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 to represent networks, travelers, and environment, 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, at the same micro-level spatial-scale The approach can be extended to identify the spatial extent of potential pedestrian paths to these destinations. This method is sensitive to the characteristics of the environment and socioeconomics of the pedestrian and utilizes recent regional household travel surveys, pedestrian count data, and the wealth of detailed, spatially differentiated environmental data available throughout the Portland region. Ultimately, the products developed from the research will be assembled to provide a stand-alone tool to estimate various aspects of pedestrian demand – trip generation, trip distribution, and areas of potential pedestrian activity. This tool will add to the analytical methods available for transportation modeling as well as pedestrian and safety analysis, health assessments, and other pedestrian planning applications.