This project aims to simplify the situation for people with visual impairment in connection with travel by public transport, using mobile augmented reality (AR), open traffic data, digital twins and machine learning. The goal is to increase accessibility through digital tools, while at the same time supporting other public transport goals (lower cost, higher accessibility & better customer experience).
The main goal of the project is to build a working prototype based on modern technology for digital guidance in dynamic public transport situations and thereby increase accessibility. Furthermore, new knowledge about the ability of mobile technology is expected to be created, partly as a sensor in the context but also about how it can support different channels for communication with the user. Effect goals through the project are also to use new technical features in digital technology for a group of users in need of support. Further effects of the project are a reinforced regional cluster.
Much accessibility work focuses on physical environments, vehicle design and information about travelers and tickets. Often this is based on new infrastructure and new "gadgets", which drives costs. Society also places increasing confidence in the ability of public transport to contribute to the environment / climate work. This is happening at the same time as the cities are increasingly densified. It is therefore common for traffic operators to have more lines / departures using the same stops. Lines can also depart from different stops depending on the current traffic location or from different locations at the same stop. The on / off situation thus becomes dynamic. This development has made it more difficult for people with visual impairments to use public transport. There are also societal requirements for faster transport, among other things for public transport to seriously be an adequate remuneration for passenger cars, taxis or travel services.
The point of the project is to create a solution that accompanies the visually impaired in the dynamic public transport without requiring new physical installations, expensive equipment on vehicles or new aids to the needs owners. The solution integrates system solutions that apply digital twins, real-time open data and machine learning with the mobile sensor systems.