Digital map systems can be categorized, based on the support they provide, into map navigation systems and map touring systems. Map navigation systems put more focus on helping travelers finding routes or directions instantly. By contrast, map touring systems such as Google Maps running on desktop computers are built to support users in developing their routes and survey knowledge before they go for travel. In this paper, traveler conceptual models are proposed as an interaction paradigm to enhance user immersion and interaction experience on map touring systems. A map touring system, MapXplorer, is also introduced as a proof of concept with its system design and implementation explained in detail. Twenty participants were invited to join the user study that investigates users' performance and preferences on navigation and exploration tasks. The results of experiments show that the proposed system surpasses traditional map touring systems on both navigation and exploration tasks for about 50 percent on average, and provides better user experience.

Navigation systems providing route-guidance and traffic information are one of the most widely used driver-support systems these days. Most navigation systems are based on the map paradigm which plots the driving route in an abstracted version of a two-dimensional electronic map. Recently, a new navigation paradigm was introduced that is based on the augmented reality (AR) paradigm which displays the driving route by superimposing virtual objects on the real scene. These two paradigms have their own innate characteristics from the point of human cognition, and so complement each other rather than compete with each other. Regardless of the paradigm, the role of any navigation system is to support the driver in achieving his driving goals. The objective of this work is to investigate how these map and AR navigation paradigms impact the achievement of the driving goals: productivity and safety. We performed comparative experiments using a driving simulator and computers with 38 subjects. For the effects on productivity, driver's performance on three levels (control level, tactical level, and strategic level) of driving tasks was measured for each map and AR navigation condition. For the effects on safety, driver's situation awareness of safety-related events on the road was measured. To find how these navigation paradigms impose visual cognitive workload on driver, we tracked driver's eye movements. As a special factor of driving performance, route decision making at the complex decision points such as junction, overpass, and underpass was investigated additionally. Participant's subjective workload was assessed using the Driving Activity Load Index (DALI). Results indicated that there was little difference between the two navigation paradigms on driving performance. AR navigation attracted driver's visual attention more frequently than map navigation and then reduces awareness of and proper action for the safety-related events. AR navigation was faster and better to support route decision making at the complex decision points. According to the subjective workload assessment, AR navigation was visually and temporally more demanding.