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March 3, 2026
A machine learning-supported path analysis to uncover the behavioral pathways in pedestrian-involved traffic crashes
JK
Jiayi Kong
NX
Ningzhe Xu
JL
Jun Liu
University of Alabama
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Puntos clave
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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A machine learning-supported path analysis to uncover the behavioral pathways in pedestrian-involved traffic crashes | Synapse
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Kong et al. (Thu,) studied this question.
synapsesocial.com/papers/69a75e2ec6e9836116a28943
https://doi.org/https://doi.org/10.1016/j.jsr.2026.01.015