Is Parking Essential to Transit-oriented Development?

Is Parking Essential to Transit-oriented Development?

by Chongyuan Wang

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Transit-oriented development (TOD) is accepted to be a promising urban planning strategy for long-term sustainability, equity, livability, and prosperity in cities. The debates over the balance and interaction continue whether TOD actually increases transit ridership and reduces vehicle miles traveled (VMT) in different sizes of spatial areas. Among those factors that affect the ridership, parking policy appears inconsistent with the underlying benefits of TOD. The thesis intends to examine whether the VMT reduces and transit ridership increases in TOD, and measure the impact of parking on VMT reduction and transit ridership enlargement. The San Francisco Bay Area is chosen as the study area. The thesis places emphasis on spatial analysis and statistical modeling for the methodology. The spatial analysis performed in the thesis utilizes a Geographic Information System (GIS) software to identify the location, scale and characteristics of TODs in study areas. Thus, what and where are the TODs can be addressed. For statistical modeling, the thesis chooses a multi-level model mixed with random and fixed effects to develop for the analysis. A census tract level and an individual trip level factors are combined as fixed effects to estimate simultaneously. Additionally, the thesis introduces a discussion on parking policies and innovative approaches in the context of the likely future trends. Through a series of logically ordered questions and approaches, the thesis is aiming to shed new light on the research question that parking is essential to TOD and needs demand management. Developing TOD in suburban areas would help to increase transit ridership and reduce VMT on the regional scale. The results unveil the evidence that parking spaces and distance to transit stations of park-and-ride have a significant impact on transit usage and vehicle miles traveled in the Bay Area. The TOD areas are highly likely to have lower GHG emissions.

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