Analyzing feature importance for older pedestrian crash severity: A comparative study of DNN models, emphasizing road and vehicle types with SHAP interpretation

Analyzing feature importance for older pedestrian crash severity: A comparative study of DNN models, emphasizing road and vehicle types with SHAP interpretation

Recognizing the importance of road safety modeling, the study explores Deep Neural Networks (DNN) with features like hidden layers, batch normalization, Rectified Linear Unit (ReLU) activation, and dropout to predict crash severity, interpreting decisions using SHapley Additive exPlanations (SHAP) f...

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Bibliographic Details
Main Authors: Rocksana Akter, Susilawati Susilawati, Hamza Zubair, Wai Tong Chor
Format: Article
Language:English
Published: Elsevier 2025-06-01
Series:Multimodal Transportation
Subjects:
Older pedestrian
Intersection
DNN
SHAP
Online Access:http://www.sciencedirect.com/science/article/pii/S2772586325000176
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