People ask us all the time: does a popular microtransit service ever lead to the addition of fixed-route service? The short answer is yes. For a good example of how this works, just take a look at Sioux Falls.
When Via and Sioux Area Metro rolled out city-wide microtransit service as part of the SAM Reimagined Plan to integrate buses, on-demand service, and paratransit, overall transit ridership surged. Adding vehicles to the fleet to meet high demand might seem like the obvious solution, but we took a more strategic, data-driven approach.
Ridership data from the city’s microtransit service revealed latent demand for high-traffic routes. Once demand was high enough to justify adding fixed-route service, we shifted part of the microtransit budget to extend bus lines to new destinations like the airport and add additional early morning runs on select routes, ultimately freeing up microtransit seats for riders whose trips aren’t served by the city’s nine bus routes.
A consistently improving transit network requires three key components. Ridership data informs changes to better aggregate rides and improve on-time performance across the network. Dynamic operations implement the updates. Then, intermodal journey planning apps guide riders to the most efficient mode and help them successfully navigate the network changes.
Sioux Falls isn’t alone in making these data-backed upgrades. Utah’s High Valley Transit also used microtransit data to introduce two new bus lines and updates to existing routes in July 2024, and Arlington, Texas launched Arlington Express using similar insights.
As cities grow and travel patterns change, data allows decision-makers to iterate quickly and make updates that better reflect observed trip durations and traffic patterns, ultimately driving ridership across the entire network.
