Stressed While Biking? Stress Maps Help Identify Infrastructure Priorities

I really enjoyed our second experiment with the TU Delft PhD students because I think it could be extremely useful to how we prioritize the development of bicycle infrastructure in my hometown.

We created a rubric for grading the “stress level” of bicycle infrastructure, then we rode our bikes around town and "graded" different routes based on that rubric. This data can be used to create a bicycle stress map like the one pictured below. Some places, like Madison, Wisconsin, have created phone apps similar to Waze and Google Maps that allow people to choose a bike route based on the stress level of that route.

Pictured is a stress map of Madison, Wisconsin. 

We first split into groups. Each group generated a list of physical attributes of a street or route that might make a bike ride comfortable or stressful. For example, the type of bike lanes (if any) available, the width of the facility, the smoothness or bumpiness of the road, nearby greenery, traffic volume and more. Then, we came together as one big group and put all of our elements together and decided which ones we wanted to keep for our final survey. We ended up with a solid list of stress factors. There was also one survey question that asked, “How comfortable do you feel using this facility?” This was the dependent variable that we later correlated to the other variables to see which factors affected our stress/comfort level the most.

Here we are putting our list of attributes up on a piece of butcher paper to widdle down to the best ones!

Then, using a map of landmarks, we split up and biked different corridors between those landmarks. We stopped about three times between each landmark, labeling on the map our stop location and which two landmarks we were stopping between. At each stop, we would pull out our paper survey and respond to the questions we generated about the physical infrastructure of the segment, and how the segment made us feel.

The last step was entering all the data into a shared excel sheet. They were all either yes or no questions, or on a Likert scale. This made it easy to compare and analyze the data. We ended up with over 100 data points between all of our groups. To communicate the data, each group was asked to choose an independent variable (a stress factor) to compare to the dependent variable (how we felt) and put the data into a chart to show how they’re correlated.

My badass group!

My group felt that greenery really affected our stress level on each segment, so we chose to compare the level of greenery, notated on the survey as 1 - no greenery, 2 - some greenery, and 3 - a lot of greenery, to both our comfort level on the segment and a question which asked about the “bikability” of the segment.

As you can see, as the amount of greenery increases both the perceived bikability and the comfort level of the segment also increases! This is great information to share with decision-makers, not only because we want to incentivize biking and make it easier for people to bike, but also because greenery provides many other functions as well, such as reducing the heat-island effect that often occurs in dense urban environments, and absorbing CO2 from cars.

This was one of the least stressful routes, even though the ground was rough and there were a lot of pedestrians, because it was next to Prinsenhof Park.

This was one of the most stressful routes, even though it was a wide, smooth path, because it had little greenery.

I'd really like to create a bicycle stress map for the University of South Florida for our next iteration of our Campus Master Plan, which is currently being updated. I also would love to create one for the City of Tampa and even Hillsborough County since we have money coming in very soon from the 1% sales tax for transportation infrastructure. This would help us prioritize routes for bicycle infrastructure upgrades.