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

被引:74
|
作者
Saha, Manaswi [1 ]
Saugstad, Michael [1 ]
Maddali, Hanuma Teja [2 ]
Zeng, Aileen [1 ]
Holland, Ryan [3 ]
Bower, Steven [2 ]
Dash, Aditya [2 ]
Chen, Sage [4 ]
Li, Anthony [2 ]
Hara, Kotaro [5 ]
Froehlich, Jon [1 ]
机构
[1] Univ Washington, Seattle, WA 98195 USA
[2] Univ Maryland, College Pk, MD 20742 USA
[3] Montgomery Blair High Sch, Silver Spring, MD USA
[4] Univ Michigan, Ann Arbor, MI 48109 USA
[5] Singapore Management Univ, Singapore, Singapore
关键词
Crowdsourcing; accessibility; mobility impairments; GIS; INFORMATION; ACCESS;
D O I
10.1145/3290605.3300292
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
We introduce Project Sidewalk, a new web-based tool that enables online crowdworkers to remotely label pedestrian-related accessibility problems by virtually walking through city streets in Google Street View. To train, engage, and sustain users, we apply basic game design principles such as interactive onboarding, mission-based tasks, and progress dashboards. In an 18-month deployment study, 797 online users contributed 205,385 labels and audited 2,941 miles of Washington DC streets. We compare behavioral and labeling quality differences between paid crowdworkers and volunteers, investigate the effects of label type, label severity, and majority vote on accuracy, and analyze common labeling errors. To complement these findings, we report on an interview study with three key stakeholder groups (N=14) soliciting reactions to our tool and methods. Our findings demonstrate the potential of virtually auditing urban accessibility and highlight tradeoffs between scalability and quality compared to traditional approaches.
引用
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页数:14
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