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Traffic Origins: A Simple Visualization Technique to Support Traffic Incident Analysis
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1007/978-3-642-39062-3_31openalex-snapshot
Unfolding – A Library for Interactive Maps
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Data mining of tree-based models to analyze freeway accident frequency
inferredcites →https://doi.org/10.1109/iri.2009.5211551openalex-snapshot
ICE--visual analytics for transportation incident datasets
inferredcites →https://doi.org/10.1109/iri.2009.5211552openalex-snapshot
Visualizing real-time and archived traffic incident data
inferredcites →https://doi.org/10.1109/iv.2007.147openalex-snapshot
The Effect of Aesthetic on the Usability of Data Visualization
inferredcites →https://doi.org/10.1111/cgf.12132openalex-snapshot
TrajectoryLenses – A Set‐based Filtering and Exploration Technique for Long‐term Trajectory Data
inferredcites →https://doi.org/10.1145/1456650.1456652openalex-snapshot
A review of overview+detail, zooming, and focus+context interfaces
inferredcites →https://doi.org/10.1145/2346496.2346502openalex-snapshot
Mining traffic incidents to forecast impact
inferredcites →https://doi.org/10.3141/2178-04openalex-snapshot
Analysis of Cascading Incident Event Durations on Urban Freeways
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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Towards a Generic Visualization Pipeline for Daily Mobility Data: A Case Study of Household Travel Surveys in France
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Background and Related Work
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How Visual Analytics Unlock Insights into Traffic Incidents in Urban Areas
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Predicting Traffic Flow Based on Average Speed of Neighbouring Road Using Multiple Regression
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TiQ: A Timeline Query Processing System over Road Traffic Data
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A Survey of Traffic Data Visualization
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Prediksi Perambatan Arus Lalu Lintas Berdasarkan Korelasi Tertinggi Antar Jalan
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Analysis of the impact of speed on traffic safety in the city of Banja Luka
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La visualisation d’information pour la prise de décision : identifier les biais et aller au-delà du paradigme de l'analyse visuelle
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