Florida DOT Case Study

In 2013, MetroPlan Orlando became one of the first planning agencies in the world to use Strava Metro data to make better decisions about where to improve bicycle and pedestrian infrastructure. When Florida’s Department of Transportation saw how helpful the Metro data was for the Orlando area, the state decided to become a Metro client and make the statewide data available to any city, town, or DOT region that wanted it.

When it comes to transportation planning, the State of Florida is focused heavily on safety. In part, that’s because road safety is important to Floridians. But it’s also because, safety-wise, Florida has a lot of room for improvement. In 2015, the Centers for Disease Control and Prevention found that Florida has the highest rate of bicycling deaths of any state in the nation. At 0.57 annual bicycle deaths per 100,000 people, Florida’s rate is more than double the national average of 0.23.

“Since about 2012, we have made a concerted effort to reduce the number of pedestrians and cyclists who die or are seriously injured,” said Shaun Davis, a data and GIS analyst at FDOT’s Safety Office, “but when we try to do that, we run into the issue of we don’t have a lot of data. We can go and look at the crash location data, but before Strava we didn’t have a clear understanding of how many cyclists were out there, and what roads they were using. That’s what interested us in using Strava as one part of our understanding of pedestrian and bike crashes.”

Davis is now the lead contact at FDOT for Strava Metro data. He receives Metro data periodically, uploads it to the State’s website, and fields special requests from people throughout the state who want to use it. “We provide the data for the whole state,” Davis explained, “so people can pull down data for a specific month, weekend, or the whole year, or for different modes, and parse out what they need for their project.”

Examples of FDOT Projects Informed by Metro Data

Street Sweeping in District Five

District Five of the Florida DOT encompasses a large area in the middle of the state, including the cities of Orlando, Ocala, Daytona Beach, and Palm Bay, and has a population of four million residents.

Deborah Tyrone is the Bicycle/Pedestrian Manager for the district and has been an advocate for using Metro data since MetroPlan Orlando first partnered with Metro in 2013. Since then, Tyrone has built D5 TransPed, a custom interactive bicycle and pedestrian planning tool that overlays Metro data and other data into an ArcGIS map of the district that’s available to the public.

In addition to more typical uses of Metro — using the data to help plan bicycle infrastructure improvements — Tyrone recently began a pilot project that uses the Metro data to inform street-sweeping routes. The idea is that, since the DOT street sweepers can’t sweep every road, they can prioritize the roads with heavy bicycle traffic evident in the Metro data. “We have barrier islands here and bridges that lead out to them,” Tyrone said. “We have a lot of riders on some of these bridges, and there’s nowhere for the litter to go, so we’re sending the sweepers on these routes frequently instead of putting them on much bigger loops less often.”

I-75 Interchange Planning in District Seven

District Seven has a population of almost three million people and includes the cities of Tampa, St. Petersburg, and Clearwater. Matthew Weaver is the traffic safety engineer for the district and spends his time identifying areas that need safety enhancement and guiding new projects on safety issues.

“Once we heard from Shaun Davis that we had data available from Metro, we brainstormed with our bicycle/pedestrian safety specialist and started coming up with ideas for how to use the data,” Weaver said. They gravitated toward the heat map and showed it to a project manager who is planning an upgrade of a busy interchange between I-75 and State Road 56. The heat map showed significant cyclists on both sides of the interchange, but very few crossing over the highway. “So when they were trying to decide which bicycle facilities to put in this upcoming big project, we were able to steer them towards providing bicycle lanes,” Weaver said.

That project won’t be built for another four years, but putting the bicycle facilities in the plan now is crucial because adding them later is more difficult and more expensive. “The Metro data was definitely able to make a difference in the scoping of the project,” Weaver said, “and it’s nice to have a definitive resource like Metro to show to project planners.”

Safety Enhancement on Gulf Boulevard

When looking more closely at the Metro data, Weaver discovered that Gulf Boulevard, in Clearwater, is the second busiest north-south route for bicycles in Pinellas County, other than the Pinellas Trail, a multi-use rail trail. Based on that information, Weaver decided to do a safety enhancement along the corridor, including green pavement markings for bike lanes. “Basically, we used the Metro data to say, This is where the most bicyclists are in the area, so let’s try this bike safety enhancement here instead of anywhere else,” Weaver said.

As part of that project, Weaver worked District Seven’s roadway design engineer, Allan Urbonas. Urbonas was in the midst of re-paving and re-striping Gulf Boulevard and trying to decide how much space to apportion to automobiles and bicycles. Initially, he planned to have 11-foot automobile lanes with 4-foot bike lanes. But when he and Weaver examined the Metro data, they noticed heavy bicycle use, and decided to make the automobile lanes a little narrower and the bike lanes wider. “The Metro data gives me an idea of the bike traffic, and that can be a tool we can use to exercise our engineering judgment on how we distribute the width of pavement between vehicles and bikes,” Urbonas said.

Conclusion

When the Florida DOT decided to acquire the Metro data for the entire state, it was taking a wisely holistic view of transportation planning. People routinely travel between towns, cities and counties via bicycle, so data for particular areas of a state is not going to show the entire picture of cyclist activity. And, as shown in the examples above, when Metro data is made available to an entire state, it turns towns, cities, and districts into data laboratories that can experiment and share knowledge and expertise.

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