification phase of the CMP rather than trying to create a transit performance measure, while still collecting the necessary data on transit usage to make informed decisions about potential transit strategies.

Source: WILMAPCO, "2009 WILMAPCO Congestion Management System Summary," July 2009 www.wilmapco.org/cms

Table 1 highlights several examples of performance measures that can be considered at a local and regional scale.

Table 1. Examples of Performance Measures: Local and Regional
Type of Measure Sample Localized/Corridor-level Measures Sample Regional/System-level Measures

Congestion intensity: volume/capacity measures

  • Volume-to-capacity ratio (V/C), for segment
  • Level of Service (LOS), for a segment or intersection
  • Number or share of roadway miles operating at V/C ratio over 1.0
  • Number/share of roadway miles at LOS E or worse
  • Number of intersections at LOS E or worse

Congestion intensity: travel time measures

  • Travel speed (miles per hour)
  • Average delay time (the difference between travel time and acceptable or free-flow travel time)
  • Travel time index (ratio of peak-period to non-peak-period travel time)
  • Average regional commute time (by mode)
  • Total excess delay time (wasted travel time)
  • Share of roads experiencing travel time index over 2.0

Congestion duration

  • Hours of travel per day at V/C ratio over 1.0
  • Hours of travel per day at LOS E or worse
  • Number or share of roadway miles experiencing more than 3 hours of congestion per day on average

Congestion extent: vehicle measures

  • Number of vehicles experiencing LOS E or worse, for a segment
  • Number or share of vehicle miles traveled at LOS E or worse, regionally

Congestion extent: delay measures

  • Total delay on roadway (average delay time per vehicle x number of vehicles)
  • Total excess delay time (wasted travel time)

Reliability

  • Planning time index - ratio of 95th percentile travel time to free flow travel time
  • Buffer index - ratio of difference between 95th percentile travel time and average travel time, divided by average travel time
  • Crash rate by route or intersection
  • Number of incidents
  • Share of freeway segments with planning time index over a certain threshold
  • Average buffer index for commute trips
  • Crash rate regionally

Transit travel conditions

  • Transit crowding
  • Transit on-time performance (by route)
  • Percentage of buses/trains exceeding a certain crowding level.
  • Percentage of buses arriving on-time regionally

Availability or service level of modes

  • Existence of sidewalks
  • Existence of bicycle lanes or paths
  • Existence of pedestrian features (countdown pedestrian signals, painted crosswalks, etc.)
  • Existence of high-frequency bus services
  • Miles of sidewalks or share of roads with sidewalks regionally
  • Miles of bicycle lanes or paths or share of roads designated as bicycle routes regionally
  • Number of intersections with pedestrian features

Accessibility

  • Number of jobs/households within a defined distance or travel time from location
  • Share of regional jobs within ¾ mile of transit
  • Share of regional households within ¼ mile of transit

Land use

  • Jobs-housing balance (ratio) within area/zone
  • Jobs-housing balance (ratio) across each area

Congestion cost

  • Wasted fuel (gallons)
  • Wasted money (value of travel time, fuel, vehicle operating costs)
  • Wasted fuel (gallons)
  • Wasted money (value of travel time, fuel, vehicle operating costs)

Traveler information

  • Existence of variable message signs (or other traveler information) by route
  • Existence of "next bus" information by bus route
  • Share of freeways regionally with variable message signs
  • Share of bus stops regionally with "next bus" information

Incident duration

N/A (data not typically available for specific locations, with limited exceptions)

  • Mean time for responders to arrive on-scene after notification
  • Mean incident clearance time

Not all of these measures are appropriate for all MPOs in all situations. For more information on the appropriateness and benefits of different measures and on other potential performance measures, refer to the FHWA/FTA publication, Advancing Metropolitan Planning for Operations: The Building Blocks of a Model Transportation Plan Incorporating Operations - A Desk Reference (2010) and the National Transportation Operations Coalition (NTOC), Final Report of the Performance Measurement Initiative (2005).

Considerations in Selecting and Utilizing Performance Measures

In addition to considering different types of performance measures, MPOs should consider several issues in selecting and utilizing performance measures.

Use Multiple Performance Measures. Some MPOs have found it beneficial to include multiple performance measures within the CMP to capture various aspects of congestion, including both recurring and non-recurring congestion. Use of multiple performance measures also may be needed to capture congestion issues relevant to the multimodal transportation system, including transit, bicycling, and walking, and to address different congestion objectives that may be developed for the region. Results of several measures could be combined into a single index for purposes of identifying the most congested roadways, or multiple measures may be used to address different aspects of congestion that may warrant different solutions.

For instance, the Mid-Region Council of Governments in Albuquerque, New Mexico, utilizes three measures of congestion: volume to capacity ratio, speed, and crash rate. Together, these three measures are indexed and combined into a corridor score, which is used to rank roadways in terms of congestion priority.5 The result is that the agency is able to map its CMP network and portray the performance of each network link according to the score in order to prioritize investments. The Boston Region MPO includes a range of performance measures in its CMP, including roadway travel time measures (average observed travel speeds, travel speed index, delay), transit on-time performance, transit passenger crowding, park-and-ride lot utilization, time that park-and-ride lots fill up, HOV lane performance measures, utilization of TDM program services (ridematching, vanpools, and suburban transit shuttles), and bicycle parking availability and utilization at transit stations, among others.6

At the same time that it is valuable to utilize multiple performance measures, it is advisable to keep the total number of measures manageable, in order to: (a) reduce data collection costs, (b) reduce complexity, and (c) improve the ease of understanding by officials and the public.

Focus on Persons and Goods, Rather than Vehicles. Traditionally, performance measures in the CMP have focused on traffic congestion, which is not surprising since traffic congestion is often a key issue of concern to the public and elected officials. However, even in looking at measures of traffic congestion, it is useful to consider performance measures that focus on people and goods movement, rather than simply on the movement of vehicles.

Vehicle-based measures, such as vehicle hours of delay, focus on the experience of individual vehicles or the cumulative experience of many vehicles. In contrast, person travel-based measures, such as person hours of delay or person travel time, may lead to selection of different types of strategies. For instance, a measure focusing on personal travel time may lead to strategies such as bus rapid transit and transit signal priority, which increase the speeds of buses carrying multiple passengers. A vehicle-based measure would not show the same benefit to these types of strategies, since all vehicles, regardless of occupancy, are treated equally.

Use Screening Measures, with Additional Measures for Identified Congested Locations. Some areas have found it helpful to use one measure, such as volume-to-capacity ratio, as a screening measure to identify congested corridors, and then apply additional performance measures only to those congested corridors. This approach allows agencies to focus scarce resources directly on the areas that benefit most from more in-depth analysis, while also providing coverage for the entire system. One example of this approach is undertaken by the Hillsborough County MPO, covering the Tampa, Florida area. The Hillsborough County MPO has developed a tiered structure for performance measures that is intended to monitor the transportation system effectively while expending monitoring resources strategically. The program measures performance system-wide and by corridor using a set of primary performance measures; corridor-specific measures include basic performance measures for roadway (volume-to-capacity), transit (ridership and frequency), bicycle (extent of corridor with bicycle facilities), and pedestrian travel (extent of corridor with sidewalks). For identified congested corridors, a more in-depth set of measures is tracked, drawing on data such as travel time surveys, pedestrian counts, employer rideshare programs, and transit on-time performance.7

Define Different Levels of Performance that are Acceptable in Different Circumstances. Different thresholds can be used to define congestion, based on location, facility type, and/or time frame. This option recognizes that the public may find different levels of congestion acceptable based on these parameters. Clearly an arterial might be expected to experience slower travel speeds than a limited-access freeway. On a high occupancy vehicle (HOV) facility, a travel speed less than 50 or 60 miles per hour or LOS C or higher might be considered unacceptable congestion, while these conditions may be more acceptable in the adjacent general purpose freeway lanes.

Facility location may also influence expectations; a central business district might be expected to experience slower travel speeds than an outlying suburban area. Differentiating between location types also recognizes that eradicating congestion may not be the sole community goal in all areas; higher levels of traffic congestion may be acceptable, for instance, in downtown areas with high levels of transit service and high-quality pedestrian environments. Lastly, although transportation planning processes often focus on weekday commute periods when examining congestion, there may be other periods of interest, such as weekend periods or specific seasons that are associated with heavy shopping or recreational travel. There may be different thresholds for performance during different periods in order to adequately capture the traffic congestion problems that are of concern to the public.

Consider Use in Communicating Information. An additional role of the performance measures selected for the CMP is to communicate to decision-makers, the public, and MPO member agencies about system performance, the progress being made, and the impact of proposed mitigation strategies. When developing performance measures for the CMP, it is important to keep in mind the role of performance measures in communications. It is useful to focus on aspects of system performance that matter most to the public so that MPOs and their member agencies can communicate effectively with the public, demonstrate accountability and transparency, and get the public’s support for transportation programs. See Section 4 on ‘Using Visualization as a Communication and Analysis Tool’ for information on visualization techniques that can be helpful in communicating performance measures and other CMP data. It is also important to remember that beneficiaries of the performance measure analysis are the MPOs themselves; performance measures should be selected such that they will be useful to the decision making of the MPO, for example by guiding decision-makers to prioritize and implement certain strategies recommended in the CMP.

Developing a Data Collection and Management Plan

An integral part of developing performance measures is creating a plan for collecting the data needed to support those measures. The plan should describe what data is needed to support the performance measures, where data will be collected, how often it will be collected, and by whom. Additionally the plan should include agreed-upon accuracy levels and data formats so that system-wide or regional statistics can be developed based on the data collected. This is particularly important when several different entities are collecting data to support the same performance measure. Close collaboration between transportation facility owners/operators and transportation planners is needed to develop a comprehensive data collection plan for the region’s CMP. Often, the MPO is not the primary data collection organization. Rather, operating agencies often collect data for their own purposes that may be transformed and shared with the MPO for the CMP. For example, the Capitol Region Council of Governments (CRCOG) in Hartford, Connecticut receives its freeway performance data for the CMP from the Connecticut Department of Transportation.8 The regional ITS architecture may be an important resource for identifying sources of data in the region that can support the CMP’s performance measures.

Refining Objectives and Performance Measures

During the selection of performance measures and identification of data needs, regions may need to reconsider the objectives and/or performance measures that they selected because of data availability. The development of a data plan serves as a "reality check" for the objectives and performance measures selected for the CMP. In this activity, the MPO and its planning partners must balance the need to work toward objectives that are tied to performance measures and communicate important aspects of multimodal system performance with the use of objectives that can be tracked using available or easily-collected data.

For example, the objective "Reduce non-recurring delay on freeways and regionally significant arterials by 10% over the next 5 years" describes an aspect of congestion that the public cares about: non-recurring delay. Unfortunately, non-recurring delay is often difficult to measure using typical transportation data sources. If a region that selected this objective does not have data available on non-recurring delay, the region may either try to modify the objective so that it can be measured or it may develop surrogate measures that are thought to directly contribute to the primary measure. Surrogate measures for non-recurring delay may include incident clearance time or work zone queue length.

Upon revising the objectives and performance measures based on resource availability, the data collection plan should be updated to reflect the latest measures.

2.4 - Action 4: Collect Data / Monitor System Performance

Gathering data to monitor system performance is typically the element of the CMP that requires the largest amount of resources and staff time for the MPO and its planning partners. After establishing performance measures that will be used to evaluate system performance and a plan for collecting data, regions are ready to gather the data necessary to inform the CMP. In-depth case studies of the CMP at several MPOs developed in association with this guidebook provide detailed information on the different approaches used for data collection and monitoring (available on-line at http://www.fhwa.dot.gov/planning/).

Common Types of Data and Collection Techniques

There are many types of data that can be used as part of the CMP process. Data types are often differentiated or categorized according to the source or underlying nature of the data. The following list is not exhaustive, but includes several common types of data that are used in the CMP by MPOs.

How does the transportation system perform?

Data collection and system monitoring are needed to provide information to make effective decisions, and are typically an on-going activity. According to Federal regulation, the CMP must include "Establishment of a coordinated program for data collection and system performance monitoring to define the extent and duration of congestion, to contribute in determining the causes of congestion, and evaluate the efficiency and effectiveness of implemented actions. To the extent possible, this data collection program should be coordinated with existing data sources (including archived operational/ITS data) and coordinated with operations managers in the metropolitan area;"

23 CFR 450.320 (c) 3

MPOs approach obtaining data for the CMP in several ways depending on a number of factors. MPOs may use their own staff to collect system performance data on a routine basis or may focus on coordinating and compiling data collected by others. Many regions use a combination of techniques to acquire data including hiring consultants to collect data and purchasing data from private data vendors in addition to staff collection efforts. Travel demand model data is widely used to allow comparison of base and future year conditions. The techniques used to acquire system data for the CMP will depend largely on the availability of MPO staff time and equipment, cost, and the ability to partner with others.

Collaboration for Data Collection

Although some MPOs are able to collect data needed for the CMP using in-house staff, collaboration to support data collection and analysis is essential. Collaboration with many partners including state, regional, and local transportation facility owners and operators is a significant opportunity to leverage and tailor existing data collection efforts for the purpose of the CMP, thereby reducing the burden on the MPO. This is particularly true of multimodal data that may be available from transit agencies, bicycle groups, or local governments. Some specific opportunities are noted in the following text.

Case Study: Data Collection at the Southwestern Pennsylvania Commission (SPC) and the Puget Sound Regional Council (PSRC)

SPC collects data on travel time, speed, and delay on a three-year cycle, using in-house staff and equipment. Each year within the cycle is divided into two data collection seasons (spring and fall), creating a total of six seasons over which to spread the entire effort. Travel time, speed, and delay information is collected by GPS through travel time runs along each corridor. Multiple runs are conducted in each direction along each corridor for both the AM and PM peak periods. In total, the level of effort required for this data collection is equal to approximately 1.5 full-time employees during the spring and fall data collection periods.

Alternatively, PSRC primarily uses data collected by member agencies. It generally views its role as the collator, coordinator, and analyzer of data collected by agencies across the region rather than data collector. Collecting data on system performance is viewed to be more the responsibility of the facility owners and operators. This role as data collator may also be the result of the large and complex region that PSRC serves and the relatively advanced data collection efforts undertaken by member agencies such as the Washington State DOT. According to PSRC staff, there are many local transportation agencies in the region that are also collecting data and PSRC is working with the agencies to coordinate and harness these somewhat disparate resources. Another reason why PSRC turns to its member agencies for CMP data is the highly multimodal nature of its CMP. PSRC's CMP covers the roadway, ferry, transit, bicycle/pedestrian, freight, and rail systems. Collaboration with a variety of agencies is necessary to obtain information across so many different modes.

Sources: SPC, Congestion Management Process, 2005, www.spcregion.org/trans_cong.shtml
PSRC, "Draft SMART Corridors/CMP Report," Feb. 2010, www.psrc.org/transportation/cmp/

Transit Agencies. There are significant opportunities in many regions to improve the overall understanding of congestion on the multimodal transportation system through the use of data collected by transit agencies. This data can not only help to provide a better picture of congestion experienced on the transit system but also on arterials and other roadways where buses travel. Obtaining data on arterial travel time is particularly important as data on arterial congestion is often missing from other CMP data sources. Frequently, State DOTs will instrument freeways in urbanized areas with some type of automated traffic detection devices to better manage traffic and collect performance data but far less often are arterials instrumented for data collection. As more and more buses become equipped with automatic vehicle location (AVL) systems, regions can use AVL data from transit agencies to help identify congestion on arterials. AVL data can also be used to monitor transit service measures such as on-time performance. Several MPOs are beginning to use AVL data as part of the CMP. For instance, the Pioneer Valley Planning Commission in Springfield, Massachusetts notes in its CMP that the Pioneer Valley Transit Authority (PVTA) is implementing AVL to accurately track bus and vehicle locations and provide on-time performance information to riders, and these data will be incorporated into the CMP as they become available.9 The Hampton Roads Transportation Planning Organization in Norfolk, Virginia similarly notes the potential use of AVL data from express transit buses.10

Operations Agencies. Another opportunity for obtaining system performance data to support the CMP is in the use of archived operations data from ITS applications, including those being operated by State DOTs and toll authorities. Data on transportation system performance, such as travel speeds, volumes, and raw video images of roadways, is collected by State DOTs and other operating agencies using cameras and loop detectors for the purpose of managing traffic in real-time often from a transportation management center. When State DOTs or other agencies archive data, it has the potential to be useful for planning. Archived operations data typically must undergo some type of re-formatting and processing so that it can be used for planning purposes in the CMP.

One example of this is in the Atlanta, Georgia metropolitan region where the Georgia Regional Transportation Authority (GRTA) obtains traffic volume and speed data from the Georgia DOT. The Georgia DOT uses NAVIGATOR, an intelligent transportation system deployed on the region’s roadways to manage traffic in real-time but also to archive the data. The volume and speed data are derived from camera images sent back to the Georgia DOT transportation management center from closed-circuit television cameras installed on State roads. Each year, GRTA conducts an intensive data processing effort to transform the archived data into information that can be shared through a report titled the "Transportation Metropolitan Atlanta Performance Report" or Transportation MAP Report. The report includes maps of the region displaying the freeway travel time index, freeway planning time index, and freeway buffer time index all calculated using archived data from Georgia NAVIGATOR.11

Operations data may be particularly important for mid-sized MPOs that do not have significant traffic congestion problems and may want to focus the CMP on reliability measures. As an example, the Capital District Transportation Committee (CDTC) in Albany, NY utilized data from the New York State DOT’s ITS system called MIST - Management Information System for Transportation. The data set covered an entire year of data for 2003, and was used to identify both recurring and non-recurring delay on major expressways (I-87, I-90, I-787, and Alternate Route 7).12

2.5 - Action 5: Analyze Congestion Problems and Needs

Once collected, raw data must be translated into meaningful measures of performance. The purpose of this action is to identify specific locations with congestion problems, and to identify the sources of these problems. The complexity of translating data into meaningful information for analysis varies with the complexity of the multimodal performance measures and data sources chosen. When data has been provided by another source (secondary data) it may have a primary use that is quite different than what is needed for the CMP. In addition, the data may represent something entirely new to the staff assigned to perform the analysis or translation. One example is the use of ITS data. ITS sensor data is collected continuously and represents a large volume of data that must be collapsed into some form that provides useful information. While this type of data can be extremely helpful to MPOs in understanding reliability issues and sources of delay, considerable effort may be needed to convert the data into a useful format for planning purposes.

The technologies needed to analyze certain types of data may be unavailable or unfamiliar to the MPO staff, creating logistical difficulties. Micro-simulation analysis is one tool that can be very effective at identifying the potential causes of congestion in corridors or segments of a road; however, it requires a great deal of detailed data to be truly illustrative of the existing condition and is not often available to MPO technical staff. Partnerships with state DOT operations staff and research institutions can greatly assist the MPO in incorporating this data into the CMP.

A strong interest in using operations data and strategies, in addition to support at the federal level, has led to the use of new techniques in many regions. The use of visualization is one example that can be used at many levels of sophistication for several uses: from communicating to the public and decision-makers to helping technical staff analyze strategies for congestion mitigation. Other innovative analysis methodologies are becoming more widely used with supporting training and technical assistance. Several examples are available on the FHWA Office of Operations website (http://www.ops.fhwa.dot.gov/trafficanalysistools/index.htm).

Case Study: Data Analysis at the Southwestern Pennsylvania Commission (SPC)

After the completion of a full season of data collection, the CMP planner at SPC spends about one week analyzing the data with regard to the performance measures that SPC has chosen to use. The primary performance measures are travel time, speed, and delay, but these are further broken into seven more specific measures. Each of these performance measures is calculated for a daily, AM, and PM value. The intention of measuring time, speed, and delay in several different ways is to ensure that different types of congestion are all addressed by the process.

As part of the analysis, SPC does not set a specific threshold defining an acceptable level of congestion. However, the analysis does result in regional rankings of the level of congestion in each corridor. Rankings of the corridors are created for each of the seven performance measures, and are broken out by functional classification so different types of roadways that are not comparable are ranked separately. These rankings are used to inform the prioritization of congestion management projects and to identify areas where local governments should be encouraged to implement congestion management improvements.

Source: SPC, Congestion Management Process, 2005, www.spcregion.org/trans_cong.shtml

There are several issues that MPOs should take into account when analyzing data for the purpose of defining or locating congestion problems, including:

Once data has been translated to allow comparisons between the various levels of congestion in the region, the MPO must begin to apply the definitions of unacceptable congestion considered in Action 2 to individual sections of the system. The result may be any of the following:

Case Study: Identification of Causes of Congestion, Puget Sound Regional Council (PSRC)

PSRC looks to its member agencies to identify the causes of congestion through route development and corridor studies. These studies have been completed on almost every major facility in the region. PSRC "rolls-up" the information on congestion causes identified by the member agencies, and uses the information as an input to discussions on the development and evaluation of congestion management strategies.

Source: PSRC, "Draft SMART Corridors/CMP Report," Feb. 2010, www.psrc.org/transportation/cmp/

Often, specific benchmarks or targets are used to analyze data on either a corridor or regional level, to determine how well (or poorly) the system meets the desired conditions. More advanced analytical methods, such as detailed traffic modeling, could also be used to accomplish this action.

In order to understand which congestion mitigation strategies are appropriate within the context of a specific congested corridor (or within a subarea or region), it is also necessary to understand the causes of congestion. In some MPOs, formal technical analysis may be conducted to complete this step. In others, congestion sources may be determined based on local knowledge, group consensus, or field notes. This also marks an appropriate point for comparison of recurring and non-recurring congestion issues. This step serves as an essential bridge between the collection of system performance data (Action 4) and the potential solutions to address the identified deficiencies (Action 6).

2.6 - Action 6: Identify and Assess CMP Strategies

The identification and assessment of appropriate congestion mitigation strategies is a key component of the CMP. At this point, the MPO turns the data and analysis (of Actions 4 and 5) into a set of recommended solutions to effectively manage congestion and achieve congestion management objectives. The identification of strategies requires several important considerations:

Contribution to Meeting Regional Congestion Management Objectives- Strategies that are selected should support the congestion management objectives that have been agreed-upon for the region (in Action 1). If policy-oriented congestion management principles have been established, these strategies should also take into account these principles in prioritizing the types of strategies that will be considered. Some areas have made specific policy decisions to prioritize demand management strategies first, followed by system management and operations strategies, and only build new capacity as a last resort if other approaches are not sufficient.

Local Context- Community context and public involvement should play an important role in determining the types of strategies that are appropriate for a specific corridor, facility, or intersection. Strategies should fit into the context of the community and should be appropriate in regard to the role of the transportation facilities within the regional network (e.g., whether it is a freight corridor, economic development corridor, major commuter route, etc.). For example, in urban centers (high density, mixed use places, typically with well-connected street networks, high levels of transit service, and pedestrian supportive environments), the strategies implemented to address traffic congestion will differ from the strategies to be applied in suburban communities (typically characterized by a limited mix of housing, employment, and commercial services, limited connections in street networks, and large amounts of surface parking). Similarly, the strategies to address freeway congestion on an urban interstate accessing a downtown or major suburban jobs center will likely differ from strategies that would be appropriate for a corridor that does not serve as much commuter traffic.

What strategies could aid in congestion management?

23 CFR 450.320 (c) 4 states that the CMP shall include: "Identification and evaluation of the anticipated performance and expected benefits of appropriate congestion management strategies that will contribute to the more effective use and improved safety of existing and future transportation systems based on the established performance measures. The following categories of strategies, or combinations of strategies, are some examples of what should be appropriately considered for each area:

  1. Demand management measures, including growth management and congestion pricing;
  2. Traffic operational improvements;
  3. Public transportation improvements;
  4. ITS technologies as related to the regional ITS architecture; and
  5. Where necessary, additional system capacity."

Contribution to Other Goals and Objectives - In addition to focusing on the operational performance of the transportation system, it is important to consider strategies in the context of multiple goals and objectives for the region. These other considerations will likely include issues such as safety, economic vitality, system preservation, and air quality.

Jurisdiction over CMP Strategies - The MPO charged with implementing the CMP will typically rely on the actions of other governmental partners in implementing strategies, including State DOTs, transit agencies, and local jurisdictions. In particular, land use strategies are often a challenge given local authority over land use planning. Coordination and collaboration among multiple agencies is critical to an effective CMP. Consequently, the MPO will need to coordinate with potential partners by framing desirable strategy types and defining roles in implementation.

Identifying Congestion Management Strategies

A wide range of strategies are available and can be broadly grouped into the following categories.

Demand Management Strategies. Travel Demand Management (TDM), nonautomotive travel modes, and land use management can all help to provide travelers with more options and reduce the number of vehicles or trips during congested periods. These include strategies that substitute communication for travel, or encourage regional cooperation to change development patterns and/or reduce sprawl.

Promoting Alternatives

Managing and Pricing Assets

Work Patterns

Land Uses

Traffic Operations Strategies. These strategies focus on getting more out of what we have. Rather than building new infrastructure, many transportation agencies have embraced strategies that deal with operation of the existing network of roads. Many of these operations-based strategies are supported by the use of enhanced technologies or Intelligent Transportation Systems (ITS).

Highway/Freeway Operations

Arterial and Local Roads Operations

Other Operations Strategies

Public Transportation Strategies. Improving transit operations, improving access to transit, and expanding transit service can help reduce the number of vehicles on the road by making transit more attractive or accessible. These strategies may be closely linked to strategies in the previous two categories (demand management and traffic operations). As with traffic operations, transit operations are often enhanced by ITS

Operations Strategies

Capacity Strategies

Accessibility Strategies

Road Capacity Strategies. This category of strategies addresses adding more base capacity to the road network, such as adding additional lanes and building new highways, as well as redesigning specific bottlenecks (such as interchanges and intersections) to increase their capacity. Given the expense and possible adverse environmental impacts of new single-occupant vehicle capacity, management and operations strategies should be given due consideration before additional capacity is considered.

Some MPOs have developed a "toolbox" of strategies for consideration by local governments that are implementing projects. For example, the New York Metropolitan Transportation Council (NYMTC) has a CMP toolbox that identifies strategies in nine categories: highway, transit, bicycle and pedestrian, travel demand management, Intelligent Transportation Systems and transportation supply management, access management, land use, parking, and regulatory strategies. It highlights congestion and mobility benefits and costs and impacts of each strategy.13 The Grand Valley Metro Council in Grand Rapids, Michigan refers to its approach as a "Cafeteria Plan," which also identifies a list of strategies along with their benefits.14 Some areas have also developed a hierarchy of strategies, drawing on policy goals or principles (e.g., they may seek to prioritize demand management and operations strategies above capacity additions).

Assessing Congestion Management Strategies

Techniques for evaluating and selecting strategies include the use of committees or group consensus, the refinement of standard "seed" strategies based on local characteristics, and staff-level technical analysis. Information collected through monitoring of implemented strategies can be most helpful in evaluating the success of individual strategies and targeting specific strategies to applications where they have demonstrated success. This feedback loop provides a continuous refinement of the strategies considered for congestion management in different situations.

Some examples of tools and methods for assessing the potential effectiveness of congestion management strategies include the following:

For more information on potential analysis tools, see FHWA, Applying Analysis Tools in Planning for Operations, FHWA-HOP-10-001 (Washington, DC) and "Traffic Analysis Tools, Types of Traffic Analysis Tools", available at http://ops.fhwa.dot.gov/trafficanalysistools.

Often, more detailed analysis of potential strategies occurs within corridor studies or project-level studies (described further in Action 7).

2.7 - Action 7: Program and Implement CMP Strategies

Implementation of CMP strategies occurs on three levels: system or regional, corridor, and project.

How will congestion management strategies be implemented?

Action 7 is critical for turning the strategy recommendations of the CMP into on-the-ground implemented projects. Federal regulations require that the CMP include: "Identification of an implementation schedule, implementation responsibilities, and possible funding sources for each strategy (or combination of strategies) proposed for implementation."

23 CFR 450.320 (c) 5

Regional-level implementation of congestion management strategies occurs through inclusion of strategies in the fiscally-constrained MTP and the TIP. At the corridor level, more specific strategies such as bicycle and pedestrian improvements and operational improvements can be assessed in studies and implemented using a variety of funding sources, including Federal funding streams such as the Surface Transportation Program (STP), National Highway System (NHS) funds, and the Congestion Mitigation and Air Quality Improvement (CMAQ) Program, as well as through state or local funding or other discretionary funding sources. For larger projects, particularly capacity-adding projects, demand management and operational strategies should also be analyzed for incorporation into the project as part of the project development process.

This tiered approach to strategy implementation integrates the CMP into all aspects of MPO planning and allows a flexible and robust incorporation of congestion management. It also introduces the consideration of scale. Some MPOs are actively engaged in efforts to integrate transportation planning into the NEPA decision-making process, and one of the notable barriers is the difference in scale between regional analysis and project analysis. The CMP offers one way to bridge that gap by translating system-level understanding to inform project-level decisions.

Regional Prioritization of Strategies

There are several ways to integrate the CMP analysis into regional prioritization of strategies:

Use the CMP in criteria for prioritizing projects in the MTP and/or TIP - The process of prioritizing projects for inclusion in the MTP and/or TIP might include a scoring element that gives weight to the relative congestion on that corridor based on the CMP data. In a formal scoring process, points could be allotted based on a number of factors, including the potential for the project to address and manage congestion. Scoring systems could treat projects differently based on location or strategy type according to congestion levels, or community goals. For instance, more points might be allotted to projects in very congested locations, or, specifically to certain types of projects in the urban core than to projects in areas where further development is not desired.

As an example, the Ohio-Kentucky-Indiana Regional Council of Governments (OKI) in Cincinnati developed a scoring process for selecting worthy highway and transit projects in its MTP. The process ranks projects using several transportation and planning factors, including existing level of congestion and projected impact on congestion, which are added together for a maximum of 100 points. Both the model V/C data and observed delay data were mapped and placed into three congestion categories: None or Low, Medium, and High. All projects under consideration for the MTP were located on the maps and given points corresponding to the congestion category of the roadway they impacted. Projects in the None or Low category were given zero points, Medium projects scored three points and projects in the High congestion locations scored five points.15 Other areas use similar scoring procedures for prioritizing projects for the TIP; one example is the Wilmington Area Planning Council in Delaware (see text box).

Case Study: Project Prioritization at the Wilmington Area Planning Council (WILMAPCO)

WILMAPCO has a mathematical process for assigning scores to proposed projects, which is used to develop a prioritized list of projects for funding. The score is divided among many different policy areas and goals (based on the goals of the long-range plan), with congestion management making up the largest single share of the score (28%). The congestion management score is based entirely on the CMP, with points awarded to projects that are located within CMP corridors (after checking that the type of improvement proposed is consistent with the strategies outlined in the CMP). Additional points are awarded to projects based on the trip volumes in the project corridor (both roadway and transit volume), as a way to give additional weight to major corridors where congestion mitigation is likely to have a greater public benefit. The final scoring/ranking of projects based on these criteria is then applied to the overall project prioritization scoring process, and the results are documented in the CMP report.

Source: WILMAPCO, "2009 WILMAPCO Congestion Management System Summary," July 2009 www.wilmapco.org/cms

Some MPOs feel that a quantitative scoring of congestion as part of project prioritization is not appropriate to their situation, given the wide range of qualitative factors, such as quality of life and livability, that need to be considered in making project investment decisions. These MPOs typically use information from the CMP along with other data to make decisions using a more qualitative process of balancing various objectives. An MPO may also specify that roadway capacity projects will not be funded unless the project emerges from the CMP as having a critical congestion problem.

Explicitly set aside funding for congestion management projects- An MPO can establish a program designed to fund relatively small congestion management projects. The CMP can be used to define criteria for rapid allocation of funds to solve straightforward congestion problems. This can be useful not only for improving mobility, but also for elevating the MPO’s visibility among stakeholders that are primarily interested in short-term implementation, such as freight shippers and developers. It may be useful to identify geographic areas of need based on congestion data, in which projects would then be eligible for funding under such a program. This approach may be useful in larger areas with numerous large projects competing for transportation funding, where smaller projects may have difficulty competing on their own, and in areas where quick-response projects may arise in between regular TIP cycles. For example, METROPLAN Orlando, the MPO in Orlando, Florida, has set aside funding for quick-response operational improvements.16 Miami-Dade MPO in Miami, Florida, is expanding an earlier set-aside program to take a more comprehensive, corridor-wide approach to funding congestion management improvements, better integrating them with one another and the MTP. Such projects will have a set-aside fund as of the 2015 TIP, and in the meantime the agency will conduct CMP improvement studies on congested corridors in preparation for design work and seek alternative funding for more immediate implementation.17

Corridor and Project Studies

In many cases, specific congestion management strategies may be identified through more detailed corridor studies and project development efforts. Some MPOs, such as the Delaware Valley Regional Planning Commission in the Philadelphia area, have required that any capacity-adding project be accompanied by congestion reducing strategies to improve the long-term effectiveness of the improvement. Because projects are most often implemented by agencies other than the MPO, this requires oversight by the MPO staff or a system to relay information on the effectiveness of associated strategies. Such information is crucial to achieving the full realization of the CMP as a continuous process. This step also represents the point at which consistency between planned/programmed projects and the CMP should be ensured, particularly for projects that will add capacity to roadways. Collaboration with partners at implementing agencies is a critical element of this step.

As projects are advanced to project development and environmental review, the CMP offers an opportunity to link planning and the NEPA process. This process can sometimes break down if project developers and designers are not aware of the CMP’s congestion management objectives or the range of performance measures that are being used regionally to monitor performance. The link between NEPA and the CMP is discussed in more detail in section 3.4.

2.8 - Action 8: Evaluate Strategy Effectiveness

Evaluation of strategy effectiveness can be seen as either a sequential step within the CMP process or as an on-going process. This is an essential, required element of the CMP that is often overlooked. The primary goal of this Action is to ensure that implemented strategies are effective at addressing congestion as intended, and to make changes based on the findings as necessary. Two general approaches are used for this type of analysis:

  1. System-level performance evaluation - Regional analysis of historical trends to identify improvement or degradation in system performance, in relation to objectives; and
  2. Strategy effectiveness evaluation - Project-level or program-level analysis of conditions before and after the implementation of a congestion mitigation effort.

Findings that show improvement in congested conditions due to specific implemented strategies can be used to encourage further implementation of these strategies, while negative findings may be useful for discouraging or downplaying the effectiveness of similar strategies in similar situations. The information learned from evaluation should be used to inform the TIP and MTP, as well as other steps within the CMP, notably the identification and assessment of strategies (Action 6).

How effectively have implemented strategies achieved congestion management objectives?

23 CFR 450.320 (c) 6 requires that the CMP include: "Implementation of a process for periodic assessment of the effectiveness of implemented strategies, in terms of the area's established performance measures. The results of this evaluation shall be provided to decisionmakers and the public to provide guidance on selection of effective strategies for future implementation."

One approach to evaluation is for the MPO to fund studies to measure the effectiveness of particular congestion strategies or projects by examining conditions before and after, or with and without, a strategy of interest. For instance, a study could be conducted to quantify vehicle-miles-traveled (VMT) reductions or mode shifts of a transportation demand management (TDM) program, to quantify the speed improvements associated with traffic flow improvement projects, to examine the reduction in vehicle delay associated with operational strategies, or other similar types of impacts. An example is the effort of the National Capital Region Transportation Planning Board (TPB) in the Washington, DC region to quantify the effectiveness of its Commuter Connections TDM program. TPB conducts a regional "State of the Commute" survey, along with additional surveys such as a Guaranteed Ride Home Program survey and tracking of participation rates in programs, in order to analyze the vehicle travel reductions and air quality improvements associated with the program.18 The North Central Texas Council of Governments (NCTCOG), the MPO for the Dallas-Ft. Worth area, has conducted evaluations of its Thoroughfare Assessment Program, which involves retiming traffic signals on major corridors. The results demonstrate reductions in travel delay and emissions.19

Another approach is for the MPO to develop guidance for evaluating strategies, and require local project sponsors to conduct evaluations of their projects and programs. Guidance can be provided on when an assessment should be done, what measures should be used, how data should be gathered, what methods should be used to analyze the data, and other aspects of evaluation studies. This approach is appropriate where partner agencies are responsible for implementation of CMP strategies, or where the MPO does not currently have sufficient resources to conduct studies. The East-West Gateway Coordinating Council (EWGCC) in St. Louis, Missouri, provides guidance to localities on when focused evaluations of strategy effectiveness are warranted, and how to conduct them. For example, if little is known about the actual benefits of the project, effectiveness evaluation can determine whether such strategies should be implemented more broadly (e.g., a trip reduction program that has not previously been used in the region), or if changes are required in the implementation of the strategy to produce the desired benefits.20


2 CDTC, "The Metropolitan Congestion Management Process," May 2007, www.cdtcmpo.org

3 FHWA, "Traffic Congestion and Reliability: Linking Solutions to Problems" p. ES-6. Sources of congestion were estimated as rough approximations based on many congestion research studies. http://ops.fhwa.dot.gov/congestion_report_04/congestion_report.pdf

4 PSRC, "Draft SMART Corridors/CMP Report," Feb. 2010, www.psrc.org/transportation/cmp/

5 Mid-Region Council of Governments, "2008 Corridor Rankings," 2009, www.mrcog-nm.gov

6 Central Transportation Planning Staff, "Mobility in the Boston Region," Dec. 2004, www.ctps.org/bostonmpo

7 Hillsborough County MPO, "Hillsborough County Congestion Management Process Definitions and Guidelines," Mar. 2008, www.hillsboroughmpo.org

8 CRCOG, Central Connecticut Regional Planning Agency, and Midstate Regional Planning Agency, "Transportation Monitoring & Management Report: Metropolitan Hartford Area: 2005," Dec. 2007, www.crcog.org

9 Congestion Management Process for the Pioneer Valley, Pioneer Valley Planning Commission, 2010. http://www.pvpc.org/resources/transport/Final%20CMP%20report_July2010_web.pdf

10 Statewide Opportunities for Integrating Operations, Safety and Multimodal Planning: A Reference Manual, FHWA 2010. http://www.fhwa.dot.gov/planning/processes/statewide/practices/manual/manual04.cfm

11 GRTA, "2009 Transportation Metropolitan Atlanta Performance Report," 2009, www.grta.org

12 CDTC, "The Metropolitan Congestion Management Process," May 2007, www.cdtcmpo.org

13 New York Metropolitan Transportation Council, "CMP Toolbox," http://www.nymtc.org/project/CMS/2009_CMP_files/CMP%20Toolbox.pdf.

14 Grand Valley Metro Council, Congestion Management Process, January 2009. http://www.gvmc.org/transportation/documents/GVMC%20CMP%20Document%202009%20Update%20Updated%205~2010.pdf

15 Telephone interview with Andy Reser, OKI Regional Council of Governments, January 2010

16 Telephone interview with Eric Hill, Metroplan Orlando, January 2010

17 Conversation with Jesus Guerra, Miami-Dade MPO, October 1, 2010.

18 See for example TPB and MWCOG, "2007 State of the Commute Survey Report," June 2008, www.mwcog.org

19 See for example Kimley-Horn and Associates for NCTCOG, "Thoroughfare Assessment Program Phase 2.0," July 2009, www.nctcog.org/trans/tsm

20 EWGCC, "St. Louis Region CMS Congestion Mitigation Handbook," February 1998, http://www.ewgateway.org/pdffiles/library/trans/cmshandbook.pdf

Updated: 05/23/2012
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