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ISSE Seed Project: Sustainable E-bikes: Naturalistic Behavior Approaches to Assess Sustainability

Team: Christopher Cherry, Civil and Environmental Engineering; Daniel Costinett, Electrical Engineering and Computer Science; Paul Frymier, Chemical and Biomolecular Engineering

2015-2016 Funded Proposal

Electric bicycles (also called e-bikes) are bicycles with a small battery-powered electric motor, used to assist the rider by adding power in conjunction with physical pedaling. E-bikes have gained recent popularity as an energy-efficient motorized mode of transportation. Over 150 million e-bikes were sold in Europe and Asia in the past ten years. The US market has been slower to adopt the new technology; only 200,000 were sold in 2013. The emergence of e-bikes in our transportation systems raises many questions not previously present in the absence of e-bike technology. The research team will develop widely deployable instrumentation to collect naturalistic behavioral data from e-bike riders. We will then use this data and survey results to make inferences about sustainability, safety, and operational sophistication (e.g. vehicle connectivity).

picture of e-bike
Specialized Turbo S

Naturalistic behavior analysis involves the collection of “real-world” use data, with little to no intervention by the observer. The research team will develop instrumentation that will be widely deployable at a low cost, be minimally intrusive to the components of the subject e-bikes, and will passively (i.e., minimal to no input needed from user) collect data. A long-term goal of this study is to widely deploy instrumented bikes with the assistance of industry. The instrumentation kit (physical hardware and a mobile device application) will collect power usage, vehicle performance, and GPS location data. The collected data will then be used to better understand how sustainability metrics are affected by changes in e-bike usage and travel behavior. In addition, we will investigate the efficacy of assessing safety-critical behavior with mildly instrumented equipment. Finally, collected data will be used to explore technological advancements in e-bike connectivity and sophistication. This can include safety sensors and warnings to user, routing based on geoboundaries, and coordination of the power control systems depending on e-bike operation and the environment.