K. Goldsberry

University of California, Santa Barbara



According to the 2005 Urban Mobility Report (Shrank and Lomax, 2006) Los Angeles, California has the worst traffic congestion in the United States. One problem is that drivers have insufficient resources for congestion avoidance. In cities like Los Angeles, drivers in pre-trip or en route situations need access to timely traffic information. Traditionally, this information has been relegated to radio and television reports. However, recent developments in distributed computing, in-car-navigation-systems, and location-based-services present newfound channels for real-time traffic communication. How can cartographers utilize these new channels to enhance the delivery of real-time traffic information in map form? This paper presents a new online traffic map designed specifically for the internet, and mobile devices. The map was created as a portion of my dissertation research at the University of California, Santa Barbara. Many of the map design decisions were guided by the findings of empirical research aimed at optimizing the intuitiveness of the map symbology. I measured human-subjects responses to several different design variables. This paper includes a summary of the experimental approach, the findings themselves, and the application of the findings toward an informed design. The collective goal of three main experiments was to reveal how and why some traffic map designs outperformed others. The central design variables include classification, representation, and symbolization. The design phase of the project employed scalable vector graphics to help create a versatile traffic mapping system capable of depicting and communicating traffic conditions in real-time over the internet. From a more conceptual standpoint, the project explores the role of human subjects evaluations as an early stage in intelligent map design. Since traffic maps have the potential to be among the most widely used maps in the world it is imperative that cartographers carefully consider their designs; this paper thoroughly examines traffic map design variables and their consequent impact on potential map-readers.