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Unique Computational Methods to Model Rideshare Behavior and Estimate Applications for Transit

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Document pages: 20 pages

Abstract: Ridesourcing services have become important part of local transportation ecosystems glob-ally. They offer new new opportunities to access rides for travelers of all kinds, and also new ways to think about variants of traditional transit and affordable transportation for those without auto access. At the same time, the tension between private companies who own and have few incentives to share data has grown. Cities want to understand trips and travel trends while private sector companies view user data and trip data as a part of their most valued intellectual property. In response to this tension this paper uses a unique and original computational approach to estimate and explore trends in ride sourcing data, without having to exchange that data.This is modeled and simulated on networks in both San Francisco and Boston, and followed by discussion of our results and how they can be informed how planners and engineers can better plan for the future of local transport using using sophisticated computational data simulation methods.

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