An Analysis of Transit Ridership in Plano, Texas PDF Download
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Author: Peter E. Ezinkwo
Publisher:
ISBN:
Category : Local transit
Languages : en
Pages : 184
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Book Description
Author: Peter E. Ezinkwo
Publisher:
ISBN:
Category : Local transit
Languages : en
Pages : 184
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Book Description
Author: Jack Lamkin
Publisher:
ISBN:
Category : Labor disputes
Languages : en
Pages : 100
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Book Description
Author: Texas Mass Transportation Commission
Publisher:
ISBN:
Category : Local transit
Languages : en
Pages : 270
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Book Description
Author:
Publisher:
ISBN:
Category : Older people
Languages : en
Pages : 50
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Book Description
Author: Han Park
Publisher:
ISBN:
Category :
Languages : en
Pages : 140
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Book Description
Transit ridership analysis has been advancing towards the use of disaggregate spatial and boarding data. This study attempts to improve the understanding of factors influencing transit ridership by estimating/comparing ridership models at the route, the segmented route, and the stop level in the Austin area. Spatial and statistic analysis methods are used in this study. The dependent variable is ridership at the transit route, the segmented route, and the stop level, whereas independent variables consist of traveler characteristics, land use, transit service characteristics, and other contextual factors. Spatial analysis is conducted using Geographic Information System (GIS) to compile data within a quarter-mile buffer from each transit stop, each segregated route, and each route. Linear and semi-log models of ridership are estimated using Statistical Analysis System (SAS). Initial analysis confirms the qualitative understanding that traveler demographics such as population and employment densities, ethnic background, and income significantly affect transit ridership. Land use composition, measured by the shares of single-family homes, multi-family homes, commercial, civic uses, as well as the total area of paved parking, all influence transit use. Service qualities such as headway and transfer opportunities also matter. Sensitivity tests of these factors affecting ridership are carried out to compare model performance among the route, segmented route, and the stop level analyses. It is expected that the study findings will help to better inform transit agencies and local communities in optimizing existing transit operations, planning for new services, and developing transit-friendly environments. Primary data were obtained from the Capital Metropolitan Transit Authority and the Census Bureau, and secondary data was processed by GIS analysis.
Author: Texas Mass Transportation Commission
Publisher:
ISBN:
Category : Urban transportation
Languages : en
Pages : 36
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Book Description
Author: North Central Texas Council of Governments
Publisher:
ISBN:
Category : Transportation
Languages : en
Pages : 32
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Book Description
Author: Charles River Associates
Publisher: Transportation Research Board
ISBN: 9780309062527
Category : Transportation
Languages : en
Pages : 168
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Book Description
Addresses transit's ridership and its share of the travel market. The research explored a variety of different public policies and transit management actions that can potentially influence transit ridership, particularly in comparison to local travel by private vehicle.
Author: Kirk E. Barnes
Publisher:
ISBN:
Category : Local transit
Languages : en
Pages : 36
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Book Description
Author: Ahmed Ismail Daqrouq
Publisher:
ISBN:
Category : Intelligent transportation systems
Languages : en
Pages : 189
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Book Description
Transit ridership is at the heart of transportation policy making and the success of any transit system. Urban planners have been focusing on the need to reduce car dependence and promote more sustainable transportation alternatives. Automobile dependence is a concern for many reasons including congestion in urban areas, pollution, and environmental damages caused by pollution. Switching to more sustainable and environmentally friendly transportation modes such as public transit is likely to be an effective solution to most of these problems. As an alternative to the private car, public transit is an efficient means to move large numbers of people within cities, and transit systems play an important role in combating traffic congestion, reducing carbon emissions, and promoting compact, sustainable urban communities (Taylor et al., 2009). In recent years, the introduction of intelligent transit information systems (ITIS) applications that provide real-time information to transit users created a new hope for increased transit ridership, however, its impact in facilitating increased Transit Usage is not clear yet. This study explores the factors affecting transit ridership including ITIS and selects the Dallas Area Rapid Transit (DART) as a case in a large metropolitan setting for this research. In order to achieve this purpose, the research examines the factors affecting rail, bus, and transit ridership. In addition, this study attempts to fill some of the gaps that exist in the literature by exploring the impact of intelligent transit information systems (ITIS) on transit ridership, and how its availability has affected transit ridership since 2012. The study adopts a monthly time series perspective (2007 to 2017) to enable the researcher to examine changes in transit ridership over a 10-year period and the incremental exposure to ITIS technology. This enables the research to capture any changes in ridership over this 10-year period, few years before to few years after the implementation of ITIS transit applications, in addition to any seasonal changes. Most previous studies of transit ridership have not included ITIS as one of the variables thought to influence transit ridership. Therefore, the disparities among the findings of empirical research completed to date point to the necessity for further study. This study addresses these shortcomings by exploring multiple factors measuring population, technology, geography, and socioeconomic characteristics. This is examined through using Time Series / Multiple Regression methods on the dataset to estimate the relationship between the models' variables to answer the research questions related to demand for transit ridership in the DFW area. In this type of research quite frequently, one is interested in interpreting the effect of a percent change of an independent variable on the dependent variable, which we can achieve through a double-log (log-log) model. As such, the elasticity of demand for transit with respect to some of the factors in the model such as percent change in fare, income or the research question variable, ITIS usage, are explored and policy implications out of these elasticities are discussed. Finally, it has been argued that ITIS reduces negative aspects and cost of using transit through providing information, saving time and other attributes, and makes transit more competitive with the automobile. Therefore, it behooves us to include also some measure of auto ridership in the models. In order to measure the responsiveness of demand for transit to a relative change in the price related to auto usage, we examine cross-price elasticity of demand for transit and how cross-price elasticity of demand could help us in measuring possible shifts from car to transit as an effect of ITIS usage. We think this research provides a significant contribution to transportation planning literature.
