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.
Even though research has explored how other modalities can be used to provide navigation instructions (e.g. auditory instructions @cite_13 or haptic clues for mobile @cite_17 and wearable devices @cite_35 @cite_59 ), map-based navigation for mobile devices and turn-by-turn instructions for wearable devices have been established as de facto standards. For example, the current version of Google Maps for Android Wear smartwatches uses turns, street names, and distances to provide the user with instructions such as: After 20 ,m turn left into Denver Road''. Importantly, current navigation systems and applications typically do not include landmarks in their instructions.
@cite_35 @cite_13 @cite_59 @cite_17
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Navigation services communicate optimal routes to users by providing sequences of instructions for these routes. Each single instruction guides the wayfinder from one decision point to the next. The instructions are based on geometric data from the street network, which is typically the only dataset available. This paper addresses the question of enriching such wayfinding instructions with local landmarks. We propose measures to formally specify the landmark saliency of a feature. Values for these measures are subject to hypothesis tests in order to define and extract landmarks from datasets. The extracted landmarks are then integrated in the wayfinding instructions. A concrete example from the city of Vienna demonstrates the applicability and usefulness of the method. In this paper the design, development and evaluation of a GPS-based auditory navigation system is presented that implicitly guides a user by a contextualized rendering of personal audio files. The benefit of this navigation system is that the user can listen to his own audio contents while being navigated. Wearing headphones, the user listens to audio contents which are located in a virtual environment. The user simply walks in the direction where the sound seems to have its origin. A formal evaluation under field conditions proved that navigation with contextualized audio contents is efficient and intuitive and that users are highly satisfied with the navigation support given by the evaluated auditory display. In the past people have used very different forms of directions depending on how those directions were acquired. If a person is giving another person directions in a familiar area, he will frequently use landmarks to describe the route [10]. If the person gets the route from a personal navigation system though, it will be displayed on a map and make use of street names for the directions. In this paper we present a system to automatically give landmark based navigation to pedestrians by using panoramic imagery to both find salient landmarks along a route automatically, and to present those landmarks to a pedestrian navigator in an immersive and intuitive manner. Our system primarily uses automatically detected business signs as landmarks, and currently works in a half dozen cities around the world. We have also evaluated our system and found that people can effectively navigate solely using landmark enhanced panoramas of decision points along the route. This paper identifies the possibility of using electronic compasses and accelerometers in mobile phones, as a simple and scalable method of localization without war-driving. The idea is not fundamentally different from ship or air navigation systems, known for centuries. Nonetheless, directly applying the idea to human-scale environments is non-trivial. Noisy phone sensors and complicated human movements present practical research challenges. We cope with these challenges by recording a person's walking patterns, and matching it against possible path signatures generated from a local electronic map. Electronic maps enable greater coverage, while eliminating the reliance on WiFi infrastructure and expensive war-driving. Measurements on Nokia phones and evaluation with real users confirm the anticipated benefits. Results show a location accuracy of less than 11m in regions where today's localization services are unsatisfactory or unavailable.