Award Abstract # 2125087
SCC-IRG Track 1: Crowd+AI Tools to Map, Analyze, and Visualize Sidewalk Accessibility for Inclusive Cities

NSF Org: CNS
Division Of Computer and Network Systems
Recipient: UNIVERSITY OF WASHINGTON
Initial Amendment Date: August 12, 2021
Latest Amendment Date: August 12, 2021
Award Number: 2125087
Award Instrument: Standard Grant
Program Manager: Abhishek Dubey
adubey@nsf.gov
 (703)292-7375
CNS
 Division Of Computer and Network Systems
CSE
 Directorate for Computer and Information Science and Engineering
Start Date: October 1, 2021
End Date: September 30, 2026 (Estimated)
Total Intended Award Amount: $2,018,000.00
Total Awarded Amount to Date: $2,018,000.00
Funds Obligated to Date: FY 2021 = $2,018,000.00
History of Investigator:
  • Jon Froehlich (Principal Investigator)
    jonf@cs.washington.edu
  • Joy Hammel (Co-Principal Investigator)
  • Yochai Eisenberg (Co-Principal Investigator)
  • Delphine LabbĂ© (Co-Principal Investigator)
Recipient Sponsored Research Office: University of Washington
4333 BROOKLYN AVE NE
SEATTLE
WA  US  98195-1016
(206)543-4043
Sponsor Congressional District: 07
Primary Place of Performance: University of Washington
4333 Brooklyn Ave NE
Seattle
WA  US  98195-0001
Primary Place of Performance
Congressional District:
07
Unique Entity Identifier (UEI): HD1WMN6945W6
Parent UEI:
NSF Program(s): S&CC: Smart & Connected Commun
Primary Program Source: 01002122DB NSF RESEARCH & RELATED ACTIVIT
Program Reference Code(s): 042Z
Program Element Code(s): 033Y00
Award Agency Code: 4900
Fund Agency Code: 4900
Assistance Listing Number(s): 47.070

ABSTRACT

Despite decades of civil rights legislation for Americans with disabilities, many city sidewalks remain inaccessible. A key problem is the lack of reliable data on where sidewalks exist and their quality. This lack of data fundamentally limits how sidewalk accessibility can be studied in cities, the ability for communities, advocacy groups, and local governments to understand, transparently discuss, and make informed planning decisions, and how sidewalks and accessibility are incorporated into interactive map, navigation, and Geographic Information Systems analysis tools. This proposal aims to (1) advance understanding of stakeholder needs and opportunities for socio-technical tools to assess and plan for accessible sidewalks; (2) develop and evaluate crowd+AI sidewalk data collection and assessment techniques to improve scalability, reliability, and better support diverse stakeholder needs; and (3) develop and evaluate a suite of open-source urban accessibility analysis and visualization tools. To address these aims, this project's cross-disciplinary team will work with urban and transportation planners, government leaders, disability advocates (e.g. EasterSeals - which also is participating as a Co-PI) and people with disabilities via participatory-design methods, crowdsourcing and stakeholder focus groups and interviews.

The proposed work makes foundational contributions to Human Computer Interaction, urban planning, and disability studies. First, this project will advance understanding of stakeholder needs and opportunities for socio-technical tools to support planning of accessible sidewalks, civic engagement, advocacy, and trip planning. Second, this project will develop new data collection and assessment techniques that will contribute new ML-based algorithms, crowd+AI workflows, and quality control mechanisms that improve scalability, reliability, and better support diverse stakeholder needs. The proposed crowd+AI approaches will enhance understanding of the challenges, concerns, and future opportunities for engaging people with disabilities in smart cities civic participation. Third, this project will develop and evaluate a suite of open-source sidewalk accessibility analysis and visualization tools, which are uniquely enabled by our data collection techniques, to help urban planners and transit agencies develop ADA transition plans for improving sidewalk accessibility, enable pedestrian and disability advocates to examine geo-spatial patterns of inaccessibility and review government progress, and help people with disabilities make safe, accessible mobility decisions. The proposed data collection and visualization tools have the potential to transform how sidewalk accessibility data is collected and analyzed, how cities plan for and improve sidewalk accessibility, and how infrastructure funding is dispersed in cities. The tools and data will be open sourced, enabling others to build off our work?including the over 80% of US cities that do not yet have plans to remove sidewalk barriers.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH

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Li, Chu and Ma, Katrina_Oi Yau and Saugstad, Michael and Fujii, Kie and Delaney, Molly and Eisenberg, Yochai and Labbé, Delphine and Shanley, Judy L and Snyder, Devon and Thomas, Florian_P P and Froehlich, Jon E "I never realized sidewalks were a big deal: A Case Study of a Community-Driven Sidewalk Accessibility Assessment using Project Sidewalk" , 2024 https://doi.org/10.1145/3613904.3642003 Citation Details

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