Martin Raubal

Enriching Wayfinding Instructions with Local Landmarks

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.

Selection of Salient Features for Route Directions

People navigating in unfamiliar environments rely on wayfinding directions, either given by people familiar with the place, or given by maps or wayfinding services. The essential role of landmarks in human route communication is well-known. However, mapping the human ability to select landmarks ad hoc for route directions to a computational model was never tried before. Wayfinding services manage the problem by using predefined points of interest. These points are not automatically identified, and they are not related to any route. In contrast, here a computational model is presented that selects salient features along a route where needed, e.g., at decision points. We propose measures to formally specify the salience of a feature. The observed values of these measures are subject to stochastical tests in order to identify the most salient features from datasets. The proposed model is implemented and checked for computability with a use case from the city of Vienna. It is also crosschecked with a human subject survey for landmarks along a given route. The survey provides evidence that the proposed model selects features that are strongly correlated to human concepts of landmarks. Hence, integrating the selected salient features in wayfinding directions will produce directions with lower cognitive workload and higher success rates, compared to directions based only on geometry, or on geometry and static points of interest.

Correlating mobile phone usage and travel behavior - A case study of Harbin, China

Abstract Information and communication technologies (ICTs), such as mobile phones and the Internet, are increasingly pervasive in modern society. These technologies provide new resources for spatio-temporal data mining and geographic knowledge discovery. Since the development of ICTs also impacts physical movement of individuals in societies, much of the existing research has focused on examining the correlation between ICT and human mobility. In this paper, we aim to provide a deeper understanding of how usage of mobile phones correlates with individual travel behavior by exploring the correlation between mobile phone call frequencies and three indicators of travel behavior: (1) radius, (2) eccentricity, and (3) entropy. The methodology is applied to a large dataset from Harbin city in China. The statistical analysis indicates a significant correlation between mobile phone usage and all of the three indicators. In addition, we examine and demonstrate how explanatory factors, such as age, gender, social temporal orders and characteristics of the built environment, impact the relationship between mobile phone usage and individual activity behavior.

Map navigation with mobile devices: virtual versus physical movement with and without visual context

A user study was conducted to compare the performance of three methods for map navigation with mobile devices. These methods are joystick navigation, the dynamic peephole method without visual context, and the magic lens paradigm using external visual context. The joystick method is the familiar scrolling and panning of a virtual map keeping the device itself static. In the dynamic peephole method the device is moved and the map is fixed with respect to an external frame of reference, but no visual information is present outside the devices display. The magic lens method augments an external content with graphical overlays, hence providing visual context outside the device display. Here too motion of the device serves to steer navigation. We compare these methods in a study measuring user performance, motion patterns, and subjective preference via questionnaires. The study demonstrates the advantage of dynamic peephole and magic lens interaction over joystick interaction in terms of search time and degree of exploration of the search space.

User-Centred Time Geography for Location-Based Services

Abstract Location‐based services assist people in their decision‐making during the performance of tasks in space. They do not consider the users individual preferences, time constraints and possible subtasks to be performed. In order to account for these important aspects, a user‐centred spatio‐temporal theory of location‐based services is required. We propose such a theory by combining classical time geography with an extended theory of affordances. It assumes that affordances belong to three realms: physical, social‐institutional, and mental. In addition to covering the capability, coupling and authority constraints from time geography, this allows for a user‐centred perspective because affordances describe action possibilities with regard to a specific person. Furthermore, the integration of mental affordances offers the possibility to account for cognitive time constraints due to the duration of decision‐making processes. This new theory for location‐based services is closer to the individual user and more plausible with respect to their daily lives. A business traveller scenario is used as a case study to demonstrate this.

A Formal Model of the Process of Wayfinding in Built Environments

Previous recent research on human wayfinding has focused primarily on mental representations rather than processes of wayfinding. This paper presents a formal model of some aspects of the process of wayfinding, where appropriate elements of human perception and cognition are formally realized using image schemata and affordances. The goal-driven reasoning chain that leads to action begins with incomplete and imprecise knowledge derived from imperfect observations of space. Actions result in further observations, derived knowledge and, recursively, further actions, until the goal is achieved or the wayfinder gives up. This paper gives a formalization of this process, using a modal extension to classical propositional logic to represent incomplete knowledge. Both knowledge and action are represented through a wayfinding graph. A special case of wayfinding in a building, that is finding ones way through an airport, is used to demonstrate the formal model.

The semantics of similarity in geographic information retrieval

Similarity measures have a long tradition in fields such as information retrieval, artificial intelligence, and cognitive science. Within the last years, these measures have been extended and reused to measure semantic similarity; i.e., for comparing meanings rather than syntactic differences. Various measures for spatial applications have been de- veloped, but a solid foundation for answering what they measure; how they are best ap- plied in information retrieval; which role contextual information plays; and how similarity values or rankings should be interpreted is still missing. It is therefore difficult to decide which measure should be used for a particular application or to compare results from dif- ferent similarity theories. Based on a review of existing similarity measures, we introduce a framework to specify the semantics of similarity. We discuss similarity-based information retrieval paradigms as well as their implementation in web-based user interfaces for geo- graphic information retrieval to demonstrate the applicability of the framework. Finally, we formulate open challenges for similarity research.

Ontology and epistemology for agent-based wayfinding simulation

Agent-based systems are used to simulate the behaviour of people in various spatial environments. Designers of such systems need to give attention to ontological and epistemological concerns during the early stages of development to assure that the agent-based system is built upon a sound foundation. Only then is it possible to model the agents behaviour in a cognitively plausible way. This paper describes an ecological approach to model ontology and epistemology for agent-based wayfinding simulation. The ontology of the wayfinding environment is based on a subdivision into medium, substances, and surfaces. The epistemological model uses the concept of affordances, which we divide into physical, social-institutional, and mental affordances. Ontology and epistemology are both grounded in peoples descriptions of their wayfinding experiences. A case study of wayfinding in airports is used to demonstrate the applicability of the method for designing a simulation with a cognizing agent.

Semantic rules for context-aware geographical information retrieval

Geographical information retrieval (GIR) can benefit from context information to adapt the results to a users current situation and personal preferences. In this respect, semantics-based GIR is especially challenging because context information - such as collected from sensors - is often provided through numeric values, which need to be mapped to ontological representations based on nominal symbols. The Web Ontology Language (OWL) lacks mathematical processing capabilities that require free variables, so that even basic comparisons and distance calculations are not possible. Therefore, the context information cannot be interpreted with respect to the task and the current users preferences. In this paper, we introduce an approach based on semantic rules that adds these processing capabilities to OWL ontologies. The task of recommending personalized surf spots based on user location and preferences serves as a case study to evaluate the capabilities of semantic rules for context-aware geographical information retrieval. We demonstrate how the Semantic Web Rule Language (SWRL) can be utilized to model user preferences and how execution of the rules successfully retrieves surf spots that match these preferences. While SWRL itself enables free variables, mathematical functions are added via built-ins - external libraries that are dynamically loaded during rule execution. Utilizing the same mechanism, we demonstrate how SWRL built-ins can query the Semantic Sensor Web to enable the consideration of real-time measurements and thus make geographical information retrieval truly context-aware.

Measuring semantic similarity between geospatial conceptual regions

Determining the grade of semantic similarity between geospatial concepts is the basis for evaluating semantic interoperability of geographic information services and their users. Geometrical models, such as conceptual spaces, offer one way of representing geospatial concepts, which are modelled as n-dimensional regions. Previous approaches have suggested to measure semantic similarity between concepts based on their approximation by single points. This paper presents a way to measure semantic similarity between conceptual regions—leading to more accurate results. In addition, it allows for asymmetries by measuring directed similarities. Examples from the geospatial domain illustrate the similarity measure and demonstrate its plausibility.