University of California Transportation Center

This dissertation summarizes research investigating the design of real-time traffic maps. As traffic congestion continues to burden our largest cities, and as the Internet continues to grow at a rapid pace, real-time traffic maps have the potential to be among the world’s most popular maps. Furthermore, as mobile devices and in-car-navigationsystems begin to connect to the Internet, millions of drivers will access and read these maps on an array of media. This dissertation reports on research aimed to understand as well as enhance the design of real-time traffic maps. The dissertation includes reviews of previous scientific research, as well as several online traffic maps from around the world. The dissertation also introduces new methods to design and empirically evaluate the performance of real-time traffic maps. The design methods are guided by established cartographic principles, as well as the findings of human subjects studies that reveal more intuitive cartographic strategies. The investigation pays particular attention to the influences of cartographic classification, and cartographic symbolization; the findings suggest that both classification and symbolization significantly influence how map readers perceive and respond to graphical depictions of traffic conditions. With this in mind, the research suggests it is imperative to not only understand the influence of design variables on map perception, but also to, as best as possible, link map design with map-readers’ perceptual preconceptions, and preferences. This idea of cognitive congruence represents a new challenge for all kinds of cartographers.