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April 3, 2026SHILAP Revista de lepidopterologíaOpen Access

Identifying and Analysing Traffic Accident Hotspots – A Holistic Approach Combining Spatial and Data Mining Techniques

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Authors

OCOmer Faruk CansizMCMehmet Fatih CANKÜKevser ÜNSALAN

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Overview

Analysis identifies accident-prone areas by integrating spatial and data mining methods, suggesting improvements for traffic safety.

Key Points

  • This research aims to identify and analyze critical traffic accident hotspots using a comprehensive analytical approach.
  • Integrated hierarchical clustering, variogram modelling, and association rule mining.
  • Identified key factors and spatial dependencies affecting traffic accidents.
  • Analyzed multiple accident-prone zones considering various environmental and geometric factors.
  • Identified four major accident hotspots: dense residential areas, city center roads, multi-curved roads, and dispersed regions.
  • Found significant spatial dependencies indicating concentration of accidents in specific areas.
  • Highlighted critical factors like dry road surfaces, fair weather, and complex road geometry as contributors to accident frequency.

Cite This Study

Cansiz et al. (2026) studied this question.

synapsesocial.com/papers/69cf58285a333a82146095ebhttps://doi.org/10.7307/ptt.v38i3.1032
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