New Data Sources Change Traffic Design and Community PlanningPosted on Wednesday, June 17th, 2020 by Mike McKenna
In Traffic, tagged in Tags: data driven design
For years, traffic engineers and communities have relied on the same resources and methods to project and accurately count traffic. With more data readily available, they now have a range of alternatives, each using its own unique approach.
I recently met with Replica, a Kansas City based company whose software strives to help individuals understand the movement of people and goods. They use their programs to help communities answer questions like, “How many people are moving, where are they going, and why are they making the trip?”
To do this, they don’t rely on a single data source. Instead, they pull information from a variety of places. Some of these include mobile location, consumer/resident, land use/real estate, credit transaction, and ground truth data. Each offers its own advantages and disadvantages, but rolled together, it provides a more comprehensive picture.
Replica was originally designed to be used in these three ways. It can be a data source for an organization’s proprietary methods, a query tool, or a reporting source. Clients can pull traffic data for a particular segment of roadway or filter by county, school district, neighborhood, or city. From there, information can be accessed about the modes of transportation used, where a person lives, average household income, and more.
In addition to its ability to support traffic engineering, the recent COVID-19 outbreak has revealed new uses for the data. Replica has recently partnered with cities, like New York City, to help them make data-driven decisions based on movement patterns. As they continue to develop this offering, they are compiling high level data for the entire country. It is proving to be valuable to elected officials, healthcare organizations, and more.
Though many communities have not adopted a platform like Replica, larger cities are using traffic data and personal information to better serve their residents. We anticipate that as the technology continues to evolve it will become more accessible to towns of all sizes. Once the accuracy of the data is verified, solutions like these could have a significant impact on the way we design.