Toward Automating the Measurement of Urban Design Qualities Related to Walkability

Streets are one of the most significant elements of urban spaces to accommodate public activity and provide access to numerous locations and services. Today, our cities face various challenges, including urban sprawl, air pollution, and obesity. To address some of these problems, cities and local governments consider land use planning and urban design to lower car dependency and promote walking and biking. Many studies have characterized the built environment in terms of D variables density, diversity, design, destination accessibility, and distance to transit. Measurement of four D variables is relatively straightforward, while the D variable, design, is more nuanced. Urban designers believe that micro features are essential for active street life but have little empirical evidence to back the claim. The conventional research approaches to objectively measure the subjective qualities of the street environment require resource-intensive street-level field observation believed to be one of the main constraints of the widespread application of such methods. This dissertation will be consist of two studies that will collectively explore the applications of advanced technologies and methods such as Google Street View, computer vision, and deep learning toward automating the measuring of micro-scale characteristics of the built environment related to pedestrian activity and overall walkability.

• Record URL:
  https://nitc.trec.pdx.edu/research/project/1527

Language

• English

Project

• Status: Active
• Funding: $15000
• Contract Numbers:

  NITC-1527

  69A3551747112

• Sponsor Organizations:

  Office of the Assistant Secretary for Research and Technology

  University Transportation Centers Program
  Department of Transportation
  Washington, DC  United States  20590
• Managing Organizations:

  TREC at Portland State University

  1900 SW Fourth Ave, Suite 175
  P.O. Box 751
  Portland, Oregon  United States  97201
• Performing Organizations:

  University of Utah, Salt Lake City

  City & Metropolitan Planning
  201 South Presidents Circle
  Salt Lake City, UT  United States  84112
• Principal Investigators:

  Ameli, Seyed

• Start Date: 20210915
• Expected Completion Date: 20230831
• Actual Completion Date: 0
• USDOT Program: University Transportation Centers

Subject/Index Terms

• TRT Terms: Built environment; Computer vision; Machine learning; Urban design; Walkability
• Subject Areas: Data and Information Technology; Design; Pedestrians and Bicyclists;

Filing Info

• Accession Number: 01781403
• Record Type: Research project
• Source Agency: National Institute for Transportation and Communities
• Contract Numbers: NITC-1527, 69A3551747112
• Files: UTC, RIP
• Created Date: Sep 7 2021 10:24PM