Novel Approaches to Model Travel Behavior and Sustainability Impacts of E-Bike Use

EVER researchers Cherry and Azad (UTK) and MacArthur (PSU) have partnered with Bosch E-Bike Systems to measure real-world travel behavior and assess the sustainability impacts of those choices. This National Science Foundation (NSF) funded project develops novel smartphone-based machine learning efforts to assess trip patterns of a panel of e-bike users over two years. This supervised machine learning approach provides a wealth of data on actual e-bike use and avoids some of the pitfalls associated with surveys. However, this dataset was compared with ad-hoc travel surveys to supplement passive data collection and, using machine learning algorithms, create the largest and richest dataset to support the growth of e-bike use as a transportation option. The data helps estimate implications on environmental sustainability using behaviorally sensitive environmental models. This four-year project is ongoing and has already amassed a wealth of data and informed policy.
Publications: The E-Bike Potential: Estimating regional e-bike impacts on greenhouse gas emissions
Project: Mobility by E-Bike Study