56 research outputs found
Hierarchical Graphs as Organisational Principle and Spatial Model Applied to Pedestrian Indoor Navigation
In this thesis, hierarchical graphs are investigated from two different angles – as a general modelling principle for (geo)spatial networks and as a practical means to enhance navigation in buildings. The topics addressed are of interest from a multi-disciplinary point of view, ranging from Computer Science in general over Artificial Intelligence
and Computational Geometry in particular to other fields such as Geographic Information Science.
Some hierarchical graph models have been previously proposed by the research community, e.g. to cope with the massive size of road networks, or as a conceptual model for human wayfinding. However, there has not yet been a comprehensive, systematic approach for modelling spatial networks with hierarchical graphs. One particular
problem is the gap between conceptual models and models which can be readily used in practice. Geospatial data is commonly modelled - if at all - only as a flat graph. Therefore, from a practical point of view, it is important to address the automatic construction of a graph hierarchy based on the predominant data models. The work presented deals with this problem: an automated method for construction is introduced and explained. A particular contribution of my thesis is the proposition to use hierarchical graphs as the basis for an extensible, flexible architecture for modelling various (geo)spatial networks. The proposed approach complements classical graph models very well in the sense that their expressiveness is extended: various graphs originating from different
sources can be integrated into a comprehensive, multi-level model.
This more sophisticated kind of architecture allows for extending navigation services beyond the borders of one single spatial network to a collection of heterogeneous networks, thus establishing a meta-navigation service. Another point of discussion is the impact of the hierarchy and distribution on graph algorithms. They have to be
adapted to properly operate on multi-level hierarchies.
By investigating indoor navigation problems in particular, the guiding principles are demonstrated for modelling networks at multiple levels of detail. Complex environments like large public buildings are ideally suited to demonstrate the versatile use of hierarchical
graphs and thus to highlight the benefits of the hierarchical approach.
Starting from a collection of floor plans, I have developed a systematic method for constructing a multi-level graph hierarchy. The nature of indoor environments, especially their inherent diversity, poses an additional challenge: among others, one must deal with complex, irregular, and/or three-dimensional features. The proposed method is also motivated by practical considerations, such as not only finding shortest/fastest paths across rooms and floors, but also by providing descriptions for these paths which are easily understood by people.
Beyond this, two novel aspects of using a hierarchy are discussed: one as an informed heuristic exploiting the specific characteristics of indoor environments in order to enhance classical, general-purpose graph search techniques. At the same time, as a convenient by-
product of this method, clusters such as sections and wings can be detected. The other reason is to better deal with irregular, complex-shaped regions in a way that instructions can also be provided for these spaces. Previous approaches have not considered this problem.
In summary, the main results of this work are:
• hierarchical graphs are introduced as a general spatial data infrastructure. In particular, this architecture allows us to integrate different spatial networks originating from different sources. A small but useful set of operations is proposed for integrating these networks. In order to work in a hierarchical model, classical graph algorithms are generalised. This finding also has implications on the possible integration of separate
navigation services and systems;
• a novel set of core data structures and algorithms have been devised for modelling indoor environments. They cater to the unique characteristics of these environments and can be specifically used to provide enhanced navigation in buildings. Tested on models of several real buildings from our university, some preliminary but promising results were gained from a prototypical implementation and its application on the models
DESIGNING A MULTI-AGENT FRAMEWORK FOR UNMANNED AERIAL/GROUND VEHICLES
Ph.DDOCTOR OF PHILOSOPH
LIPIcs, Volume 277, GIScience 2023, Complete Volume
LIPIcs, Volume 277, GIScience 2023, Complete Volum
Algorithm Engineering for Realistic Journey Planning in Transportation Networks
Diese Dissertation beschäftigt sich mit der Routenplanung in Transportnetzen. Es werden neue, effiziente algorithmische Ansätze zur Berechnung optimaler Verbindungen in öffentlichen Verkehrsnetzen, Straßennetzen und multimodalen Netzen, die verschiedene Transportmodi miteinander verknüpfen, eingeführt. Im Fokus der Arbeit steht dabei die Praktikabilität der Ansätze, was durch eine ausführliche experimentelle Evaluation belegt wird
Proceedings of the GIS Research UK 18th Annual Conference GISRUK 2010
This volume holds the papers from the 18th annual GIS Research UK (GISRUK). This year the conference, hosted at University College London (UCL), from Wednesday 14 to Friday 16 April 2010. The conference covered the areas of core geographic information science research as well as applications domains such as crime and health and technological developments in LBS and the geoweb.
UCL’s research mission as a global university is based around a series of Grand Challenges that affect us all, and these were accommodated in GISRUK 2010.
The overarching theme this year was “Global Challenges”, with specific focus on the following themes:
* Crime and Place
* Environmental Change
* Intelligent Transport
* Public Health and Epidemiology
* Simulation and Modelling
* London as a global city
* The geoweb and neo-geography
* Open GIS and Volunteered Geographic Information
* Human-Computer Interaction and GIS
Traditionally, GISRUK has provided a platform for early career researchers as well as those with a significant track record of achievement in the area. As such, the conference provides a welcome blend of innovative thinking and mature reflection. GISRUK is the premier academic GIS conference in the UK and we are keen to maintain its outstanding record of achievement in developing GIS in the UK and beyond
An Approach to Pathfinding for Real-World Situations
People plan their routes through new environments every day, but what factors influence these wayfinding decisions? In a world increasingly dependent on electronic navigation assistance devices, finding a way of automatically selecting routes suitable for
pedestrian travel is an important challenge. With a greater freedom of movement than vehicular transport, and different requirements, an alternative approach should be taken to find an answer for pedestrian journeys than those taken in cars. Although previous research
has produced a number of pedestrian route recommendation systems, the majority of these are restricted to a single route type or user group. The aim of this research was to
develop an approach to route suggestion which could recommend routes according to the type of journey (everyday, leisure or tourist) a person is making. To achieve this aim, four areas of research were undertaken.
Firstly, six experiments containing 450 participants were used to investigate the preference of seven different environment and route attributes (length, turns, decision points, vegetation, land use, dwellings and points of interest) for two attribute categories (simplicity
and attractiveness) and three journey types (everyday, leisure and tourist). These empirically determined preferences were then used to find the rank-orders of the attributes, by comparing more of them simultaneously than earlier studies, and found either new rankings (for attractiveness, leisure journeys and tourist journey) or extended those already known (everyday journeys).
Using these ranks and previously accepted relationships, an environment model was defined and built based on an annotated graph. This model can be built automatically
from OpenStreetMap data, and is therefore simple enough to be applicable to many geographical areas, but it is detailed enough to allow route selection.
Algorithms based on an extended version of Dijkstra’s shortest path algorithm were constructed. These used weighted minimum cost functions linked with attribute ranks, to select routes for different journey types. By avoiding the computational complexity of previous approaches, these algorithms could potentially be widely used in a variety of different platforms, and extended for different groups of users.
Finally, the routes suggested by the algorithms were compared to participant recommendations for ‘simple’ routes with five start/end points, and for each of the three journey types (everyday, leisure and tourist). These comparisons determined that only length is required to select simple and everyday routes, but that the multi-attribute cost functions developed for leisure and tourist journeys select routes that are similar to those chosen by the participants. This indicates that the algorithms’ routes are appropriate for people to
use in leisure and tourist journeys
12th International Conference on Geographic Information Science: GIScience 2023, September 12–15, 2023, Leeds, UK
No abstract available
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