BSc Thesis - Computer Vision For European Urban Sidewalk Accessibility

BSc Thesis by Kasper Verhavert

Cities should be easy for everyone to get to and move around in. But this doesn’t always happen. While cities are putting effort in creating a more open environment for people with disabilities, these efforts do not always suffice. This is not just due to a lack of resources, but also the way they are being used.

Right now, inspectors have to go out and physically check the sidewalks and streets to gather information about how accessible they are. While this is the best way to know about the condition of different parts of a city, it takes a great amount of time. But what if there is a way to avoid this slow and tedious process.

This is where Project Sidewalk comes in. With this project research is being done in using AI to do these inspections, instead of doing them manually. However, creating an architecture to do these inspections has some drawbacks. One major hurdle to overcome, is that training an Artificial Intelligence model requires a lot of data.

Project Sidewalk is a public crowdsourcing tool, made by the University of Washington, designed to overcome this hurdle. Using this tool everyone, whether they are an expert or just an interested individual, can start validating the sidewalk accessibility features of a certain city. By following the labeling guide, the user can virtually walk through these cities, and point out inadequate accessibility features for people with disabilities.

This research was conducted by Kasper Verhavert in collaboration with the AI Team, Urban Innovation and R&D, City of Amsterdam.

Involved civil servants: Diederik M. Roijers

Image credits

Header image: Header from Google Streetview