This thesis contributes to the design of new methods for the visual analysis of road traffic data. As recent technological advances provide traffic data with a finer and more varied spatial and temporal granularity, traffic experts and operators need new ways to explore, make sense and communicate such data. The first part of the manuscript addresses the problem of univariate analysis (found in e.g., traffic density and traffic flow data) by proposing an interactive categorization method based on Fuzzy Logic theory. The second part focuses on the analysis of the spatial component of road traffic which is inherent in this data type, by generalizing OriginDestinations maps with a technique that preserves both explicit relationships (spatial trajectories) and implicit relationships (abstract attributes of those trajectories) of datasets, using spatial nesting. The third part focuses on the problem of temporal analysis which is also an important component of traffic flows with an interactive technique to explore temporal changes using a set-based approach. The last section discusses the three techniques introduced in the manuscript, how to apply them beyond traffic data and how to deploy them in road traffic control centers.