From Sensing to Insight: Collection and Interpretation of Human Factors Data Towards Human-Centric Underground Space

The future of underground space should not be an extension of cold concrete, but a responsive, intelligent, and human-centered organ of the city. While engineering and physical infrastructure have been the traditional focus, the true key to creating safe, efficient, comfortable, and vibrant underground environments lies in a deep understanding of their users: people.

This special session aims to bridge this critical gap. We seek to bring together scholars and practitioners from civil engineering, urban planning, architecture, psychology, ergonomics, and data science. The goal is to explore cutting-edge methods for the precise collection of human factors data and develop interdisciplinary approaches for its meaningful interpretation. We hope to collectively shift the paradigm of underground space design and management from being experience-driven to being driven by data and human-centric insight.

We invite abstract submissions on topics including, but not limited to:

(1)     Advanced Sensing & Data Collection:

• Multi-modal data fusion (e.g., computer vision for trajectory analysis, Wi-Fi/Bluetooth for crowd monitoring). 
• Capturing physiological and psychological signals (e.g., using wearables for EEG, heart rate; innovative surveys and interviews).
• Emerging paradigms like Virtual/Augmented Reality for simulation and IoT-based, non-intrusive sensing.

(2)     Data Interpretation & Insight Generation:

• Uncovering behavioral patterns and spatial semantics through data mining.
• Affective computing and comfort models linking environmental parameters to subjective well-being.
• Human performance and safety assessment for scenarios like emergency evacuation.

(3)     Human-Centric Design & Management:

• Evidence-based design strategies for lighting, wayfinding, and spatial layout.
• Promoting health, well-being, and mitigating psychological stress in underground environments.
• Smart operation and personalized services using real-time human factors data.