|Cyclists face many adversities in their daily journeys, whether it is interactions with cars or ill-designed infrastructure and, as a result, these interactions affect their and other cyclists’ decisions to keep on cycling. In this sense, studying perceived risk and how different factors influence the perception of safety is key. Further, the link between how risk is perceived, and actual cycling risk is not fully know today. Current approaches on this topic are not scalable and focus mainly in performing interviews or deploying surveys.
With this in mind, I propose to research how to interlink data sensing, computer vision, image processing and signal processing to create an advantage over other research that has been carried on the topic of cyclists’ perception of safety.