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

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.