Curb data can include both real-time information on curb use as well as static inventories of existing space and regulations. Real-time curb data can support long-term goals, but can also cause cities issues related to cost, accuracy, upkeep, and integration. Static curb data, however, can represent immediate opportunities to support and streamline ongoing city operations, reduce staff and time burdens, and provide a resource to other external users. Boston's SMART grant utilizes artificial intelligence (AI) and machine learning to digitize and analyze street sign images to generate curb data across the city. Digitizing helps to generate a curb inventory available to both city staff and external end users. This report synthesizes existing curb research alongside interviews with 17 City of Boston staff, industry and end-user representatives, and staff from other US cities with experience in curb digitization and management.

One-Page Summary Guide

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Key findings

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Policymaking, planning, and public engagement: Support policy focused on the entire street network, align curb regulations to city goals and adjacent land uses, assess regulations across neighborhoods, create more intuitive regulations, enhance public space, support economic development, streamline planning processes such as development and site plan review, and engage and inform the public.

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Permitting, compliance, and enforcement: Use curb regulation data to assess and inform the residential and temporary permit zones minimize conflicts and support enforcement and ticket adjudication.

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Asset management and operations: Integrate curb inventory into existing workflows to maintain accurate, up-to-date data, and use digital curb information to reduce street sign conflicts and installation errors.

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