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January 29, 2026Journal of Safety Research

A machine learning-supported path analysis to uncover the behavioral pathways in pedestrian-involved traffic crashes

Jiayi Kong Ningzhe Xu Jun Liu Steven Jones

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Key Points

The analysis reveals key behavioral pathways involved in pedestrian-involved traffic crashes, highlighting risk factors.
Findings indicate that 20% of crashes are related to distracted behaviors and unsafe road crossings.
Assessment using machine learning techniques enhances path analysis, providing a detailed view of contributing factors.
Supports the need for targeted interventions to improve pedestrian safety, suggesting further studies are necessary.

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Implication

Observational analysis uncovers behavioral pathways in traffic crashes involving pedestrians, suggesting improved safety measures.

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Cite This Study

Kong et al. (2026) studied this question.

synapsesocial.com/papers/69a75e2ec6e9836116a28943 https://doi.org/10.1016/j.jsr.2026.01.015

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