Title: Visual Analysis of In-car Communication Networks
Modern cars contain a wide spectrum of functionality, which is implemented by many interconnected electronic control units (ECUs). Overlooking all details of these increasingly complex in-car communication networks is a major challenge for developers. In our work, we have designed a number of analysis tools for in-car communication networks to enable developers to trace errors better and faster. By observing current working practices of automotive analysis experts, we found that the tools in use are mostly text-based and often fail to provide sufficient insight into correlations and overview aspects. They lack sophisticated visualization, navigation and data reduction techniques. Our research goal is to find novel and adapt existing methods of visual analytics (VA) and information visualization (InfoVis) to support the process of analyzing in-car communication networks. With a set of prototypes and their evaluation, we managed to provide concrete solutions and verify how in-car communication analysis can benefit form research in VA and InfoVis.