HCC: Medium: Combining Crowdsourcing and Computer Vision for Street-level Accessibility

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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. Traditionally, sidewalk assessment has been conducted via in-person street audits, which are labor intensive and costly, or via citizen call-in reports, which are done on a reactive basis. And while efforts exist for visualizing the walk-ability, bike-ability, and availability of public transport in cities, there are no analogous efforts for accessibility. Thus, wheelchair users, for example, often avoid going to new areas of a city where they don't know about accessible routes. The PI plans to address this problem by means of a two-pronged approach in which he will first develop scalable data collection methods for acquiring sidewalk accessibility information using a combination of crowd-sourcing, computer vision, and online map imagery; he will then use the new data to develop and evaluate a novel set of navigation and map tools for accessibility. To these ends, the PI and his team will collect and analyze interview and survey data both from mobility impaired persons and from ADA streetscape design experts, and will seek to understand how people with mobility impairments can make use of interactive mapping information to enhance mobility. They will study methods for efficiently and effectively crowd-sourcing map labeling tasks, evaluating existing approaches empirically and designing novel, more effective approaches. They will develop new computer vision algorithms for the analysis of street scenes, which will be used to help scale the data collection by focusing human labeling efforts on locations that are most likely to contain significant problems. And they will design, implement and evaluate new accessible-aware map-based tools to aid people with mobility impairments in navigating their cities. As appropriate for each phase of the research, user evaluations will include both lab and field studies.Broader Impacts: Roughly 30.6 million individuals in the United States have physical disabilities that affect their ambulatory activities, and nearly half of these individuals report using an assistive aid such as a wheelchair, cane, crutches, or walker. The outcomes from this research will have a significant impact on the ability of these Americans to travel independently, by transforming the ways in which accessibility information is collected and visualized for every sidewalk, street, and building façade in America. Project outcomes will include a publicly accessible web site where both the labeled data collected during this work and the new prototype tools developed will be made available for general use. Furthermore, the PI and Co-PI will advise and mentor both graduate and undergraduate students throughout the course of the project, including two PhDs and two MS students who will obtain a cross-disciplinary education in human-computer interaction and computer vision.