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Improving Immersive, highly realistic in-lab, cycling experiences for analyzing active travel

dc.contributor.authorDaziano, Ricardo
dc.date.accessioned2021-12-06T20:21:08Z
dc.date.available2021-12-06T20:21:08Z
dc.date.issued2021-09-30
dc.descriptionProject Descriptionen_US
dc.description.abstractIn recent years, the continuous growth of private cars, the tight supply of land resources and, the continuous poor air conditions have led policy makers to advocate for sustainable public transportation. Bike sharing systems have been introduced in many cities and developed rapidly worldwide, due to its advantages in reducing environmental pollution and alleviating traffic congestion. It is recognized as a strategic tool to integrate public transportation and promote sustainable urban transportation. Cities around the world seek to reshape urban transportation to a greener and healthier way with the help of bike sharing systems. However, with the development of bike sharing systems, many challenges related to their operation have not yet been well solved, including modeling the demand and encouraging users to purchase memberships. This project focuses on modeling the demand of bike sharing systems and exploring the factors that affect users’ subscription memberships, in the context of the Citi Bike initiative in New York City. An online survey was designed to collect data of both characteristics and hypothetical decisions of a discrete choice experiment. Discrete choice models are built to give insights into users’ choices.en_US
dc.description.sponsorshipU.S. Department of Transportation 69A3551747119en_US
dc.identifier.urihttps://hdl.handle.net/1813/110363
dc.language.isoen_USen_US
dc.rightsAttribution 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.titleImproving Immersive, highly realistic in-lab, cycling experiences for analyzing active travelen_US
dc.typefact sheeten_US
schema.accessibilityFeaturereadingOrderen_US
schema.accessibilityFeaturestructuralNavigationen_US
schema.accessibilityFeaturetaggedPDFen_US
schema.accessibilityHazardunknownen_US

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