In-Car Navigation Systems: The Effects of Landmark Specificity and Map Rotation on Spatial Knowledge and Route Acquisition

Current in-car navigation systems do not refer to environmental landmarks when providing directions to drivers. Instead, they provide guidance by presenting drivers with distance-to-turn information. Default displays use track-up map orientations. These display conditions do not facilitate the acquisition of spatial knowledge. As a consequence, drivers using these systems are unlikely to acquire spatial knowledge needed to judge the reasonableness of the directions they are receiving, leaving them susceptible to accepting directions that are grossly incorrect and dangerous (Forbes and Burnett, 2007). Landmarks have been shown to be critical sources of information when people acquire both route and configural spatial knowledge. By providing landmark information, route and configural knowledge acquisition could potentially be enhanced. Two experiments compared the use of specific landmarks versus generic landmarks. Measures of both configural and route knowledge were obtained. Landmarks were presented either generically or specifically in voice directions or as visual icons on the display. Both Hunt\u27s distinctiveness theory (1993, 2003) and Paivio\u27s dual-coding theory (1973, 2006) indicate that participants hearing specific voice directions while simultaneously viewing specific visual icons would perform better than those experiencing the other combinations. The two experiments produced conflicting results. Experiment 1 found large effects of both landmark specificity and map orientation. Participants acquired better configural spatial knowledge with specific than generic visual icons. Also, north-up maps led to better configural spatial knowledge than track-up maps. Experiment 2, which modified the procedure somewhat, found no reliable differences

An Integrated Alerting and Notification System Utilizing Stages of Automation and Uncertainty Visualization

While NextGen operations are still under development, several key issues have already emerged, including increased information demands on the flight deck. The ALerting And Reasoning Management System (ALARMS) was designed as a strategic, automated system for combining and evaluating alert-related outputs from current and proposed NextGen systems. The modeldriven interface integrates the status of the environment, pilot, and system to automatically present the most critical information at the right time, augmenting existing flight deck technologies. The current level of uncertainty in the environment and system as a whole is also evaluated and represented within the display. The four stage model of information processing presented by Parasuraman, Sheridan, & Wickens (2000) was used to guide the development of the underlying ALARMS automation. This document provides a brief overview of the ALARMS development process. Examples of the interface are included, and we discuss its implications