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This graph maps the connections between all the collaborators of {}'s publications listed on this page.
Each link represents a collaboration on the same publication. The thickness of the link represents the number of collaborations.
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A word cloud is a visual representation of the most frequently used words in a text or a set of texts. The words appear in different sizes, with the size of each word being proportional to its frequency of occurrence in the text. The more frequently a word is used, the larger it appears in the word cloud. This technique allows for a quick visualization of the most important themes and concepts in a text.
In the context of this page, the word cloud was generated from the publications of the author {}. The words in this cloud come from the titles, abstracts, and keywords of the author's articles and research papers. By analyzing this word cloud, you can get an overview of the most recurring and significant topics and research areas in the author's work.
The word cloud is a useful tool for identifying trends and main themes in a corpus of texts, thus facilitating the understanding and analysis of content in a visual and intuitive way.
Abolfazli, M., Trépanier, M., & Labbe, A. (2024). Understanding incident effects on subway operations : clustering analysis of severity patterns. Transportation Research Record: Journal of the Transportation Research Board, 13 pages. External link
Navarro, B., Miranda-Moreno, L., Saunier, N., Labbe, A., & Fu, T. (2022). Do stop-signs improve the safety for all road users? A before-after study of stop-controlled intersections using video-based trajectories and surrogate measures of safety. Accident Analysis and Prevention, 167, 106563 (16 pages). External link
Stipancic, J., Saunier, N., Navidi, N., Racine, E. B., Miranda-Moreno, L., & Labbe, A. (2023, July). Evaluating Map Matching Algorithms for Smartphone GNSS Data: Matching Vehicle Trajectories to an Urban Road Network [Paper]. World Conference on Transport Research (WCTR 2023), Montréal, Québec. Published in Transportation research procedia, 82. External link
Stipancic, J., St-Aubin, P. G., Ledezma-Navarro, B., Labbe, A., Saunier, N., & Miranda-Moreno, L. (2021). Evaluating safety-influencing factors at stop-controlled intersections using automated video analysis. Journal of Safety Research, 77, 311-323. External link
Stipancic, J., Racine, É. B., Labbe, A., Saunier, N., & Miranda-Moreno, L. (2021). Massive GNSS data for road safety analysis: Comparing crash models for several Canadian cities and data sources. Accident Analysis and Prevention, 159, 106232 (10 pages). External link
Stipancic, J., Miranda-Moreno, L., Strauss, J., & Labbe, A. (2020). Pedestrian safety at signalized intersections: Modelling spatial effects of exposure, geometry and signalization on a large urban network. Accident Analysis and Prevention, 134, 11 pages. External link
Stipancic, J., Miranda-Moreno, L., Labbe, A., & Saunier, N. (2019). Measuring and visualizing space–time congestion patterns in an urban road network using large-scale smartphone-collected GPS data. Transportation Letters, 11(7), 391-401. Available
Stipancic, J., Miranda-Moreno, L., Saunier, N., & Labbe, A. (2019). Network screening for large urban road networks: Using GPS data and surrogate measures to model crash frequency and severity. Accident Analysis and Prevention, 125, 290-301. External link
Stipancic, J., Miranda-Moreno, L. F., Saunier, N., & Labbe, A. (2018, January). Network screening for large urban road networks: Using GPS data and surrogate measures to model crash frequency and severity [Paper]. Transportation Research Board 97th Annual Meeting, Washington, D.C.. Unavailable
St-Aubin, P., Ledezma-Navarro, B., Labbe, A., Fu, T., Saunier, N., & Miranda-Moreno, L. F. (2018, January). Speed at partially and fully stop-controlled intersections [Paper]. Transportation Research Board 97th Annual Meeting, Washington, D.C.. External link
Stipancic, J., Miranda-Moreno, L., Saunier, N., & Labbe, A. (2018). Surrogate safety and network screening: Modelling crash frequency using GPS travel data and latent Gaussian Spatial Models. Accident Analysis and Prevention, 120, 174-187. External link
Stipancic, J., Miranda-Moreno, L., Saunier, N., & Labbe, A. (2017, September). Surrogate safety and network screening : modelling crash frequency using GPS data latent gaussian models [Paper]. Conference of the Transportation Association of Canada, St. John's, NL (19 pages). External link