Background

Conventional parking demand resources are unreliable for urban areas leading to uncertainty in the land development process for the various stakeholders involved in the process including developers, community members, zoning bodies, and District agencies. The uncertainty resulting from the data gap can lead to the over-building of parking resulting in undesirable transportation, urban design, and housing affordability impacts.

Objective

To address this gap, the District Department of Transportation (DDOT) and the Office of Planning (OP) have embarked on a research effort to assess parking utilization in multifamily residential buildings throughout the District. The objective is to develop an empirical model for multifamily residential parking utilization based on local data collection. This includes accounting for how the built environment, building characteristics, and demographic factors influence parking utilization. The project resulted in a model displayed in a publicly-accessible webtool called Park Right DC. This research effort is based on King County’s (Washington) Right-Size Parking study: http://www.rightsizeparking.org/.

Completed 2015

Project Manager:Jonathan Rogers, 202-671-3022

	File	Modified
Labels No labels Preview View	PDF File TransportationResearchRecord_2568-11.pdf	08 Feb, 2022 by Former user
Labels No labels Preview View	PDF File King County Right Size Parking Study Summary.pdf	08 Feb, 2022 by Former user
Labels No labels Preview View	PDF File DC Residential Parking Study Outreach Materials.pdf	08 Feb, 2022 by Former user
Labels No labels Preview View	PDF File DC Parking Study_Sept 24 Panel_CNT Presentation.pdf	08 Feb, 2022 by Former user
Labels No labels Preview View	PDF File DC Parking Study_Sept 24 Panel_DDOT Presentation.pdf	08 Feb, 2022 by Former user
Labels No labels Preview View	PDF File DC Parking Study_Sept 24 Panel_Bozzuto Presentation.pdf	08 Feb, 2022 by Former user
Labels No labels Preview View	PDF File DC Parking Study Sept 24 Outreach Meeting Flier.pdf	08 Feb, 2022 by Former user

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