Abstract
Driving is considered a complex task that requires continuous focus and attention from the driver. Driving performance can also be impacted by changes in the driver’s stress level. However, limited research explores methods to address this challenge. With the current advances in Large Language Models (LLMs) and their ability to engage in human-like interaction, this study investigates the potential of using ChatGPT, designed to speak Egyptian Arabic, in re-engaging driver attention under different driving scenarios for low-stress and high-stress conditions within a virtual reality (VR) environment driving simulator. Drivers were asked to follow a leading car into two scenarios with and without ChatGPT while physiological data (Electroencephalography (EEG), eye-tracking, heart rate, galvanic skin response (GSR)) and driving performance parameters (reaction time, distance to lead vehicle, and number of collisions) were recorded during the sessions. The results indicate that open-ended voice conversation ChatGPT can help improve driver performance compared to not using ChatGPT. In the high-stress scenario, the EEG theta band increased significantly, which is associated with cognitive control, while the Perceived Stress Scale reduced by 16.64% in addition to an improvement of 5.78% in the driver’s reaction time. In the low-stress scenario, visual attention was improved as indicated by a decrease in parietal-occipital alpha band, and a significant increase in pupil diameter, and the performance improved by 5.32%. This work contributes to the integration of EEG-VR-ChatGPT, paving the way for adaptive Artificial Intelligence (AI) driver assistance in future research.
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School
School of Sciences and Engineering
Department
Robotics, Control & Smart Systems Program
Degree Name
MS in Robotics, Control and Smart Systems
Graduation Date
Summer 8-19-2025
Submission Date
9-16-2025
First Advisor
Khalil ElKhodary
Second Advisor
Seif Eldawlatly
Committee Member 1
Amr El Mougy
Committee Member 2
Mervat Abu-Elkheir
Committee Member 3
Mostafa Youssef
Extent
135 p.
Document Type
Master's Thesis
Institutional Review Board (IRB) Approval
Approval has been obtained for this item
Disclosure of AI Use
Thesis text drafting
Recommended Citation
APA Citation
Elfiqi, A. Z.
(2025).Re-engaging Driver Attention using ChatGPT: A Multimodal Study on Stress Impact and Driving Performance [Master's Thesis, the American University in Cairo]. AUC Knowledge Fountain.
https://fount.aucegypt.edu/etds/2598
MLA Citation
Elfiqi, Alaa Zaki. Re-engaging Driver Attention using ChatGPT: A Multimodal Study on Stress Impact and Driving Performance. 2025. American University in Cairo, Master's Thesis. AUC Knowledge Fountain.
https://fount.aucegypt.edu/etds/2598
Included in
Cognitive Science Commons, Human Factors Psychology Commons, Mechanical Engineering Commons, Quantitative Psychology Commons, Robotics Commons
