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Improving immersive, highly realistic in-lab, cycling experiences for analyzing active travel
dc.contributor.author | Daziano, Ricardo A | |
dc.contributor.author | Yoon, So-Yeon | |
dc.contributor.author | Wang, Cacho | |
dc.date.accessioned | 2021-12-02T21:40:44Z | |
dc.date.available | 2021-12-02T21:40:44Z | |
dc.date.issued | 2021-09-30 | |
dc.identifier.uri | https://hdl.handle.net/1813/110361 | |
dc.description | Final Report | en_US |
dc.description.abstract | In 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 sustainable public transportation. Bike sharing system has been introduced by many cities and developed worldwide rapidly, due to its advantages in reducing environmental pollution and alleviating traffic congestion (Fishman, Washington et al. 2015). It is recognized as a strategic tool to integrate public transportation and promote sustainable urban transportation (Martin and Shaheen 2014). Cities around the world seek to reshape urban transportation to a greener and healthier way with the help of bike sharing system. Since bike sharing systems were put into use, the service has gone through several generations. From the initial free bike system (DeMaio 2009) in the 1960s, to the coin- deposit system (Shaheen, Guzman et al. 2010), and then to the information technology-based system (Wang, Zhang et al. 2010), it has now developed into the multimodal system (Mátrai and Tóth 2016). However, with the development of´ bike sharing system, many challenges related to its operation have not been well solved, including modeling the demand and encouraging users to purchase memberships. This report focuses on modeling the demand of bike sharing system and exploring the factors that affect users’ subscription membership, in the context of the Citi Bike initiative in New York City. It is organized as follows. Chapter 1 is the literature review of related topics. Chapter 2 describes the data as well as the context of the survey. Chapter 3 develops different discrete choice models and discusses estimates of these models, with focuses on both attributes of a bike sharing system pass and socio-demographics of users. Conclusions found through these models are also discussed in this part. | en_US |
dc.description.sponsorship | U.S. Department of Transportation 69A3551747119 | en_US |
dc.language.iso | en_US | en_US |
dc.rights | Attribution 4.0 International | * |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | * |
dc.subject | Discrete choice model | en_US |
dc.subject | Cycling | en_US |
dc.subject | Subscription | en_US |
dc.subject | virtual reality | en_US |
dc.title | Improving immersive, highly realistic in-lab, cycling experiences for analyzing active travel | en_US |
dc.type | report | en_US |
schema.accessibilityFeature | readingOrder | en_US |
schema.accessibilityFeature | structuralNavigation | en_US |
schema.accessibilityFeature | taggedPDF | en_US |
schema.accessibilityHazard | unknown | en_US |
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Except where otherwise noted, this item's license is described as Attribution 4.0 International