Smartphone information and transportation demand modeling: An analysis of transportation network companies
PI: R. Church, UC Santa Barbara
Abstract: Data from mobile-phones is currently being used to derive a variety of properties about a transportation system, like average speeds and bottlenecks. Mobile data on an individual’s trips could even be collected and analyzed but is prevented by legitimate privacy issues. There is one major exception, as Transportation Network Companies (TNCs) regularly collect and analyze demands for trips based upon a smart phone platform. The use of the smart-phone in transportation demand modeling has been embraced by TNCs such as Lyft and Uber, which are defined as internet-based companies that connect travelers with drivers for fee-based livery-like service. Such a technological embrace by TNCs has proven to be a “disruptive innovation” in the transport industry via groundbreaking data collection methods and analyses - a key being TNCs measuring the latent demand for their services. Given the general lack of understating of latent demand on behalf of transportation modelers and the age of TNCs, we propose three major goals: 1) review the TNC operational model as a new transportation industry, 2) review the data collected and its use by this industry and 3) develop a framework in which to use TNC data to analyze latent trip demand.
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