Landmark-based navigation systems have proven benefits relative to traditional turn-by-turn systems that use street names and distances. However, one obstacle to the implementation of landmark-based navigation systems is the complex challenge of selecting salient local landmarks at each decision point for each user. In this paper, we present Pharos, a novel system that extends turn-by-turn navigation instructions using a single global landmark (e.g. the Eiffel Tower, the Burj Khalifa, municipal TV towers) rather than multiple, hard-to-select local landmarks. We first show that our approach is feasible in a large number of cities around the world through the use of computer vision to select global landmarks. We then present the results of a study demonstrating that by including global landmarks in navigation instructions, users navigate more confidently and build a more accurate mental map of the navigated area than using turn-by-turn instructions.
In general, landmarks have to be chosen carefully as their selection is highly important for the resulting quality of navigation instructions @cite_23 (e.g. the personal salience of a landmark could be effected by language or gender @cite_19 ). More specifically, Sorrows and Hirtle @cite_54 examined landmarks in real and electronic spaces and classified landmarks in terms of visual, cognitive and structural dimensions. Global landmarks have to be outstanding in all dimensions. Steck and Mallot @cite_27 investigated the role of global and local landmarks in virtual environment navigation. They found out that in virtual environments both local and global landmarks are used for wayfinding, but different participants rely on different strategies; some of the participants used only local landmarks while others only used global ones. This results in a key question for our work, as with Pharos we aim at improving pedestrian navigation instructions with only a single global landmark rather than multiple local landmarks.
@cite_19 @cite_54 @cite_27 @cite_23
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Navigation in unfamiliar cities often requires frequent map checking, which is troublesome for wayfinders. We propose a novel approach for improving real-world navigation by generating short, memorable and intuitive routes. To do so we detect useful landmarks for effective route navigation. This is done by exploiting not only geographic data but also crowd footprints in Social Network Services (SNS) and Location Based Social Networks (LBSN). Specifically, we detect point, area, and line landmarks by using three indicators to measure landmark's utility: visit popularity, direct visibility, and indirect visibility. We then construct an effective route graph based on the extracted landmarks, which facilitates optimal path search. In the experiments, we show that landmark-based routes out-perform the ones created by baseline from the perspectives of the lap time and the number of references necessary to check self-positions for adjusting route directions. Landmarks are significant in one's formation of a cognitive map of both physical environments and electronic information spaces. Landmarks are defined in physical space as having key characteristics that make them recognizable and memorable in the environment. The challenge of defining measurable features of landmarks that can be used in designing and recognizing landmarks in information spaces is explored. By drawing on diverse areas such as urban planning, architecture, cognitive science and hypertext, a coherent definition of a landmark is proposed, which is relevant to both physical and electronic spaces. It is argued that landmarks can be classified in terms of visual, cognitive and structural dimensions, which has implications for how environments can be designed or built in such a way that landmarks will emerge appropriately for unique situations. In visual navigation, landmarks can be used in a number of different ways. In this paper, we investigate the role of global and local landmarks in virtual environment navigation. We performed an experiment in a virtual environment called “Hexatown”, consisting of a regular hexagonal grid of streets and junctions. Each junction was identified by the presence of distinct local landmarks (buildings, phone box, and so on). Additionally, compass information or a global frame of reference was provided by global landmarks (hilltop, television tower, and city skyline). According to participants' movement decisions, egomotion was simulated, and displayed on a 180 deg. projection screen. Participants learned the route back and forth between two local landmarks. In the test phase, individual junctions were approached and the participant's movement decision was recorded. We performed two experiments involving landmark changes after learning. In the first, we used conflicting cues by transposing landmarks. In the second experiment, we reduced either local or global landmark information. Results show that both local and global landmarks are used in wayfinding decisions. However, different participants rely on different strategies. In the first experiment (cue conflict) for example, some of the participants used only local landmarks while others relied exclusively on global landmarks. Other participants used local landmarks at one location and global landmarks at the other. When removing one landmark type in the second experiment, the other type could be used by almost all participants, indicating that information about the neglected landmark type was present in memory. Pedestrian-navigation services enable people to retrieve precise instructions to reach a specific location. However, the development of mobile spatial-information technologies for pedestrians is still at the beginning and faces several difficulties. As the spatial behavior of people on foot differs in many ways from the driver's performance, common concepts for car-navigation services are not suitable for pedestrian navigation. Particularly, the usage of landmarks is vitally important in human navigation. This contribution points out the main requirements for pedestrian-navigation technologies and presents an approach to identify pedestrian flows and to imply landmark information into navigation services for pedestrians