Cooperative, connected and automated mobility (CCAM) is a step further compared to the driving solutions of the past decade. The possibility of sharing up-to-date information about the state of the traffic infrastructure, or about any agent on the road, makes it possible to generate more complex decision systems in connected and automated vehicles. In that sense, the notion of what is happening around the vehicle, as well as the representation of relevant traffic events, becomes of vital importance for decision making processes in complex traffic situations. Before starting its journey, the vehicle systems need to have a robust and clear notion of the traffic scene, i.e. all those static and dynamic elements the vehicle can come up with while driving. Thus, this information, when processed, would provide sufficient semantics of the surroundings to find out what needs to be done next depending on the context. This chapter proposes the development and design of an information system that aims to generate the necessary data structures to represent the traffic scene information. This representation will serve, once integrated in an automated software ecosystem, to understand the traffic context and act accordingly to the semantics of the scene.