UROP Research Mentor Project Submission Portal: Submission #1402
Submission information
Submission Number: 1402
Submission ID: 22375
Submission UUID: 2e19661a-a7fc-4149-b996-08627967ee75
Submission URI: /urop-research-mentor-project-submission-portal
Created: Tue, 06/30/2026 - 03:12 PM
Completed: Tue, 06/30/2026 - 03:12 PM
Changed: Tue, 06/30/2026 - 03:12 PM
Remote IP address: 146.201.222.254
Submitted by: Anonymous
Language: English
Is draft: No
Submitted to: UROP Research Mentor Project Submission Portal
| Primary Research Mentor Name | George Amu |
|---|---|
| Research Mentor Preferred Pronouns | |
| When potential research assistants are reaching out via email, what is your preferred honorific? | |
| Contact Email (FSU Email if affiliated) | gka24a@fsu.edu |
| Position Title | Graduate Student |
| Are you and FSU employee? | Yes |
| Will you be employed at FSU for the entirety of Fall and Spring semesters? | Yes |
| Faculty Advisor Name | Dr. Arda Vanli |
| Faculty Advisor's FSU Email | oavanli@eng.famu.fsu.edu |
| FSU College (if applicable) | FAMU-FSU College of Engineering |
| FSU Department or Non-FSU Organization Affiliation | Industrial and Manufacturing Engineering |
| Headshot (optional) | |
| Research Assistant Supervisor (if different from above) | |
| Research Assistant Supervisor Preferred Pronouns | |
| Research Assistant Supervisor Preferred Honorific? | |
| Contact Email (FSU Email if affiliated) | |
| Name of Other Faculty/Collaborator(s) (if applicable) | |
| Other Faculty/Collaborator(s) Preferred Pronouns | |
| Other Faculty/Collaborator(s) Preferred Honorific? | |
| Contact Email (FSU Email if affiliated) | |
| Title of the Project | Explainable Artificial Intelligence for Traffic Volume Prediction |
| Project Keywords | Artificial Intelligence, Transportation, Machine Learning, Traffic Modelling |
| Are you currently looking for research assistants? | Yes |
| Number of Research Assistants Needed | 1 |
| Relevant Research Assistant Major(s) | Open to all majors |
| Project Location: | On FSU Main Campus |
| If the project location is off campus, does the research assistant(s) need to provide their own transportation? | |
| Please select the choice that most accurately describes your expectations for the research assistant(s): | In-person |
| Approximately how many hours a week would the research assistant(s) need to work? | 10 |
| Roughly what time frame do you expect research assistant(s) to work? | Flexible schedule (Combination of business and outside of business. TBD between student and research mentor.) |
| Overall Research Project Description | Background State departments and agencies monitor traffic volumes to manage and maintain efficient highway systems. Traffic data collected are used for various applications including risk assessments to identify high crash locations as well as resource allocation, maintenance planning, and policy formulation. Research Problem Traffic data collection requires significant time and effort. Current manual methods used for data collection are insufficient and do not cover all road segments. Currently, in Florida, the department of transport uses manual ground-based methods to count traffic on some major roadways. There is still a substantial gap in data collection in terms of coverage. Artificial intelligence (AI) and statistical computing offer significant potential in providing robust and cost-effective traffic volume data for these unmonitored road segments. Research Objectives This research will focus on: 1. Reviewing existing literature and identifying best practices for traffic volume prediction. 2. Building predictive artificial intelligence models for traffic volume prediction on unmonitored roadways in Florida. Methodology The project will focus on traffic volume prediction for selected districts in Florida. The proposed methodology will include traffic demand modelling and machine learning. The designed model will be evaluated based on defined metrices to ascertain its robustness. Expected Outcomes This research is expected to result in defined tested strategies and recommendations for predicting traffic volumes using artificial intelligence. |
| Research Tasks | 1. Reviewing existing literature and identifying best practices for traffic volume prediction. 2. Building predictive artificial intelligence models for traffic volume prediction on unmonitored roadways in Florida. Methodology |
| Skills that research assistant(s) may need: | data analytics - recommended |
| Mentoring Philosophy | Developing a relationship founded on mutual respect Giving mentees’ ownership of their work and promoting accountability Sharing your own experience. Creating a safe environment in which mentees feel that is acceptable to fail and learn from their mistakes |
| Please provide a link to your publications, a video clip, or a website for your research project (if applicable): | |
| Please add any additional information here (if applicable): | |
| Are you interested in participating in the UROP Research Mentor Roundtable? | Yes |
| Roundtable times and Zoom links | |
| Mentor Handbook, FAQs, and Communication | Yes |
| UROP Performance Evaluation | Yes |
| Materials Grant | Yes |
| UROP Poster Presentation | Yes |
| Faculty Advisor Confirmation | Yes |
| Are you interested in attending in a UROP Research Mentor Workshop Series? | |
| Year | 2026 |