Summer 2025: Beyond the Wheel: Unlocking the Influence of Emotions on Driving Behavior Using Multimodal Learning

Affiliations: College of Engineering and Computer Science
Team Leader:
Ahmed Abdelrahman
ahmed.abdelrahman@ucf.edu
Civil Engineering PhD
Faculty Mentor:
Mohamed Abdel-Aty, PhD
Team Size:
4
Open Spots: 4
Team Member Qualifications:
Soft skills: Creativity, Critical Thinking, Passion, and Dedication Technical skills: Familiar with using large language models like chatGPT, coding (python), and data labelling (preferred)
Description:
Our emotions play a powerful, often subconscious, role in how we drive. Whether we're feeling stressed, frustrated, overjoyed, or excited, these internal states can influence our decisions behind the wheel. For instance, negative emotions can lead to distractions and aggressive driving, while even intense positive emotions might encourage risky maneuvers or excessive speeding. This project aims to uncover the link between drivers' emotions and their driving behavior on the road using Multimodal learning such as vision large language models (VLLMs). By identifying these emotional states, we can meticulously study how each emotion impacts driving style. This will allow us to determine which emotions pose the greatest risks and contribute most significantly to unsafe driving. Ultimately, the insights gained from this research will be instrumental in transforming driving assistance systems. Imagine a future where your smart car not only navigate the road but also anticipates your needs based on your emotional state, offering more intelligent and personalized support. This deeper understanding of the human element in driving will pave the way for a safer, more intuitive driving experience for everyone.