Outcome: Developing an applied analytics framework to help transportation program stakeholders understand demand, capacity, and system constraints, supporting more informed planning, benchmarking, and future investment decisions.

Decision Context

• National transportation systems vary widely in scale, usage, and operational constraints
• Existing summaries obscured capacity stress, underutilization, and structural differences
• Planners needed interpretable analytics to guide comparison, prioritization, and future data collection

What I’m Building

• Demand & capacity characterization: Descriptive and predictive analysis of utilization and asset capacity
• Operational segmentation: Clustering systems into comparable archetypes for benchmarking
• Optimization assessment: Identifying mismatches between observed demand and available capacity
• Resilience indicators: Constructing interpretable metrics capturing redundancy, accessibility, and connectivity
• Data readiness evaluation: Assessing survey structure and consistency to inform future analytics and design

Impact (In Progress)

• Provides a clearer picture of where systems experience capacity stress or underutilization
• Enables apples-to-apples comparison across heterogeneous transportation systems
• Establishes a foundation for scalable analytics and improved data collection strategies

This work emphasizes interpretability and decision relevance over model complexity. Methods and outputs are refined iteratively based on stakeholder feedback and practical utility.