The BUILD Discretionary Grant FY2020 deadline is fast approaching on May 18th. It’s available for planning and capital investments in order to upgrade American infrastructure such as roads, bridges, transit, rail, ports, or intermodal transportation. DOTs, transit agencies, and several other public agencies are eligible to apply for these grants. Since 2009, there have been eleven rounds of BUILD (previously TIGER) grants.
While these grants are competitive, we’ve seen that using Big Data adds a unique level of measurable detail that offers advantages for both urban and rural areas. Although BUILD applications are due soon, these takeaways can apply to any grant application.
The 7 Best Data Sets for Grants
Over the last few years, we’ve helped more and more agencies use our data to apply for similar grants. What works? Overall we see seven key metrics bolstering most types of grant applications:
1. Traffic counts
These building blocks measure levels of traffic for any road, from busy urban highways to neighborhood streets, to rural roads where traditional counts aren’t current or even available at all. Bonus: they can be used to analyze Vehicle Miles Traveled to evaluate air quality benefits of a project.
Using Big Data to determine speed can help grant applicants identify the intensity of congestion on roadway networks. This data can also be used to measure the benefits of proposed congestion reduction strategies, quantify travel time savings, and in turn, establish a baseline for calculating economic benefit.
3. Freight travel patterns
Big Data offers the ability to segment commercial trucks from personal vehicles, and analyze Origin-Destination (O-D) pairs, travel times, parking data, and more.
4. Bike and pedestrian travel patterns
Demonstrate projected health benefits by identifying hot spots where vehicle trips can be converted to non-motorized modes.
5. Top routes
When you know the most common O-Ds for trips crossing a bridge, you can assess the travel market, predict the benefits of improving that piece of infrastructure, and show why that project should be prioritized.
6. Before-and-after studies
Since we can’t predict the future, determining the benefits of a proposed project can be challenging. Using Big Data for before-and-after studies of similar projects in other regions can help.
7. Demographic and visitor information
Learn more about who’s visiting your destination to contextualize analyses of economic benefits due to tourism. Demographic data can also inform goals relating to equitable distribution of projects.
Big Data in Action: Butler, Pennsylvania
A great example of these metrics in action is in Butler County, Pennsylvania. They applied for the $100M INFRA grant from the U.S. Department of Transportation last summer. Kelly Maurer, Operations Engineer for Cranberry Township, coordinated with Whitman, Requardt and Associates on traffic data for the application.
Within StreetLight InSight, WRA ran analyses looking at current traffic volume, segment speed, segment delays, congestion and O-D analysis. “The best part was we were able to get the results within a day, including the figures,” Maurer said. “It saved us time, and obtaining the origin and destination information was invaluable to show the regional benefit of this grant.”
We hope this gives you some ideas as you prepare to apply for BUILD or any other grant application. If you have any questions, please feel free to contact our team.