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Documents authored by Manley, Ed

Document
Complete Volume
DOI: 10.4230/LIPIcs.COSIT.2026
LIPIcs, Volume 393, COSIT 2026, Complete Volume

Authors: Sabine Timpf, Gabriele Filomena, Armand Kapaj, Rui Zhu, Nicholas A. Giudice, and Ed Manley

Published in: LIPIcs, Volume 393, 17th International Conference on Spatial Information Theory (COSIT 2026)

Abstract
LIPIcs, Volume 393, COSIT 2026, Complete Volume
Cite as

17th International Conference on Spatial Information Theory (COSIT 2026). Leibniz International Proceedings in Informatics (LIPIcs), Volume 393, pp. 1-498, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026)

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@Proceedings{timpf_et_al:LIPIcs.COSIT.2026,
  title =	{{LIPIcs, Volume 393, COSIT 2026, Complete Volume}},
  booktitle =	{17th International Conference on Spatial Information Theory (COSIT 2026)},
  pages =	{1--498},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-438-3},
  ISSN =	{1868-8969},
  year =	{2026},
  volume =	{393},
  editor =	{Timpf, Sabine and Filomena, Gabriele and Kapaj, Armand and Zhu, Rui and Giudice, Nicholas A. and Manley, Ed},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.COSIT.2026},
  URN =		{urn:nbn:de:0030-drops-278484},
  doi =		{10.4230/LIPIcs.COSIT.2026},
  annote =	{Keywords: LIPIcs, Volume 393, COSIT 2026, Complete Volume}
}
Document
Front Matter
DOI: 10.4230/LIPIcs.COSIT.2026.0
Front Matter, Table of Contents, Preface, Conference Organization

Authors: Sabine Timpf, Gabriele Filomena, Armand Kapaj, Rui Zhu, Nicholas A. Giudice, and Ed Manley

Published in: LIPIcs, Volume 393, 17th International Conference on Spatial Information Theory (COSIT 2026)

Abstract
Front Matter, Table of Contents, Preface, Conference Organization
Cite as

17th International Conference on Spatial Information Theory (COSIT 2026). Leibniz International Proceedings in Informatics (LIPIcs), Volume 393, pp. 0:i-0:xiv, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026)

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@InProceedings{timpf_et_al:LIPIcs.COSIT.2026.0,
  author =	{Timpf, Sabine and Filomena, Gabriele and Kapaj, Armand and Zhu, Rui and Giudice, Nicholas A. and Manley, Ed},
  title =	{{Front Matter, Table of Contents, Preface, Conference Organization}},
  booktitle =	{17th International Conference on Spatial Information Theory (COSIT 2026)},
  pages =	{0:i--0:xiv},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-438-3},
  ISSN =	{1868-8969},
  year =	{2026},
  volume =	{393},
  editor =	{Timpf, Sabine and Filomena, Gabriele and Kapaj, Armand and Zhu, Rui and Giudice, Nicholas A. and Manley, Ed},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.COSIT.2026.0},
  URN =		{urn:nbn:de:0030-drops-278462},
  doi =		{10.4230/LIPIcs.COSIT.2026.0},
  annote =	{Keywords: Front Matter, Table of Contents, Preface, Conference Organization}
}
Document
Short Paper
DOI: 10.4230/LIPIcs.COSIT.2026.25
Document Geocoding for Inferring Spatial Familiarity Within Reddit Text (Short Paper)

Authors: Paddy Smith, Myles Gould, and Ed Manley

Published in: LIPIcs, Volume 393, 17th International Conference on Spatial Information Theory (COSIT 2026)

Abstract
In this paper, we reframe social media user geolocation as a task of inferring a user’s spatial familiarity. We propose an LLM-based approach that identifies places a user is most familiar, including the strength of familiarity. We evaluate this approach using two Reddit evaluation corpora constructed from subreddit user-flair tags: Reddit-London, where users are associated with London boroughs, and Reddit-USA, where users are associated with US states. We compare these datasets with GeoText benchmark dataset. The results show that LLMs can recover place-associated labels from social media text, achieving the strongest performance on Reddit-USA state prediction and moderate performance on fine-grained London borough prediction. We further show that inferred familiar places exhibit clear spatial dependency. Using polygon-based metrics, familiar places inferred from Reddit-London users have a mean distance to labeled boundary of 3.48 km, while Reddit-USA shows stronger alignment with state labels compared to GeoText, with higher inside-label share, and lower spatial dispersion. These findings suggest spatial familiarity provides a useful alternative framing for social media user geolocation, and that Reddit flair-based labels are more closely aligned with expressed spatial familiarity than home location labels in GeoText benchmark dataset.
Cite as

Paddy Smith, Myles Gould, and Ed Manley. Document Geocoding for Inferring Spatial Familiarity Within Reddit Text (Short Paper). In 17th International Conference on Spatial Information Theory (COSIT 2026). Leibniz International Proceedings in Informatics (LIPIcs), Volume 393, pp. 25:1-25:10, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026)

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@InProceedings{smith_et_al:LIPIcs.COSIT.2026.25,
  author =	{Smith, Paddy and Gould, Myles and Manley, Ed},
  title =	{{Document Geocoding for Inferring Spatial Familiarity Within Reddit Text}},
  booktitle =	{17th International Conference on Spatial Information Theory (COSIT 2026)},
  pages =	{25:1--25:10},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-438-3},
  ISSN =	{1868-8969},
  year =	{2026},
  volume =	{393},
  editor =	{Timpf, Sabine and Filomena, Gabriele and Kapaj, Armand and Zhu, Rui and Giudice, Nicholas A. and Manley, Ed},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.COSIT.2026.25},
  URN =		{urn:nbn:de:0030-drops-275698},
  doi =		{10.4230/LIPIcs.COSIT.2026.25},
  annote =	{Keywords: spatial familiarity, document geocoding, geoparsing, LLMs}
}
Document
Short Paper
DOI: 10.4230/LIPIcs.COSIT.2026.28
Using Social Cues for Wayfinding: An Eye-Tracking Study of Attention Allocation and Evidence Accumulation in a Virtual Reality T-Intersection (Short Paper)

Authors: Yu Qiao, Carlo Campagnoli, and Ed Manley

Published in: LIPIcs, Volume 393, 17th International Conference on Spatial Information Theory (COSIT 2026)

Abstract
In synchronous weak social wayfinding, route decisions are shaped in real time by others’ behaviour, yet the sampling and integration of social information during decision-making remain poorly understood. We investigated whether attention to pedestrians in a virtual-reality T-intersection reflects evidence accumulation preceding route commitment. Participants navigated scenes containing avatar crowds in which crowd size, proportion of credible others, directional majority, walking speed, and movement style were manipulated in an incomplete within-subjects orthogonal design. Continuous eye tracking measured attention to social cues, the destination landmark, and the surrounding scene. Results showed that gaze was directed predominantly toward social cues, whereas direct inspection of the landmark was rare. Among the manipulated factors, movement style and walking speed produced the clearest, though small, effects on fixation–saccade dynamics. Crucially, social gaze rose sharply early in the trial and then declined gradually before route commitment, suggesting that participants initially sampled social evidence and progressively reduced inspection as the decision unfolded. These findings indicate that social navigation involves accumulating and integrating others’ behaviour over time rather than simply following them.
Cite as

Yu Qiao, Carlo Campagnoli, and Ed Manley. Using Social Cues for Wayfinding: An Eye-Tracking Study of Attention Allocation and Evidence Accumulation in a Virtual Reality T-Intersection (Short Paper). In 17th International Conference on Spatial Information Theory (COSIT 2026). Leibniz International Proceedings in Informatics (LIPIcs), Volume 393, pp. 28:1-28:9, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026)

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@InProceedings{qiao_et_al:LIPIcs.COSIT.2026.28,
  author =	{Qiao, Yu and Campagnoli, Carlo and Manley, Ed},
  title =	{{Using Social Cues for Wayfinding: An Eye-Tracking Study of Attention Allocation and Evidence Accumulation in a Virtual Reality T-Intersection}},
  booktitle =	{17th International Conference on Spatial Information Theory (COSIT 2026)},
  pages =	{28:1--28:9},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-438-3},
  ISSN =	{1868-8969},
  year =	{2026},
  volume =	{393},
  editor =	{Timpf, Sabine and Filomena, Gabriele and Kapaj, Armand and Zhu, Rui and Giudice, Nicholas A. and Manley, Ed},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.COSIT.2026.28},
  URN =		{urn:nbn:de:0030-drops-275723},
  doi =		{10.4230/LIPIcs.COSIT.2026.28},
  annote =	{Keywords: Social navigation, wayfinding, eye tracking, virtual reality, evidence accumulation, attention}
}
Document
Short Paper
DOI: 10.4230/LIPIcs.COSIT.2026.34
Simulating Path Integration with Continuous Attractor Neural Networks (Short Paper)

Authors: Yulin Wu and Ed Manley

Published in: LIPIcs, Volume 393, 17th International Conference on Spatial Information Theory (COSIT 2026)

Abstract
This paper explores how grid cell-inspired neural dynamics can simulate path integration during human navigation. We combine smartphone GPS traces, trajectory interpolation, and a two-dimensional continuous attractor neural network (2D CANN) to model path integration in York and Leeds, United Kingdom. The model reproduces grid cell-like firing and estimates trajectories that closely match mapped movement. We further introduce a logarithmic psychophysical transformation of velocity to examine how perceived speed may distort cognitive spatial structure, especially under mixed transportation modes. The results suggest that velocity-driven path integration can computationally account for asymmetric distance estimation and cognitive collage-like distortions in urban environments.
Cite as

Yulin Wu and Ed Manley. Simulating Path Integration with Continuous Attractor Neural Networks (Short Paper). In 17th International Conference on Spatial Information Theory (COSIT 2026). Leibniz International Proceedings in Informatics (LIPIcs), Volume 393, pp. 34:1-34:8, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026)

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@InProceedings{wu_et_al:LIPIcs.COSIT.2026.34,
  author =	{Wu, Yulin and Manley, Ed},
  title =	{{Simulating Path Integration with Continuous Attractor Neural Networks}},
  booktitle =	{17th International Conference on Spatial Information Theory (COSIT 2026)},
  pages =	{34:1--34:8},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-438-3},
  ISSN =	{1868-8969},
  year =	{2026},
  volume =	{393},
  editor =	{Timpf, Sabine and Filomena, Gabriele and Kapaj, Armand and Zhu, Rui and Giudice, Nicholas A. and Manley, Ed},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.COSIT.2026.34},
  URN =		{urn:nbn:de:0030-drops-275784},
  doi =		{10.4230/LIPIcs.COSIT.2026.34},
  annote =	{Keywords: cognitive map, grid cell, continuous attractor neural network, path integration, spatial cognition, urban mobility}
}
Document
Short Paper
DOI: 10.4230/LIPIcs.COSIT.2024.24
Towards a General Framework for Co-Location (Short Paper)

Authors: Keiran Suchak and Ed Manley

Published in: LIPIcs, Volume 315, 16th International Conference on Spatial Information Theory (COSIT 2024)

Abstract
Previous studies into co-location exist in a variety of fields such as epidemiology and human mobility. In each field, researchers are interested identifying points of co-location amongst members of a population. In each of these fields, however, the definition of what it means for members of the population to be co-located may differ; furthermore, the ways in which data are collected vary. This piece of work aims to provide an initial outline of a general framework for identifying points of co-location. It demonstrates that the identification of co-location points between individuals is sensitive to the way in which co-location is defined in each context, as well as the types of data used. Furthermore, it highlights the impact that uncertainty in observations can have on our ability to reliably identify co-location.
Cite as

Keiran Suchak and Ed Manley. Towards a General Framework for Co-Location (Short Paper). In 16th International Conference on Spatial Information Theory (COSIT 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 315, pp. 24:1-24:10, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{suchak_et_al:LIPIcs.COSIT.2024.24,
  author =	{Suchak, Keiran and Manley, Ed},
  title =	{{Towards a General Framework for Co-Location}},
  booktitle =	{16th International Conference on Spatial Information Theory (COSIT 2024)},
  pages =	{24:1--24:10},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-330-0},
  ISSN =	{1868-8969},
  year =	{2024},
  volume =	{315},
  editor =	{Adams, Benjamin and Griffin, Amy L. and Scheider, Simon and McKenzie, Grant},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.COSIT.2024.24},
  URN =		{urn:nbn:de:0030-drops-208391},
  doi =		{10.4230/LIPIcs.COSIT.2024.24},
  annote =	{Keywords: human mobility, co-location, contact tracing}
}
Document
Short Paper
DOI: 10.4230/LIPIcs.GIScience.2023.45
National-Scale Spatiotemporal Variation in Driver Navigation Behaviour and Route Choice (Short Paper)

Authors: Elliot Karikari, Manon Prédhumeau, Peter Baudains, and Ed Manley

Published in: LIPIcs, Volume 277, 12th International Conference on Geographic Information Science (GIScience 2023)

Abstract
Understanding human behaviour is an integral task in GIScience, facilitated by increasingly large and descriptive datasets on human activity. Large-scale trajectory data have been particularly useful in measuring behaviours in different contexts, and understanding the relationship between the built environment and people. Yet, to date, most of these studies have focused on urban or regional scale analyses, with less exploration of behavioural variation at larger spatial scales. Human navigation behaviour is inherently linked to variation in spatial structure, and a study of national variations could help to better understand this variability. In this paper, we analyse GPS data from over 1 million journeys by 50,000 connected cars across the UK. Some key statistics relating to route choice are computed, and their variations are explored over time and space. A k-mean clustering of the trips identifies different types of trips and shows that their distribution varies by time of day and across the country. The insights gained from the data highlight spatio-temporal variations in road navigation, which should be considered in transportation modelling and planning.
Cite as

Elliot Karikari, Manon Prédhumeau, Peter Baudains, and Ed Manley. National-Scale Spatiotemporal Variation in Driver Navigation Behaviour and Route Choice (Short Paper). In 12th International Conference on Geographic Information Science (GIScience 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 277, pp. 45:1-45:6, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@InProceedings{karikari_et_al:LIPIcs.GIScience.2023.45,
  author =	{Karikari, Elliot and Pr\'{e}dhumeau, Manon and Baudains, Peter and Manley, Ed},
  title =	{{National-Scale Spatiotemporal Variation in Driver Navigation Behaviour and Route Choice}},
  booktitle =	{12th International Conference on Geographic Information Science (GIScience 2023)},
  pages =	{45:1--45:6},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-288-4},
  ISSN =	{1868-8969},
  year =	{2023},
  volume =	{277},
  editor =	{Beecham, Roger and Long, Jed A. and Smith, Dianna and Zhao, Qunshan and Wise, Sarah},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.GIScience.2023.45},
  URN =		{urn:nbn:de:0030-drops-189404},
  doi =		{10.4230/LIPIcs.GIScience.2023.45},
  annote =	{Keywords: Connected Car, Geospatial big Data, Navigation Behaviour, Cluster Analysis}
}
Document
Short Paper
DOI: 10.4230/LIPIcs.COSIT.2022.25
Collaborative Wayfinding Under Distributed Spatial Knowledge (Short Paper)

Authors: Panagiotis Mavros, Saskia Kuliga, Ed Manley, Hilal Rohaidi Fitri, Michael Joos, and Christoph Hölscher

Published in: LIPIcs, Volume 240, 15th International Conference on Spatial Information Theory (COSIT 2022)

Abstract
In many everyday situations, two or more people navigate collaboratively but their spatial knowledge does not necessarily overlap. However, most research to date, has investigated social wayfinding under either 1-sided or fully shared spatial information. Here, we present the pilot experiment of a novel, computerised, non-verbal experimental paradigm to study collaborative wayfinding under the face of spatial information uncertainty. Participants (N=32) learned two different neighbourhoods individually, and then navigated together as dyads (D=16), from one neighbourhood to the other. Our pilot results reveal that overall participants share navigational control, but are in control more when the task leads them to a familiar destination. We discuss the effects of spatial ability and motivation to lead, as well as the outlook of the paradigm.
Cite as

Panagiotis Mavros, Saskia Kuliga, Ed Manley, Hilal Rohaidi Fitri, Michael Joos, and Christoph Hölscher. Collaborative Wayfinding Under Distributed Spatial Knowledge (Short Paper). In 15th International Conference on Spatial Information Theory (COSIT 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 240, pp. 25:1-25:10, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)

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@InProceedings{mavros_et_al:LIPIcs.COSIT.2022.25,
  author =	{Mavros, Panagiotis and Kuliga, Saskia and Manley, Ed and Fitri, Hilal Rohaidi and Joos, Michael and H\"{o}lscher, Christoph},
  title =	{{Collaborative Wayfinding Under Distributed Spatial Knowledge}},
  booktitle =	{15th International Conference on Spatial Information Theory (COSIT 2022)},
  pages =	{25:1--25:10},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-257-0},
  ISSN =	{1868-8969},
  year =	{2022},
  volume =	{240},
  editor =	{Ishikawa, Toru and Fabrikant, Sara Irina and Winter, Stephan},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.COSIT.2022.25},
  URN =		{urn:nbn:de:0030-drops-169105},
  doi =		{10.4230/LIPIcs.COSIT.2022.25},
  annote =	{Keywords: navigation, wayfinding, collaboration, dyad, online}
}
Document
Short Paper
DOI: 10.4230/LIPIcs.COSIT.2019.5
Route Choice Through Regions by Pedestrian Agents (Short Paper)

Authors: Gabriele Filomena, Ed Manley, and Judith A. Verstegen

Published in: LIPIcs, Volume 142, 14th International Conference on Spatial Information Theory (COSIT 2019)

Abstract
Simulation models for pedestrian movement are valuable tools to support decision-making processes in urban design. However, existing models of pedestrian behaviour are built on simplistic assumptions regarding people’s representation of the urban space and spatial behaviour. In this work, a route-choice algorithm that takes into account regionalisation processes and the hierarchical organisation of geographical elements is adapted for pedestrian movement and incorporated into an agent-based model. The macro-level patterns emerging from two scenarios, one employing an angular-change minimisation algorithm and the other employing the regional algorithm here proposed, are compared for a case study in London, UK. Our routing algorithm led agents to recur to a higher number of street segments, i.e. routes were more diverse among agents. Though validation has not yet been performed, we deem the patterns resulting from the regional algorithm more plausible.
Cite as

Gabriele Filomena, Ed Manley, and Judith A. Verstegen. Route Choice Through Regions by Pedestrian Agents (Short Paper). In 14th International Conference on Spatial Information Theory (COSIT 2019). Leibniz International Proceedings in Informatics (LIPIcs), Volume 142, pp. 5:1-5:8, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2019)

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@InProceedings{filomena_et_al:LIPIcs.COSIT.2019.5,
  author =	{Filomena, Gabriele and Manley, Ed and Verstegen, Judith A.},
  title =	{{Route Choice Through Regions by Pedestrian Agents}},
  booktitle =	{14th International Conference on Spatial Information Theory (COSIT 2019)},
  pages =	{5:1--5:8},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-115-3},
  ISSN =	{1868-8969},
  year =	{2019},
  volume =	{142},
  editor =	{Timpf, Sabine and Schlieder, Christoph and Kattenbeck, Markus and Ludwig, Bernd and Stewart, Kathleen},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.COSIT.2019.5},
  URN =		{urn:nbn:de:0030-drops-110971},
  doi =		{10.4230/LIPIcs.COSIT.2019.5},
  annote =	{Keywords: pedestrians, agent-based modelling, street network, cognitive regions, cognitive maps, Lynch}
}

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