Solving the Curb Space Puzzle Through the Development of a Curb Space Allocation Tool. Issue 10 (October 2022)

• Record Type: Journal Article
• Authors: Pochowski, Alek L.; Crim, Stephen; Liu, Like; Trask, Lake; Sherman Baker, Christine; Woodworth, Sarah; Klion, Jessica
• Is Part Of: Transportation research record. Volume 2676:Issue 10(2022)
• Page Start: 601
• Page End: 621
• Publication Date: 2022-10
• Subjects: data and data science -- truck parking data -- freight systems -- city -- parking -- operations -- curbside management -- shared mobility operations -- planning and analysis -- shared mobility -- curbside -- shared use -- public transportation -- shared -- sustainability and resilience -- transportation and society -- equity in transportation -- micromobility and active transportation; Transportation -- Periodicals; Roads; Transport -- Périodiques; Routes -- Périodiques; Routes -- Conception et construction -- Périodiques; Roads; Transportation; 388.05
• DOI: 10.1177/03611981221090514
• Languages: English
• ISSNs: 0361-1981

Abstract

With new modes and technologies including ride-hail apps, e-commerce deliveries, and the revolution in micromobility services changing the transportation landscape at the curbside, jurisdictions like Arlington County, Virginia, have sought to develop tools to reconsider the allocation of curb space to provide the greatest economic and societal benefit to users of the transportation system. While other jurisdictions and researchers have developed a theoretical approach to allocating curb space under the premise that on-street parking is unlikely to provide the greatest economic or societal benefit, Arlington County sought to create a tool that allocates curb space with demand constraints and data relevant to the context of Arlington County. The developed curb space allocation tool uses six modules: (i) ride-hailing services, (ii) commercial loading, (iii) on-street parking, (iv) transit service, (v) micromobility, and (vi) non-transportation uses (parklets/streateries), which are all capable of being updated as new data or models become available. The tool uses each module to estimate the demand for each mode and then allocates the curb space to maximize the economic or societal value (number of people served). As a result of this work, Arlington County has developed the foundation for a tool that provides a mechanism for determining the optimal allocation of curb space given a block's existing or proposed land uses and transportation services and has identified gaps in research and available data to enhance the tool's usability.