3-1: Influencing Travel Behavior via Open Source Platform
|Principal Investigator||Sean J. Barbeau, Ph.D.
Michael Maness, Ph.D.
|Final Report (DOI)||Available Soon|
|Policy Brief||Available Soon|
|RIP||View RIP entry|
Multimodal transportation such as transit, bike, walk, transportation network companies (TNCs) (e.g., Uber, Lyft), car share, and bike share are vital to supporting livable communities. However, activity data of travelers using these modes have been difficult to acquire. Recent research conducted under the National Center for Transit Research developed and deployed a proof-of-concept system to passively collect multimodal travel behavior data from opt-in users of a popular open-source mobile app for multi-modal information, OneBusAway (OBA). This earlier study concluded that while the origin and destination data collected from 74 users appear promising, an in-depth effort to evaluate the accuracy of the activity transitions being captured by the app is necessary prior to large scale studies that rely on the data.
This proposed project will further evaluate the data collected by the OneBusAway app. The accuracy and precision of the activity transition timing and location will be determined by comparing collected data against ground truth information. The research team will then compare the determined accuracy and precision of the data against the requirements for several activity-related research topics. Data from this tool, if proven accurate, could shed light on how first and last-mile connections could be improved, travel behavior of specific populations (e.g., older adults, people with disabilities), and as a basis for influencing and understanding changes in travel behavior, among many other research areas.