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Predicting effects of built environment on fatal pedestrian accidents at location-specific level: Application of XGBoost and SHAP

  • Published:2022-03 Issue: Volume:166 Page:106545
  • ISSN:0001-4575
  • Container-title:Accident Analysis & Prevention
  • language:en
  • Short-container-title:Accident Analysis & Prevention

Author:

Chang Iljoon,Park Hoontae,Hong Eungi,Lee Jaeduk,Kwon Namju

Funder

Ministry of the Interior and Safety

Publisher

Elsevier BV

Subject

Public Health, Environmental and Occupational Health,Safety, Risk, Reliability and Quality,Human Factors and Ergonomics

Reference44 articles.

1. Effects of the built environment on automobile-involved pedestrian crash frequency and risk;Chen;J. Transp. Health,2016

2. August). Xgboost: A scalable tree boosting system;Chen,2016

3. An examination of the environmental attributes associated with pedestrian–vehicular crashes near public schools;Clifton;Accid. Anal. Prev.,2007

4. Fatal pedestrian crashes at intersections: Trend mining using association rules;Das;Accid. Anal. Prev.,2021

5. Descamps, B. (2017). Regression prediction intervals with XGBoos. Towards Data Science. Apr 25, 2017.
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