poster

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

Authors:

Michael Saugstad,

Kavi Asher Mankoff Dey,

Jon E. FroehlichAuthors Info & Claims

ASSETS '21: Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility

Article No.: 65, Pages 1 - 5

https://doi.org/10.1145/3441852.3476549

Published: 17 October 2021 Publication History

Abstract

How do sidewalks change over time? Are there geographic or socioeconomic patterns to this change? These questions are important but difficult to address with current GIS tools and techniques. In this demo paper, we introduce three preliminary crowd+AI (Artificial Intelligence) prototypes to track changes in street intersection accessibility over time—specifically, curb ramps—and report on results from a pilot usability study.

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References

[1]

United States Department of Justice Civil Rights Division Ada.gov. Introduction to the ADA.

[2]

Dragan Ahmetovic, Roberto Manduchi, James M. Coughlan, and Sergio Mascetti. 2015. Zebra Crossing Spotter: Automatic Population of Spatial Databases for Increased Safety of Blind Travelers. In The 17th International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS 2015).

Digital Library

[3]

Pablo F. Alcantarilla, Simon Stent, Germán Ros, Roberto Arroyo, and Riccardo Gherardi. 2018. Street-view change detection with deconvolutional networks. Autonomous Robots 42, 7: 1301–1322. https://doi.org/10.1007/s10514-018-9734-5

Digital Library

[4]

Saleema Amershi, Kori Inkpen, Jaime Teevan, Ruth Kikin-Gil, Eric Horvitz, Dan Weld, Mihaela Vorvoreanu, Adam Fourney, Besmira Nushi, Penny Collisson, Jina Suh, Shamsi Iqbal, and Paul N Bennett. 2019. Guidelines for Human-AI Interaction. In Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems - CHI ’19, 1–13. https://doi.org/10.1145/3290605.3300233

Digital Library

[5]

Kuan-Ting Chen, Fu-En Wang, Juan-Ting Lin, Fu-Hsiang Chan, and Min Sun. 2016. The world is changing: Finding changes on the street. In Asian Conference on Computer Vision, 420–435.

[6]

Marius Cordts, Mohamed Omran, Sebastian Ramos, Timo Rehfeld, Markus Enzweiler, Rodrigo Benenson, Uwe Franke, Stefan Roth, and Bernt Schiele. 2016. The Cityscapes Dataset for Semantic Urban Scene Understanding. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[7]

Yochai Eisenberg, Amy Heider, Rob Gould, and Robin Jones. 2020. Are communities in the United States planning for pedestrians with disabilities? Findings from a systematic evaluation of local government barrier removal plans. Cities 102: 102720. https://doi.org/10.1016/j.cities.2020.102720

[8]

Jon E Froehlich, Mikey Saugstad, Edgar Martínez, and Rebeca de Buen Kalman. 2020. Sidewalk Accessibility in the US and Mexico: Policies, Tools, and A Preliminary Case Study. In CSCW2020 Workshop on Civic Technologies: Research, Practice, and Open Challenges.

[9]

David Gutman. 2017. Seattle may have to spend millions making sidewalks more accessible to people with disabilities. The Seattle Times.

[10]

Richard Guy and Khai Truong. 2012. CrossingGuard: exploring information content in navigation aids for visually impaired pedestrians. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI ’12) (CHI ’12), 405–414. https://doi.org/10.1145/2207676.2207733

Digital Library

[11]

Kotaro Hara, Jin Sun, Robert Moore, David Jacobs, and Jon Froehlich. 2014. Tohme: detecting curb ramps in google street view using crowdsourcing, computer vision, and machine learning. In Proceedings of the 27th annual ACM symposium on User interface software and technology - UIST ’14, 189–204. https://doi.org/10.1145/2642918.2647403

Digital Library

[12]

Winnie Hu. 2017. For the Disabled, New York's Sidewalks Are an Obstacle Course. The New York Times.

[13]

Wei Ji, Jia Ma, Rima Wahab Twibell, and Karen Underhill. 2006. Characterizing urban sprawl using multi-stage remote sensing images and landscape metrics. Computers, Environment and Urban Systems 30, 6: 861–879. https://doi.org/10.1016/J.COMPENVURBSYS.2005.09.002

[14]

Vikram Mohanty, David Thames, Sneha Mehta, and Kurt Luther. 2019. Photo Sleuth: Combining Human Expertise and Face Recognition to Identify Historical Portraits. In Proceedings of the 24th International Conference on Intelligent User Interfaces (IUI ’19), 547–557. https://doi.org/10.1145/3301275.3302301

Digital Library

[15]

Ladan Najafizadeh and Jon E. Froehlich. 2018. A Feasibility Study of Using Google Street View and Computer Vision to Track the Evolution of Urban Accessibility. In Poster Proceedings of ASSETS’18.

[16]

Gerhard Neuhold, Tobias Ollmann, Samuel Rota Bulo, and Peter Kontschieder. 2017. The Mapillary Vistas Dataset for Semantic Understanding of Street Scenes. In Proceedings of the IEEE International Conference on Computer Vision (ICCV).

[17]

Ronald A. Rensink. 2002. Change Detection. Annual Review of Psychology 53, 1: 245–277. https://doi.org/10.1146/annurev.psych.53.100901.135125

[18]

Emily Alpert Reyes. 2015. L.A. agrees to spend $1.3 billion to fix sidewalks in ADA case. Los Angeles Times.

[19]

Manaswi Saha, Devanshi Chauhan, Siddhant Patil, Rachel Kangas, Jeffrey Heer, and Jon E. Froehlich. 2020. Urban Accessibility as a Socio-Political Problem: A Multi-Stakeholder Analysis. In Proceedings of the ACM on Human Computer Interaction (PACM HCI); To Be Presented at CSCW2020.

[20]

Manaswi Saha, Michael Saugstad, Hanuma Maddali, Aileen Zeng, Ryan Holland, Steven Bower, Aditya Dash, Sage Chen, Anthony Li, Kotaro Hara, and Jon E. Froehlich. 2019. Project Sidewalk: A Web-based Crowdsourcing Tool for Collecting Sidewalk Accessibility Data at Scale. In Proceedings of CHI 2019.

[21]

Ken Sakurada, Daiki Tetsuka, and Takayuki Okatani. 2017. Temporal city modeling using street level imagery. Computer Vision and Image Understanding 157: 55–71. https://doi.org/10.1016/j.cviu.2017.01.012

Digital Library

[22]

Daniel J. Simons and Michael S. Ambinder. 2005. Change Blindness. Current Directions in Psychological Science 14, 1: 44–48. https://doi.org/10.1111/j.0963-7214.2005.00332.x

[23]

Xiao-Peng Song, Joseph O. Sexton, Chengquan Huang, Saurabh Channan, and John R. Townshend. 2016. Characterizing the magnitude, timing and duration of urban growth from time series of Landsat-based estimates of impervious cover. Remote Sensing of Environment 175: 1–13. https://doi.org/10.1016/J.RSE.2015.12.027

[24]

M Toomim, A Begel, and S L Graham. 2004. Managing Duplicated Code with Linked Editing. In 2004 IEEE Symposium on Visual Languages - Human Centric Computing, 173–180. https://doi.org/10.1109/VLHCC.2004.35

Digital Library

[25]

US Department of Transportation Federal Highway Administration. 2015. ADA Transition Plan.

[26]

Jan D. Wegner, Steve Branson, David Hall, Konrad Schindler, and Pietro Perona. 2016. Cataloging Public Objects Using Aerial and Street-Level Images — Urban Trees. In 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 6014–6023. https://doi.org/10.1109/CVPR.2016.647

[27]

Galen Weld, Esther Jang, Anthony Li, Aileen Zeng, Kurtis Heimerl, and Jon E Froehlich. 2019. Deep Learning for Automatically Detecting Sidewalk Accessibility Problems Using Streetscape Imagery. In The 21st International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS ’19), 196–209. https://doi.org/10.1145/3308561.3353798

Digital Library

[28]

2Jianguo Wu, G. Darrel Jenerette, Alexander Buyantuyev, and Charles L. Redman. 2011. Quantifying spatiotemporal patterns of urbanization: The case of the two fastest growing metropolitan regions in the United States. Ecological Complexity 8, 1: 1–8. https://doi.org/10.1016/J.ECOCOM.2010.03.002

[29]

1993. Kinney v. Yerusalim, 9 F.3d 1067 (3d Cir. 1993). Retrieved from https://casetext.com/case/kinney-v-yerusalim

Cited By

Froehlich JLi CHosseini MMiranda FSevtsuk AEisenberg Y(2024)The Future of Urban Accessibility: The Role of AIProceedings of the 26th International ACM SIGACCESS Conference on Computers and Accessibility10.1145/3663548.3688550(1-6)Online publication date: 27-Oct-2024
https://dl.acm.org/doi/10.1145/3663548.3688550
Su XZhang HCheng KLee JLiu QOlson WFroehlich J(2024)RASSAR: Room Accessibility and Safety Scanning in Augmented RealityProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642140(1-17)Online publication date: 11-May-2024
https://dl.acm.org/doi/10.1145/3613904.3642140
Correia AGrover ASchneider DPimentel AChaves Rde Almeida MFonseca B(2023)Designing for Hybrid Intelligence: A Taxonomy and Survey of Crowd-Machine InteractionApplied Sciences10.3390/app1304219813:4(2198)Online publication date: 8-Feb-2023
https://doi.org/10.3390/app13042198
Show More Cited By

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Experimental Crowd+AI Approaches to Track Accessibility Features in Sidewalk Intersections Over Time
1. Information systems

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Information & Contributors

Information

Published In

cover image ACM Conferences

ASSETS '21: Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility

October 2021

730 pages

ISBN:9781450383066

DOI:10.1145/3441852

Editors:
Jonathan Lazar
University of Maryland, USA
,
Jinjuan Heidi Feng
Towson University, USA
,
Faustina Hwang
Towson University, USA

Copyright © 2021 Owner/Author.

Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

Sponsors

SIGACCESS: ACM Special Interest Group on Accessible Computing

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 17 October 2021

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Poster
Research
Refereed limited

Funding Sources

US Department of Transportation, Pacific Northwest Regional University Transportation Center

Conference

ASSETS '21

Sponsor:

SIGACCESS

ASSETS '21: The 23rd International ACM SIGACCESS Conference on Computers and Accessibility

October 18 - 22, 2021

Virtual Event, USA

Acceptance Rates

ASSETS '21 Paper Acceptance Rate 36 of 134 submissions, 27%;

Overall Acceptance Rate 436 of 1,556 submissions, 28%

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Cited By

Froehlich JLi CHosseini MMiranda FSevtsuk AEisenberg Y(2024)The Future of Urban Accessibility: The Role of AIProceedings of the 26th International ACM SIGACCESS Conference on Computers and Accessibility10.1145/3663548.3688550(1-6)Online publication date: 27-Oct-2024
https://dl.acm.org/doi/10.1145/3663548.3688550
Su XZhang HCheng KLee JLiu QOlson WFroehlich J(2024)RASSAR: Room Accessibility and Safety Scanning in Augmented RealityProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642140(1-17)Online publication date: 11-May-2024
https://dl.acm.org/doi/10.1145/3613904.3642140
Correia AGrover ASchneider DPimentel AChaves Rde Almeida MFonseca B(2023)Designing for Hybrid Intelligence: A Taxonomy and Survey of Crowd-Machine InteractionApplied Sciences10.3390/app1304219813:4(2198)Online publication date: 8-Feb-2023
https://doi.org/10.3390/app13042198
Paananen VVisuri Avan Berkel NHosio S(2023)Eliciting Empathy towards Urban Accessibility IssuesProceedings of the 15th Biannual Conference of the Italian SIGCHI Chapter10.1145/3605390.3605416(1-13)Online publication date: 20-Sep-2023
https://dl.acm.org/doi/10.1145/3605390.3605416
Froehlich JEisenberg YHosseini MMiranda FAdams MCaspi ADieterich HFeldner HGonzalez ADe Gyves CHammel JKirkham RKneisel MLabbÉ DMooney SPineda VPinhÃO CRodrÍGuez ASaha MSaugstad MShanley JSharif AShen QSilva CSukel MTokuda EZappe SZivarts A(2022)The Future of Urban Accessibility for People with Disabilities: Data Collection, Analytics, Policy, and ToolsProceedings of the 24th International ACM SIGACCESS Conference on Computers and Accessibility10.1145/3517428.3550402(1-8)Online publication date: 23-Oct-2022
https://dl.acm.org/doi/10.1145/3517428.3550402

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