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Documents authored by Van de Weghe, Nico

Document
Short Paper
DOI: 10.4230/LIPIcs.COSIT.2026.16
From Trajectories to Relations: Interpreting Overtake Manoeuvres with Large Language Models and Qualitative Spatial Representations (Short Paper)

Authors: Jana Verdoodt, Changbo Zhang, Lars De Sloover, Haosheng Huang, and Nico Van de Weghe

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

Abstract
This paper explores whether qualitative spatial encodings make overtake manoeuvres more interpretable to a large language model (LLM). Using simulated traffic trajectories from a microscopic road-network model, we encode the same overtake event at three levels of complexity through Point-Descriptor-Precedence (PDP) inequality matrices. An LLM is then used in a staged, zero-shot API workflow in which longitudinal and lateral descriptor encodings derived from these matrices are interpreted separately and then merged into a final manoeuvre interpretation. Outputs are assessed through expert-based qualitative evaluation focusing on relational correctness, spatial precision, completeness, and interpretive adequacy. For the selected case, the results suggest that the model can produce meaningful natural-language interpretations at all three levels, but that these change as complexity increases. The 2-point representation yields the clearest focal manoeuvre, the 5-point representation offers the best balance between contextual richness and interpretability, and the 10-point representation produces the most nuanced structural reading, although in a less concise form. The paper should be read as an exploratory study of representation effects rather than as a benchmark of LLM performance.
Cite as

Jana Verdoodt, Changbo Zhang, Lars De Sloover, Haosheng Huang, and Nico Van de Weghe. From Trajectories to Relations: Interpreting Overtake Manoeuvres with Large Language Models and Qualitative Spatial Representations (Short Paper). In 17th International Conference on Spatial Information Theory (COSIT 2026). Leibniz International Proceedings in Informatics (LIPIcs), Volume 393, pp. 16:1-16:8, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026)

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@InProceedings{verdoodt_et_al:LIPIcs.COSIT.2026.16,
  author =	{Verdoodt, Jana and Zhang, Changbo and De Sloover, Lars and Huang, Haosheng and Van de Weghe, Nico},
  title =	{{From Trajectories to Relations: Interpreting Overtake Manoeuvres with Large Language Models and Qualitative Spatial Representations}},
  booktitle =	{17th International Conference on Spatial Information Theory (COSIT 2026)},
  pages =	{16:1--16:8},
  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.2026.16},
  URN =		{urn:nbn:de:0030-drops-275607},
  doi =		{10.4230/LIPIcs.COSIT.2026.16},
  annote =	{Keywords: micro-scale traffic analysis, overtaking behaviour, symbolic movement encoding, spatial reasoning, expert evaluation}
}
Document
Short Paper
DOI: 10.4230/LIPIcs.COSIT.2026.32
The Same Street, Different Safety Judgments: Evaluative Framing Effects in Daytime and Nighttime Street View Imagery (Short Paper)

Authors: Tong Qin, Nico Van de Weghe, Wim Fias, and Haosheng Huang

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

Abstract
Street View Imagery (SVI) is widely used to study perceived street safety, yet most studies treat safety as a general impression of urban scenes and rely mainly on daytime imagery. It remains unclear whether safety judgments differ across evaluative framings, defined here as the safety question asked of participants, and whether this difference varies between daytime and nighttime scenes. We analyzed 7,320 safety ratings from 61 participants for 120 SVIs, including 60 daytime and 60 nighttime images. Participants judged scenes under two evaluative framings: crime-related safety and traffic-related safety. Using cumulative link mixed models with random intercepts for participants and stimuli, we found that the stimulus set received higher safety ratings in the crime-related framing than in the traffic-related framing. This evaluative-framing effect was stronger for daytime than for nighttime scenes. These findings indicate that perceived street safety in SVI is not a fixed property of image content, but also depends on the safety question asked during judgment.
Cite as

Tong Qin, Nico Van de Weghe, Wim Fias, and Haosheng Huang. The Same Street, Different Safety Judgments: Evaluative Framing Effects in Daytime and Nighttime Street View Imagery (Short Paper). In 17th International Conference on Spatial Information Theory (COSIT 2026). Leibniz International Proceedings in Informatics (LIPIcs), Volume 393, pp. 32:1-32:7, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026)

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@InProceedings{qin_et_al:LIPIcs.COSIT.2026.32,
  author =	{Qin, Tong and Van de Weghe, Nico and Fias, Wim and Huang, Haosheng},
  title =	{{The Same Street, Different Safety Judgments: Evaluative Framing Effects in Daytime and Nighttime Street View Imagery}},
  booktitle =	{17th International Conference on Spatial Information Theory (COSIT 2026)},
  pages =	{32:1--32:7},
  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.2026.32},
  URN =		{urn:nbn:de:0030-drops-275763},
  doi =		{10.4230/LIPIcs.COSIT.2026.32},
  annote =	{Keywords: street view imagery, spatial cognition, safety perception, evaluative framing, geographic information science}
}
Document
Short Paper
DOI: 10.4230/LIPIcs.COSIT.2022.16
Smart Crowd Management: The Data, the Users and the Solution (Short Paper)

Authors: Laure De Cock, Steven Verstockt, Christophe Vandeviver, and Nico Van de Weghe

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

Abstract
This research project is situated in the domain of smart crowd management, a domain that is gaining importance because of the challenges that arise from urbanization, but also the opportunities that come with smart cities. While our cities become more crowded every day, they also become smarter, for example by employing pedestrian tracking sensors. However, the datasets that are generated by these sensors do not allow smart crowd management yet, because they are sparse and not linked to the perception of the crowd. This research will tackle these issues in three steps. First, pedestrian counts will be estimated on streets that have no tracking data by use of deep learning and space syntax data. Next, the perception of crowdedness within the crowd will be linked to the objective pedestrian counts by conducting two user studies, and finally, the resulting subjective pedestrian counts will be used as weights for a routing algorithm. The last step has already been developed as a proof of concept. The routing algorithm, that uses partly simulated data and partly real-time tracking data, has been embedded in a webtool to show stakeholders the potential and goal of this innovative project.
Cite as

Laure De Cock, Steven Verstockt, Christophe Vandeviver, and Nico Van de Weghe. Smart Crowd Management: The Data, the Users and the Solution (Short Paper). In 15th International Conference on Spatial Information Theory (COSIT 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 240, pp. 16:1-16:7, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)

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@InProceedings{decock_et_al:LIPIcs.COSIT.2022.16,
  author =	{De Cock, Laure and Verstockt, Steven and Vandeviver, Christophe and Van de Weghe, Nico},
  title =	{{Smart Crowd Management: The Data, the Users and the Solution}},
  booktitle =	{15th International Conference on Spatial Information Theory (COSIT 2022)},
  pages =	{16:1--16:7},
  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.2022.16},
  URN =		{urn:nbn:de:0030-drops-169013},
  doi =		{10.4230/LIPIcs.COSIT.2022.16},
  annote =	{Keywords: crowd tracking, crowd modeling, space syntax, deep learning, perception, routing}
}
Document
Short Paper
DOI: 10.4230/LIPIcs.GISCIENCE.2018.55
Novel Models for Multi-Scale Spatial and Temporal Analyses (Short Paper)

Authors: Yi Qiang, Barbara P. Buttenfield, Nina Lam, and Nico Van de Weghe

Published in: LIPIcs, Volume 114, 10th International Conference on Geographic Information Science (GIScience 2018)

Abstract
Multi-scale analysis for spatio-temporal data forms a fundamental challenge for many analytic systems. In geographic information systems, analysis and modeling at pre-defined spatial and temporal scales may miss critical relationships in other scales. Previous studies have investigated the uses of the triangle model as a multi-scale framework in analyzing temporal data. This article demonstrates the utilities of the triangle model and pyramid model for multi-scale spatial analysis through real-world analytical tasks and discusses the potential of developing a unified modeling framework that integrates the two models.
Cite as

Yi Qiang, Barbara P. Buttenfield, Nina Lam, and Nico Van de Weghe. Novel Models for Multi-Scale Spatial and Temporal Analyses (Short Paper). In 10th International Conference on Geographic Information Science (GIScience 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 114, pp. 55:1-55:7, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)

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@InProceedings{qiang_et_al:LIPIcs.GISCIENCE.2018.55,
  author =	{Qiang, Yi and Buttenfield, Barbara P. and Lam, Nina and Van de Weghe, Nico},
  title =	{{Novel Models for Multi-Scale Spatial and Temporal Analyses}},
  booktitle =	{10th International Conference on Geographic Information Science (GIScience 2018)},
  pages =	{55:1--55:7},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-083-5},
  ISSN =	{1868-8969},
  year =	{2018},
  volume =	{114},
  editor =	{Winter, Stephan and Griffin, Amy and Sester, Monika},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.GISCIENCE.2018.55},
  URN =		{urn:nbn:de:0030-drops-93832},
  doi =		{10.4230/LIPIcs.GISCIENCE.2018.55},
  annote =	{Keywords: Triangle Model, Pyramid Model, multi-scale spatial and temporal analysis, GIS}
}

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