Route schematization with landmarks

Predominant navigation applications make use of a turn-by-turn instructions approach and are mostly supported by small screen devices. This combination does little to improve users\u27 orientation or spatial knowledge acquisition. Considering this limitation, we propose a route schematization method aimed for small screen devices to facilitate the readability of route information and survey knowledge acquisition. Current schematization methods focus on the route path and ignore context information, specially polygonal landmarks (such as lakes, parks, and regions), which is crucial for promoting orientation. Our schematization method, in addition to the route path, takes as input: adjacent streets, point-like landmarks, and polygonal landmarks. Moreover, our schematic route map layout highlights spatial relations between route and context information, improves the readability of turns at decision points, and the visibility of survey information on small screen devices. The schematization algorithm combines geometric transformations and integer linear programming to produce the maps. The contribution of this paper is a method that produces schematic route maps with context information to support the user in wayfinding and orientation

This is the tricky part: When directions become difficult

Automated route guidance systems, both web-based systems and en-route systems, have become commonplace in recent years. These systems often replace humangenerated directions, which are often incomplete, vague, or in error. However, humangenerated directions have the ability to differentiate between easy and complex steps through language in a way that is more difficult in automated systems. This article examines a set of human-generated verbal directions to better understand why some parts of directions are perceived as being more difficult than the remaining steps. Insights from this analysis will lead to recommendations to improve the next generation of automated route guidance systems

This is the tricky part: When directions become difficult

Automated route guidance systems, both web-based systems and en-route systems, have become commonplace in recent years. These systems often replace human-generated directions, which are often incomplete, vague, or in error. However, human-generated directions have the ability to differentiate between easy and complex steps through language in a way that is more difficult in automated systems. This article examines a set of human-generated verbal directions to better understand why some parts of directions are perceived as being more difficult than the remaining steps. Insights from this analysis will lead to recommendations to improve the next generation of automated route guidance systems

How human schematization and systematic errors take effect on sketch map formalizations

Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial TechnologiesSketch map is an important way to represent spatial information used in many geospatial reasoning tasks (Forbus, K., Usher, J., & Chapman, V. 2004). Compared with verbal or textual language, sketch map is a more interactive mode that more directly supports human spatial thinking and thus is a more natural way to reflect how people perceive properties of spatial objects and their spatial relations. One challenging application of sketch maps is called Spatial-Query-by-Sketch proposed by Egenhofer. Being a design of query language for geographic information systems (GISs), it allows a user to formulate a spatial query by drawing the desired spatial configuration with a pen on a touch-sensitive computer screen and get it translated into a symbolic representation to be processed against a geographic database (Egenhofer, M. 1997). During the period of sketch map drawing, errors due to human spatial cognition in mind may occur. A ready example is as follows: distance judgments for route are judged longer when the route has many turns or landmarks or intersections (Tversky, B. 2002). Direction get straightened up in memory. When Parisians were asked to sketch maps of their city, the Seine was drawn as a curve, but straighter than it actually is (Milgram, S. and Jodelet, D. 1976). Similarly, buildings and streets with different shapes are often simply depicted as schematic figures like blobs and lines. These errors are neither random nor due solely to ignorance; rather they appear to be a consequence of ordinary perceptual and cognitive processes (Tversky, 2003). Therefore, when processing sketch map analysis and representing it in a formal way, like Egenhofer's analysis approach for Spatial-Query-by-Sketch, the resulting formalization must necessarily be wrong if it does not account for the fact that some spatial information is distorted or omitted by humans. Therefore, when sketch map analysis is processed and represented in a formal way same as Egenhofer’s analytical approach to Spatial-Query-by-Sketch, the resulting formalization is simply erroneous since it never takes into account the fact that some spatial information is distorted or neglected in human perceptions. Though Spatial-Query-by-Sketch overcomes the limitations of conventional spatial query language by taking into consideration those alternative interaction methods between users and data, it is still not always true that accuracy of its query results is reliable.(...

Schematic bus transit maps for the web using genetic algorithms

Dissertation submitted in partial fulfilment of the requirements for the degree of Master of Science in Geospatial TechnologiesThe octilinear schematic map, layout recognized worldwide in metro maps, is an important transit informative tool. This research investigates how algorithms for the visualization of schematic maps can be availed in mobile web devices context in order to empower the efficiency in transmitting information of bus transit maps. A genetic algorithm for path octilinear schematization technique has been used and tested to create the schematic data. Location-based and interactivity functionalities were embedded to the resulting digital maps in order to create personalized maps to meet specific user needs. A prototype of a web application and real transit data of the city of Castellón in Spain was used to test the methodology. The results have shown that real time schematizations open possibilities concerning usability that add extra value to schematic transit maps. Additionally, suggested improvements have been made to the genetic algorithm and performance tests show that genetic algorithms are adequate, in terms of efficiency, to sketch bus transit maps automatically

Personal Wayfinding Assistance

We are traveling many different routes every day. In familiar environments it is easy for us to find our ways. We know our way from bedroom to kitchen, from home to work, from parking place to office, and back home at the end of the working day. We have learned these routes in the past and are now able to find our destination without having to think about it. As soon as we want to find a place beyond the demarcations of our mental map, we need help. In some cases we ask our friends to explain us the way, in other cases we use a map to find out about the place. Mobile phones are increasingly equipped with wayfinding assistance. These devices are usually at hand because they are handy and small, which enables us to get wayfinding assistance everywhere where we need it. While the small size of mobile phones makes them handy, it is a disadvantage for displaying maps. Geographic information requires space to be visualized in order to be understandable. Typically, not all information displayed in maps is necessary. An example are walking ways in parks for car drivers, they are they are usually no relevant route options. By not displaying irrelevant information, it is possible to compress the map without losing important information. To reduce information purposefully, we need information about the user, the task at hand, and the environment it is embedded in. In this cumulative dissertation, I describe an approach that utilizes the prior knowledge of the user to adapt maps to the to the limited display options of mobile devices with small displays. I focus on central questions that occur during wayfinding and relate them to the knowledge of the user. This enables the generation of personal and context-specific wayfinding assistance in the form of maps which are optimized for small displays. To achieve personalized assistance, I present algorithmic methods to derive spatial user profiles from trajectory data. The individual profiles contain information about the places users regularly visit, as well as the traveled routes between them. By means of these profiles it is possible to generate personalized maps for partially familiar environments. Only the unfamiliar parts of the environment are presented in detail, the familiar parts are highly simplified. This bears great potential to minimize the maps, while at the same time preserving the understandability by including personally meaningful places as references. To ensure the understandability of personalized maps, we have to make sure that the names of the places are adapted to users. In this thesis, we study the naming of places and analyze the potential to automatically select and generate place names. However, personalized maps only work for environments the users are partially familiar with. If users need assistance for unfamiliar environments, they require complete information. In this thesis, I further present approaches to support uses in typical situations which can occur during wayfinding. I present solutions to communicate context information and survey knowledge along the route, as well as methods to support self-localization in case orientation is lost

Information measures and cognitive limits in multilayer navigation

Cities and their transportation systems become increasingly complex and multimodal as they grow, and it is natural to wonder if it is possible to quantitatively characterize our difficulty to navigate in them and whether such navigation exceeds our cognitive limits. A transition between different searching strategies for navigating in metropolitan maps has been observed for large, complex metropolitan networks. This evidence suggests the existence of another limit associated to the cognitive overload and caused by large amounts of information to process. In this light, we analyzed the world's 15 largest metropolitan networks and estimated the information limit for determining a trip in a transportation system to be on the order of 8 bits. Similar to the "Dunbar number," which represents a limit to the size of an individual's friendship circle, our cognitive limit suggests that maps should not consist of more than about $250$ connections points to be easily readable. We also show that including connections with other transportation modes dramatically increases the information needed to navigate in multilayer transportation networks: in large cities such as New York, Paris, and Tokyo, more than $80\%$ of trips are above the 8-bit limit. Multimodal transportation systems in large cities have thus already exceeded human cognitive limits and consequently the traditional view of navigation in cities has to be revised substantially.Comment: 16 pages+9 pages of supplementary materia

Influence of Motivation on Wayfinding

This research explores the role of affect in the domain of human wayfinding by asking if increased motivation will alter the performance across various routes of increasing complexity. Participants were asked to perform certain navigation tasks within an indoor Virtual Reality (VR) environment under either motivated and not-motivated instructions. After being taught to navigate along simple and complex routes, participants were tested on both the previously learned routes and new routes that could be implicitly derived from the prior spatial knowledge. Finally, participants were tested on their ability to follow schematized instructions to explore familiar and unfamiliar areas in the VR environment. Performance of the various spatial tasks across the motivated and control groups indicated that motivation improved performance in all but the most complex conditions. Results of the empirical study were used to create a theoretical model that accounts for the influence of affect on the access of route knowledge. Results of the research suggest the importance of including past knowledge and affect of the traveler as components of future wayfinding systems