15 Increase the availability and attractiveness of transit, bicycling, and walking
Increase the availability and attractiveness of transit, bicycling, and walking to encourage healthy communities through the use of active transportation options.
15.1 The Regional Bicycle Transportation Network (RBTN)
The Regional Bicycle Transportation Network (RBTN) is the official regional bikeway network that sets the region’s priority vision for planning and investment. The network was established in 2014 based on a Regional Bicycle System Study analysis and prioritization of potential corridors. This analysis was based on factors like bicycle trip demand, network connectivity, social equity, population and employment density, and connections to transit.
15.1.1 RBTN Corridors and Alignments
The RBTN consists of a series of corridors and general alignments. The corridors are established where there is existing or potentially high bicycle trip demand between regional destinations and activity centers, and reflect where alignments have not yet been identified. Alignments are defined where there are existing or planned bikeways, or in the absence of these, a general consensus of which road or roadways would most efficiently meet the regional corridor’s intent. Corridors and alignments are classified as Tier 1 or Tier 2 priorities, with Tier 1 representing the region’s highest priorities for bikeway planning and investment. Figure 15.1 is an online interactive map of the current RBTN corridors and alignments by priority tier.
The RBTN has provided the backbone arterial network vision to accommodate daily bicycle trips since 2014 and the region continues to monitor progress on its implementation. Figure 15.2 shows the regional network’s implementation status by existing and planned bikeway miles. Figure 15.3 displays the shares of total RBTN centerline miles for existing and planned bikeways.
15.2 Bicycle and pedestrian miles traveled
This section shows how the total amount of bicycle and pedestrian travel has changed over time, using the Travel Behavior Inventory (TBI) household survey. An increase in the total distance and/or the total number of trips made by walking and biking is one indicator that the transportation system is working to support increased active travel in the region. Increased walking and biking can also reflect how the region is developing and where people are living, working, and recreating. Because of differing data collection methods over time, some increases in bicycle and pedestrian travel metrics is likely attributable to better data collection.
15.2.1 Results
Results from the TBI 1 suggest that total walk miles traveled has increased since 2010. Walk miles traveled in 2019 was 1.7 times greater than that of 2010; and grew again by 58% from 2019 and 2021. The black lines indicate the standard error.
In contrast, bike miles traveled remained steady from 2010 to 2019, then decreased 17% from 2019 to 2021.
The increase in walk miles traveled from 2010 was primarily driven by an increase in the number of walk trips, which almost quadrupled from 2010 to 2019. This trend is explainable in part by the use of smartphone-based survey data collection in 2019, which likely improved reporting of short trips and walk trips. The black lines indicate the standard error.
From 2019 to 2021, walk miles traveled grew by 58%, even while the total number of walk trips decreased. During this two-year interval, the increase in walk miles traveled was driven primarily by an increase in the typical length of walk trips. Median walk trip distance increased from 0.4 miles per trip in 2019 to 0.6 miles per trip in 2021. Walk trip distance increased the most for trips to school and work. Figure 15.6 shows the median walk trip distance over time. The black lines indicate the standard error.
The reasons for an increase in walk trip length from 2019 to 2021 are unclear. One potential explanation is a reduction in transit service from 2019 to 2021, which could have shifted some walk-to-transit trips to walking alone. Improved capture of children’s trips to school in the 2021 survey may also be a contributing factor. Future iterations of the TBI will reveal if this is a lasting trend.
The Travel Behavior Inventory survey suggests that residents are doing more walking, and slightly less bicycling in 2021 than in previous years (2010, 2019). Residents seem to be making slightly fewer, but longer, walk trips.
It is important to note that the uncertainties of survey data – especially for these modes where the sample size is significantly smaller than for dominant auto/driving modes – meaning that these findings should be taken not as a definitive answer, but rather one piece of evidence of increased active travel in the region. Additional years of survey data collection, as well as research by Met Council staff into alternative sources of information surrounding active travel, are crucial to determining whether these data points form a real trend.
15.3 High frequency transit accessibility
Increasing the availability of transit across the region - especially high-frequency transit - is one way to support active travel in the region. Here, we assess transit availability in the region as both the amount of geographic area within a ten-minute walk of transit, and as the population served by transit within a ten-minute walk of home.
We focus on high-frequency transit service, as defined by Metro Transit:
- stops served by routes that depart every 15 minutes or better,
- with at least three stops per hour,
- on weekdays from 6:00 a.m. to 7:00 p.m. and Saturdays from 9:00 a.m. to 6:00 p.m.
An index of the number of stops served by high-frequency routes and which routes are considered high-frequency can be found in Section C.4.
Our data comprise walkshed information from all regional transit agencies except Minnesota Valley Transit Authority (MVTA), which does not provide high-frequency transit.
Figure 15.8 shows the areas served by high-frequency transit in 2016 (yellow) and 2022 (green). You can choose different years to view by clicking on the check boxes in the legend. High-frequency service is clustered in the downtown areas of Minneapolis and Saint Paul, as well as along the I-94 corridor between these two cities. A handful of areas in the north and south suburbs also appear, where transit service stations are located.
The map reveals a few changes from 2016 to 2022, especially where some core local routes in Roseville and northern Saint Paul were reduced to less frequent service (the 62 and 65). These two routes in particular were supported with greater frequency in the years after the Green Line construction (2014-2016), with the hope that riders would use the lines to access the Green Line. Frequency was scaled back when ridership did not respond as hoped. Also apparent on the map are areas where express routes through Richfield and Edina were reduced or eliminated (the 515, 540, and 542) following driver shortages and ridership declines during COVID-19 pandemic.
Transit can operate most efficiently when it serves areas where people live, work and shop close to one another in dense communities. In our region, the percent of geographic area served by high-frequency transit has remained mostly flat since 2013, ranging between 2 and 2.5%. Meanwhile, the percent of area served by any transit at all has declined markedly in COVID-19, from 14% in 2019 to 11% in 2022. These diverging trends by service type speak to the need to continue supporting transit in their core market areas.
Transit availability can be improved in a few ways
- Encouraging population growth within well-served areas (i.e., increasing the density of jobs and homes)
- Expanding service into new areas
- Improving frequency of existing transit routes.
As of 2022, roughly 15% of the region’s population lived in that small slice of area (2% of the region’s area) served by high frequency transit.
The share of the regional population that can reach the high-frequency network within a ten-minute walk has been relatively flat since 2013, varying within a few percentage points (15%-18%). The peak of high-frequency transit availability by this measure occurred in 2016: 18% of residents in the region could reach high-frequency transit within a ten-minute walk.
Today roughly one in seven residents have access to the kind of service that could allow a person to build a full life around public transit service. This number has been relatively flat for the last decade. This speaks to the regional prioritization of preserving core high-frequency service in the face of COVID-19 and driver shortages, while also suggesting that significant investment and changes to development strategies will be needed to increase transit availability in any meaningful way going forward.
15.4 Access to employment driving vs. transit
In the Twin Cities, the number of employment opportunities accessible by traveling in a private automobile is several magnitudes greater than the number of employment opportunities accessible traveling using public transportation; 741,265 jobs on average are accessible within 30 minutes to those traveling by private automobile in the Twin Cities (Murphy and Owen 2020), compared to only 14,171 jobs being accessible within 30 minutes by those traveling by public transportation (Murphy and Owen 2021).
The probability that a Twin Cities’ residents’ place of employment is within 30 minutes using automobile versus public transportation is evident when looking at the mode share of how people commute in the Twin Cities with 78% (+/- 1%) of work trips by automobile (Travel Behavior Inventory, 2021).
Deriving a total miles traveled measure from the TBI requires some special considerations. While smartphone-based surveys collected in 2019 and 2021 collected observed trip distances along the actual path taken by the survey respondents, neither the 2010 TBI nor the phone- and web-based surveys from 2019 and 2021 TBI collected actual travel distances. To standardize across all years and survey types, travel distances for all trips were calculated using the Open Source Routing Machine (OSRM), a web-based routing engine. Trip origin and destination coordinates were fed to OSRM, which solved for the shortest-distance path by bike or foot.
It is important to know that trip distances calculated in this manner are likely an under-estimated, for two reasons.
First, using OSRM necessitates solving for the shortest-path distance, which is not always chosen by those on foot or bicycle owing to other considerations like safety, comfort and enjoyment.
Second, survey respondents may not remember or report all of their trips. Walk trips in particular are more likely to be forgotten relative to trips made by driving, transit, and long-distance modes; and short trips like those made by walking are more likely to be forgotten than long trips. Smartphone-based data collection, used in 2019 and 2021, improved collection of walk trips, but no self-reported survey is perfect.↩︎