In the business district of North Kansas City, Missouri, planners envisioned a corridor where cyclists and vehicles could coexist safely. Would a protected bike lane increase bicycling and reduce speeding without causing congestion? A before-and-after study—powered by StreetLight analytics—reveals what happened.
In 2019, Armour Road in North Kansas City, Missouri, underwent a series of improvements. The new infrastructure added brightly colored crosswalks, pedestrian refuges, and a new protected bike lane.
The bike lane was separated from vehicle traffic by a floating parking lane running parallel to the road, as well as special buffers and markings—a design intended to keep cyclists safe.
North Kansas City promotes itself as a livable city with suburban character. Armour Road is a principal thoroughfare running through the city’s downtown and adjacent commercial area. The bike lane installation wasn’t a routine upgrade, but a core part of the city’s broader plan to invest in biking and walking infrastructure, accessible urban destinations, and a vibrant cultural and business scene.
In working toward their vision, the planners had multiple goals for the Armour Road bike lanes. They wanted to promote efficient travel, but also safety and a greater amount of biking and walking in the heavily trafficked district.
To see if the new infrastructure worked, StreetLight conducted a before-and-after study using StreetLight InSight®, an on-demand mobility analytics platform. The study analyzed whether three of the stated policy goals of the Armour Road project were achieved. Specifically, did the bike lane:
- Encourage biking so it makes up a greater overall share of traffic volume
- Lead to a safer corridor with less speeding
- Improve or at least maintain travel times
Planners can use StreetLight to complement more expensive, traditional methods of measuring traffic volume and vehicle speeds, such as direct observation, surveys, and counters. In this instance, there were several advantages to using StreetLight’s analytics for a data-driven, self-serve approach:
- First, we were able to easily run multiple analyses to account for the possible distorting effect of 2020 pandemic restrictions. The bike lane was completed in late 2019, so our analyst ran the “before” data for the months of January to March of 2019. Although the obvious approach would have been to compare that data to the same period in 2020 (as the “after”), the tail end of that interval was affected by pandemic-driven lockdowns and altered traffic patterns. So we ran the data for January to March of 2021 as well, resulting in three sets of data to compare.
- Second, we were able to inexpensively compare Armour Road data to a control road in the study area. Using StreetLight’s platform, the analyst measured bike activity on East 21st Street, a nearby road that runs parallel to Armour Road, to see if the new bike lane pulled in bike activity that would have happened elsewhere or actually increased biking activity overall.
- Third, StreetLight captured nighttime bike volume that traditional methods usually can’t measure. Because traditional techniques often only operate well in daylight or business hours, they can miss a significant slice of volume. Later analysis showed that 15% of bike usage on Armour Road happened in night hours between 7 p.m. and 7 a.m., which likely would have been missed with traditional data collection.
- Finally, StreetLight’s platform allowed for quick, multimodal snapshots and a synthesis of metrics tied to very different dimensions, including traffic share, safety, travel times, and congestion rate.
A visualization from StreetLight InSight® of bike volume on Armour Road from the 2019 study period shows how the distribution of volume (shown by the yellow line) peaks near midday but shows significant volumes in other parts of the day such as late evening, when traditional data collection is difficult.
The safety question was high among planners’ concerns.
As StreetLight Speed Metrics confirm, in 2019 drivers were speeding on Armour Road, with as many as one in every 20 car trips down the corridor moving in excess of 40 mph (miles per hour), despite a posted speed limit of 25 mph. After project implementation, the share of drivers going above 40 mph dropped to almost 0, significantly reducing the risk that pedestrians will be killed or seriously injured in the event of a crash.
As planners know all too well, higher vehicle speeds lead to an exponentially higher probability of severe injury or death in vehicle collisions with pedestrians. A widely cited AAA study shows that in the U.S., the average risk of severe injury for a pedestrian struck by a vehicle reaches 25% at 23 mph, but is three times higher, 75%, at 39 mph. The chance of death for pedestrians struck by a vehicle is on average 10% at 23 mph and 50% at 42 mph.
Ideally, a safer Armour Road would see less speeding without a significant increase in travel times or congestion.
Of course, the main purpose of bike lanes isn’t simply to slow down speeding cars—it’s to encourage bike activity. And planners wanted to make progress on the city’s goal of encouraging bike use.
The before-and-after: Reduction in speeding, doubling of bike traffic, and more
As hoped, bike traffic on Armour Road increased its share of the traffic-volume pie, according to StreetLight’s measurements.
Before the bike lanes, in early 2019, bikes accounted for only 1% of the daily trips on Armour Road. In early 2021, biking’s share had grown to 2%. That may seem like a modest increase but represents a significant uptick in day-to-day bike travel: there were around 50 daily bike trips on average passing through the study sites along the corridor in early 2019. In 2021, after the protected bike lane went in, that number more than doubled to 114.
But was this the result of cyclists from other neighborhoods and bike routes being attracted to the upgraded Armour Road corridor? Or is there evidence that some of the biking would not have happened without the bike lanes?
As mentioned, that’s where the control data became useful. While less trafficked overall than Armour, the control segment on East 21st Street saw a proportional increase in bike traffic between 2019 and 2020 (though it remained flat between 2020 and 2021). The lack of a decrease in biking on East 21st Street supports the hypothesis that the new bike lane led to an overall net increase in biking’s adoption in the study area, rather than simply funneling in preexisting bike traffic.
In terms of safety, the most significant safety improvement was possibly a life-saving one. The bike lanes led to the near elimination of the most dangerous speeds—vehicles traveling above 40 mph, which had previously been roughly 5% of vehicles.
As for congestion, which is measured in several ways, it saw a slight increase. When looking at congestion rate, or the proportion of hours of the day in which congestion occurs, there was an uptick from 13% to 20% between the 2019 and 2020 study periods. In 2021, however, the congestion rate slipped back to 18%.
But did this congestion meaningfully impact travel time?
Travel time data showed that vehicle trips through the corridor were taking on average 124 seconds in 2019, and 129 seconds in 2021, an increase of only 5 seconds. The travel time data indicates that the uptick in congestion isn’t having a substantial impact on travelers’ trip length.
Tracking holistic infrastructure goals
When designing their vision and plans for Armour Road in 2016 and 2017, North Kansas City planners drew on Complete Streets, a transportation planning approach that helps cities and towns build safe and accessible mobility corridors that open up opportunities for biking or pedestrian traffic.
The approach targets more than one goal: it values safety, but also ease of use, efficient travel, connectivity, and equity.
In other words, Complete Streets is a multidimensional and holistic approach. And that makes the choosing and analyzing of metrics more challenging.
Due to limitations on staff time and the preventatively expensive nature of traditional methods, planners don’t typically measure before-and-after data to determine if a roadway improvement succeeded.
That’s why a mobility analytics-based approach is a helpful alternative, allowing on-demand before-and-after studies.
StreetLight processes vast amounts of location data from connected devices and contextualizes the data using parcel data and digital road network data. Finally, StreetLight’s Data Science team has developed proprietary methods to expand the sample and create reliable, validated Bike and Pedestrian Volume estimates.
The end result is a repository of multi-modal traffic patterns across North America’s vast network of roads, bike lanes, and sidewalks. This repository can be consulted for multimodal volume estimates, congestion rates, travel times, and more, for any period of time, on any facility, on demand.
This versatility allows planners a great deal of freedom in analyzing a diverse set of factors when conducting before-and-after studies, without needing to plan ahead to collect that data.
It also can lead to surprising revelations and, thus, more informed planning. For example, the finding that a significant share of bike activity happens at night could help planners focus on measures to ensure overnight safety.
Why before-and-after studies are so important for infrastructure planning
Traditional data collection methodologies have made it challenging to study the impact of changes to the built environment. Mobility analytics solve this challenge by allowing retroactive analysis. Planners can then build up a strong repository of empirical evidence on what does and doesn’t work for infrastructure planning.
As governments look to meaningfully reduce greenhouse gas emissions from transportation and improve health, equity, and livability, it’s critical to measure which changes move the needle—and which don’t.
This data can also shape public perception of infrastructure planning. Without real-world evidence of what a particular planning decision’s impact will be on the community, it’s easy to misdiagnose projected outcomes. The more data we have on how similar investments perform, the easier it becomes for practitioners to make informed decisions about their priorities and effectively explain those priorities to the government leaders and constituents they serve.
For example, measuring the impact of a road diet initiative on Rainier Avenue in Seattle led the city to expand the road diet further along the road, making one of Washington State’s most dangerous streets safer.
In the case of the Armour Road bike lane, the outcomes of this project—additional bike activity and limited congestion increases—can inform other localities’ planning and communication.