Where: Room 204 of the Distance Learning Center Wing of the Urban Center at PSU
Follow this link on the day of the seminar to stream it live.
New technologies such as smart phones and web applications constantly collect data on individuals' trip-making and travel patterns. Efforts at using these "Big data" products, to date, have focused on using them to expand or inform traditional travel demand modeling frameworks; however, it is worth considering if a new framework built to maximize the strengths of big data would be more useful to policy makers and planners.
In this presentation Greg Macfarlane will present a discussion on elements of travel models that could quickly benefit from big data and concurrent machine learning techniques, and results from a preliminary application of a prototype framework in Asheville, North Carolina.
Dr. Macfarlane is an analyst in the Systems Analysis Group of WSP | Parsons Brinckerhoff, developing and applying advanced travel demand models. His research and expertise includes trip-based models, activity-based models, integrated land-use/...Read more