There’s an intersection in Seattle located in the Madison Park lakeside neighborhood where a ½ mile hill leads right into a populated business district. There sits Seattle’s busiest Starbucks location and a Wells Fargo Bank. This arterial connection is both the neighborhood’s busiest intersection for pedestrians and a city-designated school crossing location. Due to the rampant speeding and sight-line problems with this location, people walking often have difficulty crossing the street without trepidation.
Busy intersection at East Madison Street and McGilvra Boulevard East in Seattle
It took a serious collision between a cyclist and a pedestrian to force the city to try and fix the problems with the intersection. That’s where Bob Edmiston, his team from Seattle Neighborhood Greenways, and volunteers from Tableau saw an opportunity to make difference.
Their success would all depend on the data.
The Long and Winding Road to Funding
The plan for Seattle Neighborhood Greenways was to conceptualize and implement a safer intersection strategy for pedestrians. First, the team secured a $90,000 grant through Madison Park Community Council to enable the Seattle Department of Transportation (SDOT) to redesign the intersection.
However, to secure the addition $390,000 necessary to implement the changes, they would need to prove that the redesigned intersection would actually solve a problem. On top of that, there is a competitive pitching process for allocating grants in Seattle divided by district. Edmiston and his team were competing for the top spot against 15 other grant projects from the area. After initially failing to convince the decision makers of the value of the project by using an emotional appeal, a more persuasive approach was desperately needed.
If the team didn’t win the grant right now, their project would be dead.
Answering the Call with Data
Seattle Neighborhood Greenways sensed that they needed quantifiable proof of the improved safety of their solution. To collect the evidence necessary for a persuasive argument, Edmiston built a traffic counter that could record gaps in traffic with millisecond precision and conducted a gap analysis of the intersection. Seattle Neighborhood Greenways volunteer Troy Heerwagen worked with Edmiston to visualize the data using Tableau Public for ease of understanding.
Edmiston made some key observations:
- During the critical 15-minute period before the morning school bell, there were only two opportunities with gaps long enough to walk across the street.
- Crossing distance reductions provided by the curb extensions would reduce the crossing time enough to triple the number of safe crossing opportunities for pedestrians during the critical 30 minutes before the morning school bell, without requiring any changes to driver behavior or roadway function.
After presenting the new data and logic to the East District Neighborhood Council, the people responsible for funding decisions were convinced that the project would, in fact, produce the safety outcomes it promised. They reversed their earlier decision to not fund the project and chose to make it their top priority for 2017 funding.
Don’t Underestimate the Data
Edmiston reminds us to not underestimate the data, when he says,
“data matters, counts matter, gap analysis matters. We would have been dead in the water without it. But it’s about being able to show data in a way people can understand and relate to. That’s an equally important part of the problem.”
If it weren’t for the data collected, Seattle’s busiest intersection would still be dangerous for pedestrians. More so, it was the way team presented the data through visualization that made it digestible and accessible to everyone.
Miovision is passionate about enabling other change-minded individuals to use data to justify their road safety solutions.
Want to learn more how we can help you leverage meaningful data? Contact us today.