Challenge Provider: CycleAI
Perception of risk impedes people from cycling. We aim to build an AI model to estimate a score of perceived road safety based on the objects in an image. Using Google Street View, a map of safety will be affordably created for entire cities, enhancing urban planning and policies.
Context
Nowadays, mobility is a priority theme for the European Union in the context of urban development - the EU even announced that funding for sustainable infrastructure, including for new or better bike lanes, will be doubled to €20 billion. At the same time, hundreds of people, including cyclists and pedestrians, lose their lives on our roads. We hesitate in commuting by bicycle simply because it is perceived as dangerous! As frequently referred in literature, pavement quality is a crucial factor to consider when evaluating safety. [1] [2] [3] Pavement quality refers to the quality of the road when there is no cycle lane, or to the cycle lane itself, when it is present. Along with the presence of water drainers and trails, these are one the most important risk factors.
Goals
This challenge addresses the 11 th United Nations Goal: Make cities and human settlements inclusive, safe, resilient, and sustainable. It directly targets goal 11.2 by improving road safety and contributing to an increase in cycling rates. One of the most affordable and healthy ways of transport. Thus, empowering those economically vulnerable with no means to afford a car.