Browsing by Subject "Bicycling"
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Item Campus on two wheels : increasing bicycle mode share on the UT-Austin campus(2012-08) Rosenbarger, Elizabeth Mae; Dooling, Sarah; Machemehl, Randy B.This research report examines infrastructure strategies to increase the bicycle commute mode share. By analyzing existing conditions and results from on-campus participatory events, recommendations to improve and increase bicycling at the University of Texas at Austin campus are proposed. This report includes a literature review of sustainable transportation and university campuses, bicycle infrastructure best practices, bicyclist route preferences, evaluations of bicycle infrastructure, the role of bicycling in past master plans at the UT-Austin campus, and bicycling in other university’s plans. Existing conditions analyze the characteristics of streets in and around campus and data from the Bike-UT survey is discussed. Participatory research events are described and their findings analyzed to better understand how current bicyclists perceive spaces on campus and make their route choices. Finally, considering best practices, existing conditions, and findings from campus research events, recommendations are proposed to increase the bicycle mode share on the UT-Austin campus.Item A new estimation approach for modeling activity-travel behavior : applications of the composite marginal likelihood approach in modeling multidimensional choices(2011-08) Ferdous, Nazneen; Bhat, Chandra R. (Chandrasekhar R.), 1964-; Machemehl, Randy; Abrevaya, Jason; Waller, Steven; Stolp, ChandlerThe research in the field of travel demand modeling is driven by the need to understand individuals’ behavior in the context of travel-related decisions as accurately as possible. In this regard, the activity-based approach to modeling travel demand has received substantial attention in the past decade, both in the research arena as well as in practice. At the same time, recent efforts have been focused on more fully realizing the potential of activity-based models by explicitly recognizing the multi-dimensional nature of activity-travel decisions. However, as more behavioral elements/dimensions are added, the dimensionality of the model systems tends to explode, making the estimation of such models all but infeasible using traditional inference methods. As a result, analysts and practitioners often trade-off between recognizing attributes that will make a model behaviorally more representative (from a theoretical viewpoint) and being able to estimate/implement a model (from a practical viewpoint). An alternative approach to deal with the estimation complications arising from multi-dimensional choice situations is the technique of composite marginal likelihood (CML). This is an estimation technique that is gaining substantial attention in the statistics field, though there has been relatively little coverage of this method in transportation and other fields. The CML approach is a conceptually and pedagogically simpler simulation-free procedure (relative to traditional approaches that employ simulation techniques), and has the advantage of reproducibility of the results. Under the usual regularity assumptions, the CML estimator is consistent, unbiased, and asymptotically normally distributed. The discussion above indicates that the CML approach has the potential to contribute in the area of travel demand modeling in a significant way. For example, the approach can be used to develop conceptually and behaviorally more appealing models to examine individuals’ travel decisions in a joint framework. The overarching goal of the current research work is to demonstrate the applicability of the CML approach in the area of activity-travel demand modeling and to highlight the enhanced features of the choice models estimated using the CML approach. The goal of the dissertation is achieved in three steps as follows: (1) by evaluating the performance of the CML approach in multivariate situations, (2) by developing multidimensional choice models using the CML approach, and (3) by demonstrating applications of the multidimensional choice models developed in the current dissertation.Item New life for downtown alleys : creating an open space network in downtown Austin, Texas(2009-05) Hammerschmidt, Sara M.; Sletto, BjørnThis report looks at the system of alleys that exist in downtown Austin, Texas and proposes a way to integrate them into the open space network within the area by creating a series of alley connections. Through analysis of case studies from other cities and public space theories, alternative methods of use are suggested for implementation throughout the alley system, including “green”, activity based and pedestrian and bicycle priority throughways. The next steps needed to create a Downtown Alley Master Plan and begin alley renovations are also discussed. The renovation of spaces that typically contain unsightly uses and activities can help create attractive places for people to congregate rather than places that people generally avoid.Item Programmatic and fixed variables and their effects on commuting by bicycle in two cities : a descriptive case study(2007-05) Barrera, Nadia Mojica; McMillan, Tracy E.Rapid growth and congestion within the City of Austin amplify the need to plan for and incorporate multi-modal infrastructure, facilities and policies. According to the 2005 US Census sample, the City of Austin falls short of many other bicycle-friendly cities in the number of commuters riding bicycles to work. Experiencing the achievements towards a more diverse modal share in other cities prompted the author to evaluate programmatic bicycle planning and fixed variables (geographic, demographic, and climatic conditions) in a descriptive multiple-case study. Data was collected from the City of Austin and the City of Tucson; both with significant university populations, and descriptive comparisons were made between the two cities. Findings show that the City of Tucson met most of the predicted values of ideal demographic, climatic, and programmatic variables. In addition, the City of Tucson has a well-staffed bicycle and nationally recognized regional bicycle program. Recommendations for the City of Austin include improving upon all programmatic variables (education, engineering, evaluation, enforcement and encouragement) through a new local and regional bicycle plan, and a legally mandated focus on supportive bicycle legislation, policies and enforcement.Item Sociotechnical co-production of planning information : opportunities and limits of crowdsourcing for the geography and planning of bicycle transportation(2019-05) Griffin, Greg P.; Jiao, Junfeng; Rosenbloom, Sandra; Zhang, Ming; Lease, Matthew; Stephens, KeriUrban planners deploy civic technologies to engage publics with digital tools in a relative vacuum of theory, understanding of challenges, or benefits. The issue, Lewis Mumford might have framed, could be of authoritarian and democratic technics—whether the technology contributes more to top-down control or bottom-up understanding. Building from collaborative planning theory, co-production suggests ways people can leverage technologies to build urban solutions with or without professional planners. Empirical research shows that crowdsourcing to address planning questions with digital civic platforms can help fill or mitigate information gaps, including support for bicycling as a safe and comfortable travel mode. However, no research has addressed how crowdsourced information for bicycle planning offers new insights for safety, the geography of participation, or how its social construction impacts its representation of bicycling in a community. A new framework for evaluating co-productive planning is proposed, considering legitimacy, accessibility, social learning, transparency, and representation (LASTR). This dissertation addresses these concerns of safety, geography, and social construction through the LASTR framework using mixed-methods case studies in Portland, Oregon, and Austin, Texas. Bicycle volumes and street ratings through the crowdsourcing platform, along with geographic information system environmental data, and interviews with thirty-three informants form the basis for evaluating these issues. Viewed from pragmatism and social construction of technology, the social processes of planning and technological developments are intertwined and traced in tandem. The first three chapters frame the problems, build a background in theory, and describe the research questions, planning contexts, and data for analysis. The next three chapters are empirical, evaluating the use of crowdsourced information for bicycle safety, comparing the geography of crowdsourced participation with in-person meetings from both cities’ most recent bicycle planning process, and tracing the sociotechnical representation of crowdsourcing bicyclist information through interviews and case materials. The final chapter summarizes the findings and implications for practice and research. This dissertation shows that the biased representation of bicycling in these two crowdsourcing cases pose opportunities to identify safer bicycling routes and expand public participation geographies, but could exacerbate problems with aligning public improvements with the users of a specific technological approach. Further, the construct of crowdsourcing for urban planning remains flexible and therefore merits further study and knowledge transfer for practitioners and students.