Pedestrians, Pedestrians -- Safety measures
There is growing support for improvements to the quality of the walking environment, including more investments to promote pedestrian travel. Planners, engineers, and others seek improved tools to estimate pedestrian demand that are sensitive to environmental and demographic factors at the appropriate scale in order to aid policy-relevant issues like air quality, public health, and smart allocation of infrastructure and other resources. Further, in the travel demand forecasting realm, tools of this kind are difficult to implement due to the use of spatial scales of analysis that are oriented towards motorized modes, vast data requirements, and computer processing limitations.
To address these issues, a two-phase project between Portland State University and Oregon Metro is underway to develop a robust pedestrian planning method for use in regional travel demand models. The first phase, completed in 2013, utilizes a tool that predicts the number of walking trips generated with spatial acuity, based on a new measure of the pedestrian environment and a micro-level unit of analysis. Currently, phase two is building upon this tool to predict the distribution of walking trips, connecting the origins predicted in phase one to destinations. This presentation will focus on phase two, which is one of the first studies to focus on destination choices among pedestrians separately from other modes. The approach can be extended to identify the spatial extent of potential pedestrian paths to these destinations. Ultimately, the products developed from the research can estimate various aspects of pedestrian demand – trip generation, trip distribution, and areas of potential pedestrian activity. These tools will add to the analytical methods available for transportation modeling, pedestrian and safety analysis, health assessments, and other pedestrian planning applications.
Muhs, Christopher D.; Clifton, Kelly; Singleton, Patrick Allen; and Schneider, Robert J., "Development of a Pedestrian Demand Estimation Tool: a Destination Choice Model" (2015). Civil and Environmental Engineering Faculty Publications and Presentations. 307.