Exploring the underlying dimensions of elements affecting traffic congestion relief impact of transit

Document Type

Journal Article

Publication Date

2011

Subject Area

land use - planning, land use - transit oriented development, mode - mass transit, policy - congestion

Keywords

Global cities, Public transport, Congestion relief, Underlying dimensions

Abstract

In this paper a new approach for transit congestion relief measurement in urban areas is described. The paper reviews relevant transport data sources and describes how a comparable international transport database has been selected for this study. The elements affecting the congestion relief impact of public transport in global cities are explored. Factor analysis is used to identify the underlying dimensions of the measured elements from the readily available urban and transport data for a broad international spectrum of cities. The multivariate data analysis manifests three major dimensions of factors affecting congestion relief: (1) transit-oriented factor, (2) car-deterrence factor, and (3) urban-form factor. Finally, by using linear regression analysis, this paper has determined how these three dimensions are related to the congestion relief value of transit. The results of the regression analysis show that all three dimensions positively influence transit congestion relief. Car-deterrence factor has the strongest influence on transit congestion relief, followed by transit-oriented factor and urban-form factor. In addition, the regression model provides a quantitative link between city variables, transport characteristics and transit congestion relief without using comprehensive transport modelling approach. This quantitative link can provide insight to our understanding of the strength of these dimensions to transit congestion relief for urban areas.

Rights

Permission to publish the abstract has been given by Elsevier, copyright remains with them.

Comments

Cities Home Page:

http://www.sciencedirect.com/science/journal/02642751

Share

COinS