Physical barriers and where to find them

Abstract

Movement-impaired groups, like wheelchair users, face challenges navigating sidewalks and pathways due to physical barriers such as curbs, stairs, and inclinations. However, existing navigation services often lack information about these barriers, hindering the ability to suggest optimal routes. Volunteered Geographic Information (VGI) offers a collaborative solution by harnessing volunteers' efforts to collect data for various projects. Despite its promise, VGI projects like OpenStreetMap struggle to effectively promote information about physical barriers and more open data is required for the development of navigation applications tailored to the user’s needs.

This research project aims to address these shortcomings by developing a framework to capture and visualize data points of potential physical barriers. Utilizing a clustering algorithm, the visualization of barriers is optimized to reduce similar data points. Two participants were recruited to capture data points including curbs with assigned height and crosswalk connections, stairs with or without stroller ramps, inclinations whether they are natural or wheelchair ramps, and other unspecified barriers.

The results revealed challenges in capturing and optimizing data for curbs and inclinations. However, the VGI approach showed promise in identifying the presence of stairs. Additionally, unspecified barriers related to weather effects were found, such as snow, underscored their impact on streets and pathways.

Overall, this research sheds light on the limitations of the approach in this research project and its technical implementation. Furthermore, this research highlights difficulties in data acquisition, recommendations of visualization of physical barriers, and the need for increased initiatives and data collection efforts.

Abstract (Swedish)

Rörelsehindrade grupper, som rullstolsanvändare, möter utmaningar när de navigerar trottoarer och vägar på grund av fysiska hinder som trottoarkanter, trappor och lutningar. Trots detta saknar befintliga navigeringstjänster ofta information om dessa hinder, vilket hindrar förmågan att föreslå optimala rutter. Volontärgeografisk information (VGI) erbjuder en samarbetslösning genom att utnyttja frivilligas insatser för att samla in data för olika projekt. Trots dess potential, arbetar VGI-projekt som OpenStreetMap med att effektivt främja information om fysiska hinder, och mer öppna data behövs för utvecklingen av navigeringsapplikationer anpassade till användarens behov.

Det här forskningsprojektet syftar till att åtgärda dessa brister genom att utveckla en ram för att fånga och visualisera datapunkter av potentiella fysiska hinder. Genom att använda en klusteralgoritm optimeras visualiseringen av hinder för att minska liknande datapunkter. Två deltagare rekryterades för att fånga datapunkter inklusive trottoarkanter med tilldelad höjd och övergångar för gångvägar, trappor med eller utan barnvagnsrampar, lutningar oavsett om de är naturliga eller rullstolsrampar och andra ospecificerade hinder.

Resultaten visade utmaningar med att fånga och optimera data för trottoarkanter och lutningar. Samtidigt visade VGI-metoden lovande resultat när det gäller att identifiera förekomsten av trappor. Dessutom hittades ospecificerade hinder relaterade till väderfenomen, som snö, deras påverkan på gator och gångvägar.

Sammanfattningsvis belyser den här forskningen begränsningarna i tillvägagångssättet i detta forskningsprojekt och dess tekniska genomförande. Vidare lyfter forskningen fram svårigheter med datainsamling, rekommendationer för visualisering av fysiska hinder och behovet av ökade initiativ och insamlingsinsatser.

Popular Abstract

Have you ever struggled to navigate city sidewalks, especially if you are a wheelchair-user? Most navigation apps do not show pathway and sidewalk obstacles, making it hard to plan routes. These obstacles include infrastructure that is challenging for wheelchair users to overcome, such as elevated curbs, staircases, and inclinations.

This project set out to change that with the help of volunteers who gathered information about pathway and sidewalk barriers, using a user-friendly data acquisition app which was developed specifically for this project. The collected data was then projected on a web map with the help of computation tools, making it possible to spot obstacle locations and provide valuable insights into the location and characteristics of these obstacles. Additionally, the project aimed to make it possible to contribute information about physical barriers for anyone who wants to.

During the data gathering process, challenges – such as technical difficulties and lack of specific instructions – were encountered, but the research results showed great promise in visualizing obstacles. Two participants collected a total of 167 data points in the study area of Traneberg in Stockholm. After carefully researching the data, 119 data points were left that were used to display the locations of physical barriers on a web map. During this process, it became clear that physical barriers can also be temporary, which resulted in suggestions to visualize these temporary physical barriers in a different manner. By sharing the results, the project aimed to make the built-environment more accessible for everyone.

All in all, this project shows that with teamwork and geographical data, it is possible to detect obstacles on sidewalks and pathways. There is still room for improvement and next steps, but this provides insights into the inaccessibility of the built-environment and how navigation apps can be improved for everyone.

• author: Wigen, Karl-Martin
• supervisor: Lars Harrie
• organization: Dept of Physical Geography and Ecosystem Science
• course: GISM01 20241
• year: 2024
• type: H2 - Master's Degree (Two Years)
• subject: Earth and Environmental Sciences
• keywords: Geography, GIS, Volunteered Geographic Information, Physical Barriers, Mobility Impairment, Application
• publication/series: Master Thesis in Geographical Information Science
• report number: 176
• language: English
• id: 9151393
• date added to LUP: 2024-05-17 10:04:12
• date last changed: 2024-05-17 10:04:12