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Analytics and Bikes: Riding Tandem with Motivate to Improve Mobility
Wednesday 2 September, 11am-12pm AEST via Zoom Webinar.
Professor Shane Henderson, Cornell University
In this lecture, Professor Shane Henderson discusses how mathematics, statistics and computational methods improved bike sharing systems. Professor Henderson and his team have worked with Motivate, the operator of the systems in, for example, New York, Chicago, and San Francisco, to innovate methods for managing both their day-to-day operations and to provide insight on several central issues in the design of its systems. Key questions tackled relate to the placement of bikes and docks, methods to handle surges in demand during peak periods, and the design of a crowd-sourcing scheme to improve "balance" in the system. On this last point, a bike station is balanced if, most of the time, it is neither empty nor completely full. To avoid the former so that people wanting to go for a ride can usually find a bike. And avoid the latter so that bikers returning bikes can find an empty dock into which they can return their bike. Their work has resulted in fundamental changes in the way Motivate runs its bike-sharing programs. For example, the Bike Angels program in New York City yields a system-wide improvement comparable to that obtained through Motivate’s traditional rebalancing efforts, at far less financial and environmental cost. This required a mixture of statistics, mathematics and computation.
Register here: https://bit.ly/39N1Iyk
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