UROP Project

Hurricane Impact on Urban Mobility: Congestion Detection and Resilience Analysis

Hurricane Evacuation, Urban Mobility, Big Data Analytics, Transportation Resilience, Traffic congestion and Bottleneck Identification
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Research Mentor: yp25f@fsu.edu Yuyan Pan, she/her
Department, College, Affiliation: Florida State University, FAMU-FSU College of Engineering
Contact Email: yp25f@fsu.edu
Research Assistant Supervisor (if different from mentor): Dr. Dr. Qianwen Guo she/her
Research Assistant Supervisor Email: yp25f@fsu.edu
Faculty Collaborators: Yuyan Pan
Faculty Collaborators Email:
Looking for Research Assistants: Yes
Number of Research Assistants: 6
Relevant Majors: Open to all majors.
Project Location: On FSU Main Campus
Research Assistant Transportation Required: No, the project is remote
Remote or In-person: Fully Remote
Approximate Weekly Hours: 6, Flexible schedule (Combination of business and outside of business. TBD between student and research mentor.)
Roundtable Times and Zoom Link:
Not participating in the roundtable

Project Description

This project investigates how hurricanes affect traffic flow dynamics and urban mobility systems. Using high-resolution real-world data from INRIX (which will be provided by the supervisor), we aim to understand how congestion emerges, spreads, and recovers during extreme weather events. The study will provide valuable insights into transportation resilience and emergency response. Students will gain hands-on experience in data analytics, Python programming, and interpreting mobility patterns under disaster conditions.

Research Tasks: Students will:
Conduct literature reviews on transportation resilience and disaster response.
Process and analyze large-scale INRIX traffic datasets.
Visualize traffic congestion and recovery patterns using Python.
Identify key relationships between storm intensity and mobility impacts.
Contribute to discussions and reports summarizing findings for research dissemination.

Skills that research assistant(s) may need: Required:
Basic knowledge of data analysis and statistics
Familiarity with Microsoft Excel or Google Sheets
Interest in transportation, urban mobility, or environmental issues
Recommended:
Experience with Python (e.g., pandas, matplotlib, or Jupyter Notebook)
Familiarity with GIS tools or data visualization software
Understanding of basic concepts in transportation systems or urban planning

Mentoring Philosophy

My mentoring philosophy is to create a supportive and collaborative environment where students can explore their interests and develop research confidence. I encourage students to think critically, ask questions, and take ownership of their work. I believe in guiding them with patience and constructive feedback, helping them learn from both successes and mistakes. My goal is to help students build strong analytical and communication skills that will benefit their future academic and professional paths.

Additional Information


Link to Publications

https://yuyananniepan.github.io/