Table of contents

Introduction

The 2050 Transportation Policy Plan uses a performance-based approach to measure success in meeting the region’s transportation goals and objectives. This chapter describes the performance measures the Metropolitan Council will use to monitor and evaluate this plan’s effectiveness.

The Met Council and its regional partners have selected performance measures that are clear, measurable, and closely tied to the plan’s goals and objectives. The measures will indicate where the region is meeting its goals and objectives and what areas require greater emphasis and resources.  

The 2050 Transportation Performance Plan performance measures fall into one of two main categories:

• Required federal performance measures that are tracked and must be reported about on a regular basis. As the region’s Metropolitan Planning Organization, the Met Council is required to set short-term performance targets for these measures. The results of these measures are primarily concerned with the overall short-term trend and whether this trend is meeting the desired expectations.  
• Regional performance measures that the Met Council tracks to evaluate the region’s progress towards its goals and objectives. 

Regional performance measures are organized by the plan’s goals and objectives:

• Our region is equitable and inclusive
• Our communities are healthy and safe
• Our region is dynamic and resilient
• We lead on addressing climate change
• We protect and restore natural systems  

Each section describes what measures will be used for that goal and objective. The sections provide tables or graphics summarizing existing trends. In cases where a measure can be forecasted, this chapter provides projections of the measure under the following scenarios:

• Base Scenario: This scenario uses 2022 regional population and employment estimates and the existing roadway and transportation network, as well as some projects with an estimated completion date of 2025.
• 2050 No-build Scenario: This scenario uses year 2050 regional population and employment forecasts and the Base Scenario transportation network. This scenario explores how the transportation system will perform under forecasted regional growth if we do not make any further investments.
• 2050 Current Revenue Scenario: This scenario uses regional population and employment forecasts for the year 2050 and investments included in the plan’s current revenue scenario. 

The Met Council used forecasts from the Regional Travel Demand Forecast Model (called an Activity-Based Model) and the Regional Transit Ridership Model to forecast the performance outcomes of each scenario.

Some performance measures apply to multiple goals and objectives. For instance, access to destinations can be used to evaluate progress towards both an equitable and inclusive region as well as a dynamic and resilient region. In these cases, measures have been linked to the goals and objectives where they can provide the greatest insight.  

This performance-based approach is an ongoing, dynamic program. The Met Council and its partners in the region will update these measures throughout the plan’s implementation as needed. Ongoing Met Council studies and reports, like the Met Council’s Transportation System Performance Evaluation and future work items, will continuously refresh these performance measures. Going forward, the Met Council will also explore methods of providing evaluations in more dynamic and interactive ways. 

Federal Performance Measures

Federal law (23 CFR 490.29) requires that all state departments of transportation and metropolitan planning organizations establish a performance-based planning program that monitors and tracks the transportation system’s performance. This requires setting performance measure targets for the following six categories:

• Transportation safety
• Bridge and pavement condition
• System performance and reliability
• Congestion mitigation and air quality
• Transit asset management  
• Transit safety

For each of the non-transit performance measures, the Minnesota Department of Transportation has an established deadline to set an overall statewide target. After that target is set, metropolitan planning organizations have 180 days to either:

• Adopt a performance measure target specific to the metropolitan planning organization planning area, or
• Agree to plan and program projects so that they contribute toward accomplishing the state department of transportation performance measure target.

The performance measure categories are either four-year targets with the option to revise in the middle of the performance period or set on an annual basis. Per federal requirements, the Transportation Policy Plan includes an evaluation of the region’s progress in meeting the established performance measure targets. The following sections discuss the current metro area performance. 

Roadway safety

This plan sets an objective that people do not die or face life-changing injuries on our transportation system, supported by several policies and actions to improve safety for users of all modes. These support the Met Council’s commitment to aggressively reduce the number of fatal and serious injury crashes annually, with an aspirational goal of achieving zero fatal and serious injury crashes no later than 2050, supporting the Minnesota Strategic Highway Safety Plan’s commitment towards zero deaths.  

Pursuant to federal requirements, the Met Council has adopted short-range annual highway safety performance targets that are both reasonable and achievable. The Met Council adopted 2024 targets that reflect an annual reduction from the base-year data for fatal and serious injury crashes, as shown in Table 16.1. For 2024, the Met Council set safety targets on a straight-line decline from the 2020 and 2021 targets. Additionally, baseline and prior year performance in the federal pedestrian and bicycle measure has been disaggregated by mode and injury type. 

The Transportation Policy Plan uses two ways of measuring fatalities and injuries: total injuries and deaths and injury rates. Injury rates look at the number of people being killed or seriously injured per hundred million vehicle miles traveled. Both are ways of measuring the region’s progress towards zero deaths and serious injuries.  

Fatal injuries 
Figure 16.1 and Figure 16.2 show recent trends. Between 2019 and 2022, injuries in the Twin Cities rose from 0.44 people killed per 100 million miles traveled (or 130 total people) to a rate of 0.65 (or 179 total people). Although this rate declined slightly from 2021 to 2022, the rates are still alarmingly higher than rates prior to the COVID-19 pandemic. Fatalities across the state of Minnesota have followed a similar pattern.  

Figure 16.1: Number of crash fatalities on all Minnesota roads and Twin Cities metropolitan planning area roads

Figure 16.2: Fatal injury rate on all Minnesota roads and Twin Cities metropolitan planning area roads, per 100 million vehicle miles traveled

Serious injuries 
Serious injuries have also increased over the last three years (see Figure 16.3 and Figure 16.4). Between 2019 and 2022, serious injury rates in the Twin Cities increased from 2.37 (or 699 total injuries) to a rate of 3.46 (or a 949 total) in 2022. As with fatalities, the regional injuries followed a similar pattern as rates across the state. Starting in 2021 following the onset of the COVID-19 pandemic, the regional injury rate began to surpass the state injury rate. 

Figure 16.3: Number of serious injuries on all Minnesota roads and Twin Cities metropolitan planning area roads

Figure 16.4: Serious injury rate on all Minnesota roads and Twin Cities metropolitan planning area roads, per 100 million vehicle miles traveled

Pedestrian and bicycle fatal and serious injuries 
Figure 16.5 shows pedestrian and bicyclist injuries over the last several years. In 2022, the latest year of available data, the bicyclist serious injuries rose to 62, a 43% increase over the previous year. There were 3 fatalities in 2022, one higher than in 2021. In 2022, there were 139 pedestrian deaths and 32 serious injuries, which were slight decreases over 2021.  

Figure 16.5: Pedestrian and bicyclist fatal and serious injuries 

Bridge and pavement condition

In 2023, the Met Council adopted bridge and pavement performance measure targets that matched the statewide targets adopted by MnDOT. The targets were determined through close coordination with MnDOT staff. Overall, bridge and pavement conditions are similar in the metro area to the entire state. The adopted targets are shown in Table 16.2 and Table 16.3. 

System performance and reliability

The Met Council adopted performance and reliability measures for interstate, non-interstate, and truck travel times. System reliability is a measure of the dependability of travel times across different days. Table 16.4 shows the adopted targets for 2023 and 2025. 

Congestion mitigation and air quality

Congestion mitigation and air quality measures are unique in that they only apply to areas which are not in full air quality attainment. Targets must be jointly agreed to by both the Met Council and MnDOT. The region is currently in full air quality attainment; however, new two- and four-year congestion mitigation and air quality measures were required in October 2021, just under a year before the 20-year maintenance period expired in September 2022. These two- and four-year targets are shown below.  

The on-road mobile source emission target applies to PM-10 emission, the pollutant for which the region was under a maintenance plan until 2022. The maintenance plan applied to a small portion of Ramsey County. PM-10 emissions in this maintenance area are largely due to stationary sources; transportation sources are not a significant contributor. Staff have determined that the only project in this area that might reduce PM-10 emissions is the METRO Gold Line Project, and these impacts would be very small. Based on this, the two- and four-year targets for PM-10 reductions due to transportation projects were set to 0.0 kg/day.  

The percentage of regional travel by non-single-occupancy vehicles has been gradually increasing over the past several years, with more residents choosing to carpool, walk, bike, or take transit to and from work. The slight increase from >28% to >29% reflects expectations that this trend of increasing use of alternatives to single-occupancy vehicles will continue in the future.

Excessive delay is a significant mobility concern within the metro area and affects the access to destinations goal of the Transportation Policy Plan, among others. The adopted target was set to no more than 8.5 hours of peak-hour excessive delay per capita in both 2023 and 2025. 

Transit asset management

Transit asset management, a best practice and a requirement under federal law, is a business model that prioritizes funding decisions based on the condition of transit assets. Transit providers are required to assess, track, and report on their assets to FTA, and develop annual targets for asset management to ensure a state of good repair. Transit providers also develop transit asset management plans that document implementation actions for asset management within their transit systems. Initial transit asset management targets must be coordinated with the Met Council, which is the region’s metropolitan planning organization. The four FTA-required performance measures for transit asset management are:  

• Rolling stock (buses and trains used for serving customers): The percentage of revenue vehicles (by type) that exceed the useful life benchmark.  
• Equipment (vehicles used in a support role): The percentage of nonrevenue service vehicles (by type) that exceed the useful life benchmark.
• Facilities: The percentage of facilities (by group) that are rated less than 3.0 on the Transit Economic Requirements Model Scale.
• Infrastructure: The percentage of rail track segments (by mode) that have performance restrictions.

Track segments are measured to the nearest one-hundredth of a mile. The region’s transit operators’ officially established targets are shown in Table 16.6. The Federal Transit Administration (FTA) does not require metropolitan planning organizations to adopt regional transit asset management targets on an annual basis. 

Transit safety

The Federal Transit Administration provides some guidance for transit providers in setting their safety performance targets. Transit agencies are required to these targets by mode. Agencies are allowed to set targets for mode categories as broad as “fixed-route bus,” “non-fixed-route bus,” and “rail” when setting safety performance targets.

Metro Transit monitors performance and sets federally required targets for rail and fixed-route bus service. The Strategic Initiatives department of Metro Transit works with data collected from many sources to identify significant risk factors and trends in accidents and injuries, leading to informed recommendations for accident reduction programs and more efficient use of limited resources. Table 16.7 summarizes the region’s transit safety measures. 

Regional Performance Measures

The Transportation Policy Plan regional performance measures track the region’s progress towards achieving this plan’s goals and objectives. This chapter looks at recent trends and current conditions to evaluate where the region presently stands in relation to goals and objectives. Where possible, the chapter compares existing conditions with performance goals or with forecasts of different transportation investment scenarios.

Goal: Our region is equitable and inclusive 

These measures evaluate how the transportation system provides access to opportunities for historically disadvantaged communities and repairs disparate impacts to Black people, Indigenous people, and people of color. These measures also explore how well the transportation system accommodates people with disabilities or limited mobility.

A key feature of these measures is that they look at the impacts of the transportation system on different groups of people, not just how the transportation system affects the region as a whole.  

Access to destinations 
Access measures look at how many opportunities and resources (jobs, shopping, etc.) people can reach within a certain travel time.  

Unlike measures like average speeds, access considers both land use and the transportation system. Access measures acknowledge that it doesn’t just matter how fast you can travel to your destination, but also how close or far you might be from that destination.¹⁴³

Job access is a useful measure since it indicates both employment opportunities and access to services like retail. As the chart Figure 16.6 shows, automobiles currently offer the highest job accessibility. The average resident can reach 50% of all jobs in the region in 20-35 minutes by car on a weekday and 100% of jobs in about 50 minutes. (Note: Percentages in Figure 16.6 exceed 100% since commuters also begin to have access to jobs outside the region with higher travel times). Access to jobs by other modes (for example, bikes, transit) is much lower under our current land use and transportation system. 

Figure 16.6: Access to regional jobs, base year

Regional job access varies across the Twin Cities and is affected by factors such as surrounding land uses, transit service, and transportation infrastructure. For instance, communities designated as Urban are the most centrally located cities in the region. These include Saint Paul and Minneapolis as well as surrounding cities like Columbia Heights, Hopkins, and Richfield. In Urban communities, half of the region’s jobs can be reached by auto in between 15 and 20 minutes. By contrast, for cities designated as Suburban Edge, it takes between 25 and 30 minutes to access half of the regional jobs on average.

Because of the dramatic difference between auto accessibility and other modes, it is useful to look at these other modes with a separate chart. Bikes and transit offer the next highest levels of access to jobs. By bike, less than 2% of all regional jobs are accessible within 30 minutes and just over 6% of regional jobs can be reached in an hour on average. By transit, just under 2% of all regional jobs are accessible within 40 minutes and just over 5% of regional jobs can be reached in an hour on average.  

This transit accessibility varies widely across the region. In some areas of the region, transit service is not available. In areas with more limited transit service, such as Suburban communities, 5% of regional jobs are only accessible on average within 70 minutes of travel time. In Suburban Edge Communities, about one-half of one percent can be reached by transit in 70 minutes. Bike access to regional jobs is similarly lower outside of Urban and Urban Edge Communities. 

Figure 16.7: Access to regional jobs, nonmotorized, base year

Another way of looking at how accessibility differs by mode is measuring how long it takes people to get to common destinations by different travel modes. Table 16.8 uses analysis from the University of Minnesota’s Accessibility Observatory of typical travel times for two different common destinations: food stores and K-12 schools. This analysis looks at how long it takes to reach the three nearest options for food stores and K-12 schools, based on the assumption that people might need access to more than the nearest option to meet their needs.  

Table 16.8 shows that driving offers significantly faster average travel times to common destinations compared to other modes.  

Improving these differences requires a combination of changes to transit services as well as land use changes. For instance, communities that fall within the Imagine 2050 Community Designation of Urban feature some of the densest land uses in the region. These include Saint Paul and Minneapolis as well as surrounding cities like Columbia Heights, Hopkins, and Richfield. These cities also feature some of the most abundant transit service. In these communities, the typical travel times for transit, biking, and walking are much lower. For instance, the typical travel time to the nearest three food stores is 12 minutes by transit and 6 minutes by biking, nearly half as much as the regional average (21 minutes and 11 minutes, respectively). The median time for walking to the third nearest school in Urban areas is also much shorter, 22 minutes, which is 10 minutes shorter than the regional median. 

One way of looking at how accessibility changes with future scenarios is to forecast the change in average job accessibility. Table 16.9 shows average job accessibility by auto within 30 minutes and transit by 45 minutes for the three different scenarios. The numbers in this table reflect how many jobs a person (on average) can reach by traveling 30 minutes by car and 45 minutes by transit.  

The table shows that job accessibility by automobile goes down in the future between the base year and the no-build scenario. This could be due to population growth in areas where there is less employment as well as slightly higher travel times due to more people using the highway network. The current revenue scenario goes up 2% compared to the no-build, suggesting that some of the new highway investments will improve job accessibility slightly compared to the no-build; however, average job accessibility is forecasted to decrease between the base year and 2050, even under the current revenue scenario.

Future transit accessibility is forecasted to increase in the future. The average job accessibility of 45 minutes by transit goes up 28% between the base-year and the no-build. This increase is probably due to the forecasted growth of jobs and population along transit-rich corridors. This transit accessibility goes up even further in the current revenue scenario due to the increased transit service provided by improvements such as arterial bus rapid transit and new transitways. 

Why does job accessibility change in the no build scenario? Job accessibility can increase or decrease even without new transportation investments. Other factors, like population growth, job location, and congestion can affect job accessibility

A more detailed breakdown of how job accessibility changes under the current revenue and no-build scenarios by neighborhood demographics is discussed in the Environmental Justice Analysis section.

Exposure to pollution 
Exposure to air pollution is a risk for all communities in the region; however, studies show that low-income neighborhoods and communities of color face higher risks. According to the Minnesota Pollution Control Agency, 46% of all low-income communities and 91% of communities of color face air-pollution risks above health guidelines. The statewide average is 32%.¹⁴⁶ 

The region’s pollution measures will go beyond measuring regional pollution totals; it will also look at how pollution exposure concentrates in specific communities based on socioeconomic characteristics. To do this, this measure evaluates localized indicators of pollution.

One tool that summarizes more localized indicators of pollution is the U.S. Department of Transportation’s (USDOT) Equitable Transportation Community (ETC) Explorer.¹⁴⁷ This website application provides measures of “the cumulative burden communities face,” including a community’s environmental burden. The Environmental Burden is an index that compares a community’s exposure to environmental burdens – from sources like air pollution, hazardous sites, infrastructure, and water pollution – to other communities across the nation or state. It includes factors such as ozone levels, diesel particulate matter, air toxics cancer risk, highway proximity, and impaired surface waters.  

Figure 16.8 shows how higher Environmental Burden indices are often concentrated in areas that have a higher percentage of people experiencing poverty or where more people of color live. The map highlights census tracts where the Environmental Burden is above average for the state. The map also identifies census tracts where the either the percentage of people of color or the percentage of people in poverty is higher than average for the region.  

Although areas experiencing above average Environmental Burden indices are found throughout the region, most tracts with high Environmental Burden indices are located in tracts with higher shares of people in poverty or people of color. In Figure 16.8, about 57% of all tracts in the region have an Environmental Burden higher than the stateside average. For tracts with higher shares of people in poverty or people of color, this percentage is significantly higher – about 79%.  

Several other useful sources look at local pollution across the region. One is the Environmental Protection Agency’s Environmental Justice Screening and Mapping Tool.¹⁴⁸ This resource provides environmental and socio-economic indicators to help identify communities at higher environmental risks.  

Another is the Minnesota Pollution Control Agency’s Understanding Environmental Justice in Minnesota story board,¹⁴⁹ which provides an online, interactive depiction of local air pollution risk. This resource provides maps of the Air Pollution Score (an index that looks at the highest air pollution risk communities face) alongside maps of Areas of Environment Justice Concerns. 

Figure 16.8: Environmental Burden Index

Exposure to noise 
Noise exposure is a complex topic; noise modeling is very technical and exposure varies depending upon where you are in the region. Both factors make noise exposure a challenging topic to encapsulate in a few paragraphs in this chapter. Even so, noise exposure is an important way that the transportation system affects different communities.  

At a very simple level, exposure to highway traffic noise is heavily dependent on three things:

• Traffic volumes
• Traffic speeds
• How much of that traffic comes from trucks¹⁵⁰ 

A rise in any of these things increases noise exposure for populations living near transportation facilities. Furthermore, this noise exposure decreases the further people are from these things. Consequently, populations living close to highways and other major roads have the greatest potential for noise exposure. Noise exposure can also affect wildlife.¹⁵¹ Mitigation efforts such as noise barriers can minimize how much actual noise people experience near roads.

The Met Council will explore ways to work with other agencies to evaluate how transportation projects disparately affect communities. One potential resource for this work will be the upcoming Freeway Harms Study, which can explore this topic in more depth. A good place to look at noise exposure is the Bureau of Transportation Statistics’ National Transportation Noise Map. 

Exposure to extreme heat 
As stated in the Met Council’s Keeping our Cool project, “Extreme heat has unequal impacts across the region. Individual with low incomes are more likely to live in areas with less tree cover and more impervious surfaces compare to wealthier individuals.”¹⁵²  

The project explored land surface temperatures to look at extreme heat risk throughout the region. Residents with low incomes are more likely to live in hotter neighborhoods (see Figure 16.9). The transportation infrastructure plays a role in this heat exposure through impacts like increasing impervious spaces or altering tree canopies. The transportation system also plays a role in people’s accessibility to places that provide relief from extreme heat.  

Figure 16.9: Land temperature and median household income

Figure 16.10 shows surface temperature across the region. The map highlights how surface temperatures are often higher in areas characterized by impervious surfaces associated with the transportation infrastructure.

Figure 16.10: Map of land surface temperatures, 2022

Goal: Our communities are healthy and safe 

This goal’s measures include indicators of how we reduce the harmful impacts of our transportation system, such as pollution and deaths and serious injuries from traffic crashes, for all the region’s residents. They measure how our transportation system promotes public health by providing opportunities for active transportation.

Roadway fatalities and serious injuries 
The Met Council reports roadway safety performance measures as part of the federal performance-based planning requirements. Please refer to the Federal Performance Measures: Transportation safety section of this document for detail on roadway fatal and serious injuries. 

Travel by mode 
The health and safety goal promotes the comfortable use of all modes and increased opportunities for active transportation. Differences in the modes of travel people use can be one measure of how our transportation system meets this goal. As shown in the table below, most trips made by households in the region are made by car (about 85%). The remaining 15% of trips use other modes. But these regional numbers do not tell the whole story. Mode share varies widely across the region based on geography and demographic factors.

For instance, the Travel Behavior Inventory (2021) shows that Black people, Indigenous people, and people of color are more likely to make trips using some alternative to driving alone compared to white people. The use of transit to make trips is especially higher among Black people, Indigenous people, and people of color (see Figure 16.11).  

Figure 16.11: Mode share by race

Mode share also differs depending upon where you live. Factors like land use patterns and the availability of alternate modes affect how people travel. Figure 16.12 below shows mode share by Imagine 2050 Community Designations. Urban areas show significantly higher usage of walking, biking, and transit compared to suburban areas. Higher density and more transit options likely influence these differences in mode share. Higher density can include higher numbers of housing and jobs or services in closer proximity, which can make modes like walking, biking, and transit more convenient and appealing.  

Figure 16.12: Mode share by Imagine 2050 Community Designation

One measure of the transportation plan’s investments will be to evaluate how these mode shares might change based on transportation system improvements, changing demographics and future land use patterns. Future transportation investments – for instance, making suburban street networks less circuitous, more frequent transit service, or improvements to bike infrastructure – will also influence what mode people use. The table below summarizes how the Regional Travel Demand Model and the Regional Transit Ridership Model forecast mode share will change under three transportation investment scenarios. 

The first row in the table is based on observed data (in other words, not forecasts) from the 2021 Met Council Travel Behavior Inventory Household Survey. The second and third rows are forecasts of how this mode share will change in 2050 under the 2050 no-build and current-revenue scenarios.  

The forecasts show slight increases in people using transit, walking, and biking in the future. The main difference between the base - 2021 and the no-build is future population – both assume a similar transportation system. Some of these forecasted changes are likely occurring due to demographic changes, such as an aging population. For instance, the Other category includes school bus trips, which is forecasted to go down as the average age of the population increases in 2050. A share of these lower school bus trips could be shifted to other modes like transit, walking, or biking. Other factors, such as more people living along transit lines, or increased congestion, might also account for the small shift to transit.

The table also shows further slight increases to transit under the current revenue scenario. These shifts are likely due to the increased transit services in the form of increasing arterial bus rapid transit and new transitway corridors. 

Air pollutants emission levels¹⁵⁵ 
The Clean Air Act (1970) established standards for six pollutants known to cause harm to human health and the environment. These six pollutants, known as criteria pollutants, are:

• Particulate matter (currently PM2.5 and PM10)
• Ozone (O3)
• Nitrogen dioxide (NO2)
• Sulfur dioxide (SO2)
• Carbon monoxide (CO)
• Lead (not monitored in the transportation planning process) 

The federal Environmental Protection Agency (EPA) developed National Ambient Air Quality Monitoring Standards for each of these criteria pollutants. Primary standards are set to protect public health, while secondary standards are set to protect the environment and public welfare (for example, visibility, crops, animals, vegetation, and buildings).

As shown in Figure 16.13, the region is currently in attainment for all the pollutants regulated by the EPA. The figure shows the maximum pollutant level for each year as a percentage of the National Ambient Air Quality Standards from all sources (not just transportation); anything below the solid line means the pollutant is below the standard.  

Figure 16.13: Maximum air pollutant values as a percent of National Ambient Air Quality Standards

As shown in the chart, pollutant levels have generally trended downward since 2000 except for PM10. Not all emissions come from transportation sources. Some decreases are due to changes in things such as energy production, building practices, and land use changes. Other changes are due to things beyond the region’s control, such as the weather and wildfires. But regional transportation decisions do play a part in minimizing air pollution. Examples of transportation-related changes that might decrease pollutant levels include decreased vehicle travel, changes in vehicle emissions technology, and growing use of alternative fuel sources.

While Minnesota Pollution Control Agency measures of observed air pollutant levels include all sources (including non-transportation sources), the Met Council can use an EPA model called Mobile Vehicles Emissions Simulation to estimate pollutants specifically from vehicle emissions. The Mobile Vehicles Emissions Simulation model takes information from the Regional Travel Demand Model about vehicle miles traveled and vehicle speeds to estimate pollutants. This connection with the Regional Travel Demand Model also allows Mobile Vehicles Emissions Simulation to forecast how these emissions might change under different transportation scenarios.

Table 16.11 shows the results of emission modeling for criterion air pollutants for the base year of 2025. (Note: Volatile organic compounds and oxides of nitrogen are included since they are precursors of ozone). It also compares the base year emissions with modeling for the no-build scenario and the current revenue scenario. The table shows dramatic decreases in emissions between the 2025 base year and the 2050 no-build. These differences are largely due to assumptions of increased fuel efficiency and cleaner burning combustion engines over the next 30 years. These decreases also include forecasts of increasing proportions of electric vehicles. Emissions in the build scenario are slightly higher compared to the No Build scenario due to a small increase in vehicle miles traveled. These emissions increases are very small – each is under one-half of 1%.

Goal: Our region is dynamic and resilient 

The measures under this objective look at the transportation infrastructure’s ability to withstand and recover from natural or human-caused disruptions. Performance measures for this goal also look at whether the region’s transportation infrastructure meets users’ need for predictable and reliable travel times.

Infrastructure 
Several sources look at the condition of our regional infrastructure, as well as its vulnerability to extreme heat and flooding.  

One useful source of information about bridges throughout the region is MnDOT’s Bridge Info Interactive Map. The resource provides an interactive tool to see the location of bridges as well as information about their age and condition.

Other information can be found in the Metropolitan Council’s Climate Vulnerability Assessment, which includes links to a Localized Flood Map Screening Tool among other resources. According to a 2018 Regional Climate Vulnerability Assessment, about 17% percent of the region’s transportation and transit assets fall within a Flood Impact Zone (FIZ).¹⁵⁷ Table 16.12 below summarizes the percentage of various regional transportation asset that fall within a FIZ. 

MnDOT also provides several resources for assessing flood vulnerability, including the Extreme Flood Vulnerability Analysis and the Flash Flood Vulnerability and Adaptation Assessment Pilot Project.  

The Met Council will explore ways to work with MnDOT to bring in the most up-to-date studies and tools to measure how the regional transportation infrastructure’s vulnerability to flooding changes over time. 

Congestion and reliability 
System reliability measures how dependable travel times are on different days. Reliability acknowledges that congestion is not the only thing that affects users. Inconsistent travel times can also cause problems for travelers. Travel time reliability is a measure of the ratio of vehicle miles traveled on the highway system that incur longer-than-normal travel times to vehicle miles traveled that experience normal travel times. A higher percentage means more consistent travel times and a lower percentage means more inconsistent travel times. Table 16.13 shows recent travel time reliability measures from MnDOT and compares them to the federal performance measure target. 

Travel-time reliability increased significantly after the COVID-19 pandemic. Between 2019 to 2020, travel-time reliability jumped from 74% to 98%, within the statewide target. This increase occurred as fewer people made peak-period commuting trips at the beginning of the COVID-19 pandemic. This number began to creep back down after COVID-19; however, as of 2022 travel time reliability is still well above pre-COVID levels. It will be important to keep monitoring this over the coming years to see the longer-term post-COVID trends.  

One regional measure of congestion is the weekday delay per capita. The Regional Travel Demand Model provides a way to forecast this delay by looking at the automobile travel time for each forecasted trip and comparing that to the trip time if there was no congestion (for example, posted speed limits). The difference between these congested travel times and free travel times is the weekday delay. Adding those delays by each person gives us the delay for each traveler.

Table 16.14 below compares median delay per automobile traveler using the Regional Travel Demand Model for the three scenarios. The median is the mid-point of traveler’s delay in the forecasts, in other words, the point where half of the travelers have a lower delay and half of the travelers experience higher delay.  

The table shows some small changes in the median delay per travel across the scenarios. Median delay per traveler goes up from 9 and three-quarter minutes in base year to just under 11 minutes in the no build. This increase is due to increased population (and, consequently, more trips) in 2050 under the same transportation system. This median delay goes down slightly in the current revenue scenario, but these changes are small since the current revenue adds relatively little new capacity to the highway system. 

Goal: We lead on addressing climate change 

These measures will be used to evaluate how well our transportation decisions minimize our region’s contribution to climate change. This includes policies that increase confidence in zero emissions transportation options and decrease vehicle miles traveled.

Greenhouse gas emissions
The transportation sector is the largest contributor to regional greenhouse gas emissions. According to the Met Council’s Greenhouse Gas Inventory, the transportation sector, including all on-road emissions sources, accounts for about 35% of the region’s total greenhouse gas emissions in 2021.¹⁶¹  

As with vehicles emissions modeling, the Met Council uses the Motor Vehicle Emissions Simulator Model, in conjunction with Regional Travel Demand Model, to forecast how our transportation investment strategy will change greenhouse gas emissions. Table 16.15 shows the results of greenhouse gas emission modeling for the base year of 2022 and how those emissions are forecasted to change by 2050 under minimal transportation investments (no build) and under our planned transportation investment scenario (current revenue scenario). 

As with the mobile air pollutant emission forecasts, greenhouse gas equivalent emissions are forecasted to go down between the base year and the 2050 no build. These changes are due to forecast assumptions of more efficient vehicles and increased adoption of electric vehicles. The current revenue scenario is forecasted to see slightly higher greenhouse gas emissions (under one-quarter of 1%) due to slightly higher vehicle miles traveled. 

Vehicle miles traveled 
Vehicle miles traveled typically rise with population increases. If typical travel behavior remains the same, more people in a region means more vehicle miles traveled. Without changes to the transportation system and travel behavior, regional vehicle miles traveled historically goes up over time with population growth.

Vehicle-miles-traveled per capita accounts for population growth by dividing the total vehicle miles traveled by the population. This filters out the effects of population growth on vehicle miles and highlights how vehicle travel goes up or down due to changes in travel behavior, such as people making fewer trips, commuters making shorter trips, or people switching from driving alone in a vehicle to other modes (for example, transit, bikes, etc.).  

Figure 16.14 shows that average weekday vehicle-miles-traveled per capita remained constant around 25 miles per day for much of the early 2000s. In 2020, however, vehicle-miles-traveled per capita dropped dramatically to just over 20 miles per day as people reduced their trips and stayed home due to COVID-19. Beginning in 2021, vehicle-miles-traveled per capita began to trend up and by 2023 vehicle-miles-traveled per capita was nearly 23 miles. It is uncertain when or if vehicle-miles-traveled per capita will return to its pre-COVID levels. Some travel behaviors, such as telecommuting, will likely persist in the long-term.

Figure 16.14: Average daily vehicle miles traveled (VMT) per capita

Table 16.16 includes forecasts from the Regional Travel Demand Model that show that vehicle-miles-traveled per capita is forecasted to change going from the base year to the no-build year. Since the transportation network remains the same between the two scenarios, this decrease likely reflects demographic changes such as an aging population or smaller households. The current revenue scenario vehicle-miles-traveled per capita goes up slightly (about 0.4 %) compared to the no build; however, vehicle-miles-traveled per capita in the current revenue scenario is still lower than the base year.

Electric vehicles 
Electric and hybrid vehicles are still a small portion of light-duty vehicles, but their usage appears to be growing in the last few years. Figure 16.15 shows the current percentage of light-duty vehicles in the Twin Cities metropolitan planning organization area that are fully electric or hybrid. Across the nine counties, the percentage of hybrid or fully electric vehicles ranges from about 1.6% (Hennepin County) to around 0.4% (Sherburne County). 

Figure 16.15: Electric vehicles as a percent of all light-duty vehicles, Twin Cities metropolitan planning organization counties

While still a small portion of overall personal vehicles, electric vehicle market share of newer vehicles has begun to pick up recently. Statewide registration of battery and plug-in hybrid electric vehicles grew rapidly over the last five years. The total number of registered battery electric vehicles increased nearly seven times, from over 5,300 in 2019 to over 40,000 in 2024. During this same period, plug-in hybrids nearly tripled, from 4,888 to over 18,000.  

Figure 16.16: Statewide electric vehicle registrations

Electric vehicles’ share of statewide new vehicles (see table below) has risen substantially over the last several years, although they are still trending well below MnDOT’s goals of 60% by 2030 and 100% by 2035. 

Goal: We protect and restore natural systems

This goal aims to limit the transportation system’s impact on natural systems such as water, vegetation, and habitats. One feature of the transportation system with a big impact on these resources is impervious surfaces.

Impervious surfaces 
Paving over surfaces creates several adverse effects. Impervious surfaces prevent water from filtering into the ground either by directing it into storm drains and/or concentrating it into runoff, which increases how fast water flows into rivers and streams. This reduction of infiltration and increase in runoff can affect water quality and the risk of flooding.24 Impervious surfaces can also trap heat, which is worsened where more impervious surfaces are present, creating the “urban heat islands.” This warming effect is made more concerning as temperatures rise due to climate change.

As of 2023, about 2.94% of the region’s land area is covered by impervious surfaces used for paved roads. This number is even higher in more urbanized counties such as Ramsey and Hennepin (6% and 4.9%, respectively). This number has gone up gradually over time as new facilities are built. Barring any future removal of roads or major changes in their design, these percentages will continue to increase over time as new the region builds more transportation infrastructure. 

Figure 16.17: Percent lane area by county

Potential Measures for Work Plan

As part of its Performance and Evaluation Program, the Met Council will explore new measures that might be accomplished through future work programs, new research, and increased partnerships with other agencies and community groups. A robust performance and evaluation system needs to constantly evolve. Shifts such as technological innovation and environmental change will create the need for new evaluation measures. Innovations in research and data availability will open opportunities to measure things the Met Council has not been able to study. 

Potential measures for future exploration include:

• Research into where transportation redundancy is needed to minimize the impacts of system disruptions.
• An inventory of compliance with the Americans with Disabilities Act (ADA) on public rights-of-way.
• A study of transportation stormwater conveyance systems.
• An examination of public perceptions about the safety of the region’s transportation network.
• A project evaluating how well the transportation system connects different communities, and where investments can be made to improve connectivity in places that are geographically isolated.