Data Collection and Spatial Interpolation of Bicycle and Pedestrian Data – year 2 (2013-14)
PI: Michael Lowry (UI)
Co-Investigators: Yinhai Wang (UW), Mike Dixon (UI), Ahmed-Abdel Rahim (UI), Mark Hallenbeck (UW)
Dates: 07/01/2013 – 6/30/2015
It is very difficult to measure safety without knowing how many people use a facility. For this reason, millions of dollars and decades of research have sought to estimate and forecast travel demand, such as through the ubiquitous 4-step model. Unfortunately, existing methods are lousy for estimating pedestrian and bicycle volumes. In fact, most agencies forego expensive, data-intensive models and instead resort to simply using expert judgment when estimating pedestrian and bicycle volumes. Cities and state DOTs struggle to collect and utilize pedestrian and bicycle data in an effective and meaningful way.
This project will create new planning tools to estimate and forecast pedestrian and bicycle volumes. Local agencies and state DOTs can use the tools to help improve safety, prioritize capital improvement projects, and create transportation plans that improve overall quality of life by enhancing these modes.