Project Description

2012–Present
Roughly 30.6 million individuals in the US have physical disabilities that affect their ambulatory activities; nearly half of those individuals report using an assistive aid such as a wheelchair, cane, crutches, or walker. Despite comprehensive civil rights legislation for Americans with disabilities, many city streets, sidewalks, and businesses remain inaccessible. The problem is not just that street-level accessibility affects where and how people travel in cities but also that there are few, if any, mechanisms to determine accessible areas of a city a priori.

This project describes a two-pronged vision: first, to develop scalable data collection methods for acquiring sidewalk accessibility information using a combination of crowdsourcing, computer vision, and online map imagery, and second, to use this new data to design, develop, and evaluate a novel set of navigation and map tools for accessibility. Our overarching goal is to transform the ways in which accessibility information is collected and visualized for every sidewalk, street, and building façade in America.

Publications

LabelAId: Just-in-time AI Interventions for Improving Human Labeling Quality and Domain Knowledge in Crowdsourcing Systems

Chu Li, Zhihan Zhang, Mikey Saugstad, Esteban Safranchik, Minchu Kulkarni, Xiaoyu Huang, Shwetak Patel, Vikram Iyer, Tim Althoff, Jon E. Froehlich

CHI 2024 To Appear | Acceptance Rate: 26.3% (1060 / 4028)

“I never realized sidewalks were a big deal”: A Case Study of a Community-Driven Sidewalk Audit Using Project Sidewalk

Chu Li, Katrina Ma, Mikey Saugstad, Kie Fujii, Molly Delany, Yochai Eisenberg, Delphine Labbé, Judy L. Shanley, Devon Snyder, Florian P. Thomas, Jon E. Froehlich

CHI 2024 To Appear | Acceptance Rate: 26.3% (1060 / 4028)

Multiple-Stakeholder Perspectives on Accessibility Data and the Use of Socio-Technical Tools to Improve Sidewalk Accessibility

Delphine Labbé, Yochai Eisenberg, Devon Snyder, Judy L. Shanley, Joy Hammel, Jon E. Froehlich

Disabilities

Implementing a Community-Based Virtual Tool To Characterize Sidewalk Accessibility in a Northern New Jersey (NJ) Town

Kie Fujii, Katrina Ma, Chu Li, Mikey Saugstad, Lisa Stolarz, Michael Starr, Florian P. Thomas, Jon E. Froehlich

Extended Abstract ASCIP 2023 Annual Meeting

Implementing a Community-Based Virtual Tool To Characterize Sidewalk Accessibility in a Northern New Jersey (NJ) Town

Kie Fujii, Katrina Ma, Chu Li, Mikey Saugstad, Michael Starr, Lisa Stolarz, Florian P. Thomas, Jon E. Froehlich

Extended Abstract CMSC 2023 Annual Meeting

Scaling Crowd+AI Sidewalk Accessibility Assessments: Initial Experiments Examining Label Quality and Cross-city Training on Performance

Michael Duan, Sho Kiami, Logan Milandin, Johnson Kuang, Mikey Saugstad, Maryam Hosseini, Jon E. Froehlich

Poster Proceedings of ASSETS'22 | Acceptance Rate: 58.9% (43 / 73)

A Pilot Study of Sidewalk Equity in Seattle Using Crowdsourced Sidewalk Assessment Data

Chu Li, Lisa Orii, Mikey Saugstad, Stephen J. Mooney, Yochai Eisenberg, Delphine Labbé, Joy Hammel, Jon E. Froehlich

UrbanAccess 2022

Participatory Design of Crowd+AI Tools to Map, Analyze, and Visualize Sidewalk Accessibility

Yochai Eisenberg, Delphine Labbé, Sierra Berquist, Judy L. Shanley, Joy Hammel, Jon E. Froehlich

Extended Abstract Proceedings of TRANSED 2022

Designing Interactive Data-Driven Tools for Understanding Urban Accessibility at Scale

Manaswi Saha

UW CS PhD Dissertation

Towards Global-Scale Crowd+AI Techniques to Map and Assess Sidewalks for People with Disabilities

Maryam Hosseini, Mikey Saugstad, Fabio Miranda, Andres Sevtsuk, Cláudio T. Silva, Jon E. Froehlich

CVPR2022 Workshop: Accessibility, Vision, and Autonomy (AVA)

Visualizing Urban Accessibility: Investigating Multi-Stakeholder Perspectives through a Map-based Design Probe Study

Manaswi Saha, Siddhant Patil, Emily Cho, Evie Yu-Yen Cheng, Chris Horng, Devanshi Chauhan, Rachel Kangas, Richard McGovern, Anthony Li, Jeffrey Heer, Jon E. Froehlich

CHI | Acceptance Rate: 24.7% (637 / 2579)

Experimental Crowd+AI Approaches to Track Accessibility Features in Sidewalk Intersections Over Time

Ather Sharif, Paari Gopal, Mikey Saugstad, Shiven Bhatt, Raymond Fok, Galen Weld, Kavi Dey, Jon E. Froehlich

Extended Abstract Proceedings of ASSETS 2021 | Acceptance Rate: 61.8% (55 / 89)

Sidewalk Gallery: An Interactive, Filterable Image Gallery of Over 500,000 Sidewalk Accessibility Problems

Michael Duan, Aroosh Kumar, Mikey Saugstad, Aileen Zeng, Ilia Savin, Jon E. Froehlich

Extended Abstract Proceedings of ASSETS 2021 | Acceptance Rate: 61.8% (55 / 89) | Best Artifact Runner-up Award

Urban Accessibility as a Socio-Political Problem: A Multi-Stakeholder Analysis

Manaswi Saha, Devanshi Chauhan, Siddhant Patil, Rachel Kangas, Jeffrey Heer, Jon E. Froehlich

CSCW

Sidewalk Accessibility in the US and Mexico: Policies, Tools, and A Preliminary Case Study

Jon E. Froehlich, Mikey Saugstad, Edgar Martínez, Rebeca de Buen Kalman

Extended Abstract Workshop Proceedings of Civic Tech 2020

Towards Mapping and Assessing Sidewalk Accessibility Across Socio-cultural and Geographic Contexts

Jon E. Froehlich, Mikey Saugstad, Manaswi Saha, Matthew Johnson

Extended Abstract Data4Good

Interactive Computational Tools for Assessing and Understanding Urban Accessibility At Scale

Manaswi Saha

SIGACCESS Newsletter 2020

Deep Learning for Automatically Detecting Sidewalk Accessibility Problems Using Streetscape Imagery

Galen Weld, Esther Jang, Anthony Li, Aileen Zeng, Kurtis Heimerl, Jon E. Froehlich

Proceedings of ASSETS 2019 | Acceptance Rate: 25.9% (41 / 158) | Best Paper Award

Project Sidewalk: A Web-based Crowdsourcing Tool for Collecting Sidewalk Accessibility Data at Scale

Manaswi Saha, Mikey Saugstad, Teja Maddali, Aileen Zeng, Ryan Holland, Steven Bower, Aditya Dash, Sage Chen, Anthony Li, Kotaro Hara, Jon E. Froehlich

Proceedings of CHI 2019 | Acceptance Rate: 23.8% (705 / 2960) | Best Paper Award

Grand challenges in accessible maps

Jon E. Froehlich, Anke Brock, Anat Caspi, Joao Guerreiro, Kotaro Hara, Reuben Kirkham, Johannes Schoning, Benjamin Tannert

Interactions

A Feasibility Study of Using Google Street View and Computer Vision to Track the Evolution of Urban Accessibility

Ladan Najafizadeh, Jon E. Froehlich

Extended Abstract Proceedings of ASSETS 2018

Interactively Modeling and Visualizing Neighborhood Accessibility at Scale: An Initial Study of Washington DC

Anthony Li, Manaswi Saha, Anupam Gupta, Jon E. Froehlich

Extended Abstract Proceedings of ASSETS 2018

SIG: Making Maps Accessible and Putting Accessibility in Maps

Anke Brock, Jon E. Froehlich, Joao Guerreiro, Benjamin Tannert, Anat Caspi, Johannes Schoning, Steve Landau

Extended Abstract Proceedings of CHI 2018

A Pilot Deployment of an Online Tool for Large-Scale Virtual Auditing of Urban Accessibility

Manaswi Saha, Kotaro Hara, Soheil Behnezhad, Anthony Li, Mikey Saugstad, Teja Maddali, Sage Chen, Jon E. Froehlich

Extended Abstract Proceedings of ASSETS 2017

Temporal Tracking Urban Areas using Google Street View

Ladan Najafizadeh

UMD CS MS Thesis

Scalable Methods to Collect and Visualize Sidewalk Accessibility Data for People with Mobility Impairments

Kotaro Hara

UMD CS PhD Dissertation

The Design of Assistive Location-based Technologies for People with Ambulatory Disabilities: A Formative Study

Kotaro Hara, Christine Chan, Jon E. Froehlich

Proceedings of CHI 2016 | Acceptance Rate: 25.0% (600 / 2400)

Characterizing and Visualizing Physical World Accessibility at Scale Using Crowdsourcing, Computer Vision, and Machine Learning

Kotaro Hara, Jon E. Froehlich

SIGACCESS Newsletter '15

Scalable methods to collect and visualize sidewalk accessibility data for people with mobility impairments

Kotaro Hara

Extended Abstract Proceedings of UIST 2014

Tohme: Detecting Curb Ramps in Google Street View Using Crowdsourcing, Computer Vision, and Machine Learning

Kotaro Hara, Jin Sun, Robert Moore, David Jacobs, Jon E. Froehlich

Proceedings of UIST 2014

An Initial Study of Automatic Curb Ramp Detection with Crowdsourced Verification using Google Street View Images

Kotaro Hara, Jin Sun, Noa Chazan, David Jacobs, Jon E. Froehlich

Poster Proceedings of HCOMP 2013

Exploring Early Solutions for Automatically Identifying Inaccessible Sidewalks in the Physical World using Google Street View

Kotaro Hara, Victoria Le, Jin Sun, David Jacobs, Jon E. Froehlich

HCIC2013 Workshop

Combining Crowdsourcing and Google Street View to Identify Street-level Accessibility Problems

Kotaro Hara, Victoria Le, Jon E. Froehlich

Proceedings of CHI 2013

A feasibility study of crowdsourcing and google street view to determine sidewalk accessibility

Kotaro Hara, Victoria Le, Jon E. Froehlich

Poster Proceedings of ASSETS 2012

Videos

Don't Forget about the Sidewalk: The Role of Mobility Management and Coordination

Project Sidewalk Chi Hack Night

Talks

Project Sidewalk: Crowd+AI Techniques to Map & Assess the World's Sidewalks

Feb. 29, 2024 | NSF Smart and Connected Communities Panel on “Pathways to Transitioning Project Outcomes"

Nashville, Tennessee

Scalable Techniques to Study the Equitable Distribution and Condition of US Sidewalks

Dec. 14, 2022 | ITS (Intelligent Transportation Systems)

Tacoma, Washington

Crowd + AI Tools for Scalable Sidewalk Assessment

Dec. 13, 2021 | Spatial Data Science Symposium 2021

Virtual

Making with a Social Purpose

Oct. 13, 2017 | DUB Retreat

University of Washington, Seattle

Making with a Social Purpose

June 7, 2017 | UMD CS Staff Talk

University of Maryland, College Park

Making with a Social Purpose

April 13, 2017 | HCDE Invited Talk

University of Washington, Seattle

Making With a Social Purpose

April 11, 2017 | UW CSE Colloquium

University of Washington, Seattle

Making with a Social Purpose

April 6, 2017 | Lecture Series at the Laboratory for Telecommunication Sciences

LTS Auditorium, College Park, MD

Interactive Computational Tools for Accessibility

Nov. 7, 2016 | Diversity in Computing Summit 2016

College Park, Maryland

Tech+Design: Interaction Design for a Purpose

Nov. 3, 2016 | Technica: Tech+X Talk Series

University of Maryland, College Park

Characterizing Physical World Accessibility at Scale

Nov. 3, 2016 | GroupSight @ HCOMP2016

Austin, Texas