Webinar Recording: Improving the Quality and Cost Effectiveness of Multimodal Travel Behavior Data Collection

April 22, 2020

Improving the Quality and Cost Effectiveness of Multimodal Travel Behavior Data Collection

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, current data collection techniques for multimodal travel behavior, including apps built specifically for travel behavior surveys, have limitations (e.g., significant negative impact on battery life, user acquisition) which prevent a better understanding of significant real-world challenges (e.g., multimodal traveler choices, relationships between travel behavior and health).

This webinar discusses the results of a recently completed research project funded by the National Center for Transit Research, “Improving the Quality and Cost Effectiveness of Multimodal Travel Behavior Data Collection”. In this project, the research team developed and deployed a proof-of-concept system to collect multimodal travel behavior data on an ongoing basis directly from users of a popular open-source mobile app for multi-modal information, OneBusAway (OBA). To overcome battery life challenges, the research team used the Android Activity Transition API, which leverages hardware advancements in modern mobile phones.

This webinar presents the technology used to implement this data collection tool, as well as the results of a pilot deployment to 676 beta testing users. Over 10 weeks, 74 users opted into the study without any incentive and contributed 65,582 trips. Key concerns discussed for data collection when conserving battery life include the timeliness and accuracy of data. Download Report

Presenter: Sean J. Barbeau, Ph.D., Center for Urban Transportation Research

Sean J. Barbeau, Ph.D. is the Principal Mobile Software Architect for R&D at the Center for Urban Transportation Research at the University of South Florida. His research interests include multimodal mobile apps, open-source software, standardized open data, and cybersecurity for mobile phones and transportation infrastructure. Dr. Barbeau holds a B.S. and M.S. in Computer Science from USF as well as a Ph.D. in Computer Science and Engineering from USF.