AI Driven Biointegrated Control Systems for Enhancing Driver Safety and Personalized Vehicle Adaptation

Raju Bhadrabasolara Revappa, Seema Vasudevan, Jaideep Rukmangadan

2025

Abstract

Rapid development of AI has brought revolutionary change in the auto industry, creating a new generation of driver-vehicle interactions. This article proposes the AI-Driven Biointegrated Control Systems (AI-BICS), a next generation platform to optimize vehicle-to-user interaction based on real-time physiological and cognitive information from drivers. AI-BICS is the fusion of cutting-edge bio-sensing devices and the latest deep learning technologies for increased safety, ease of use and customization of our cars. The technology entails embedding bio-sensors in the car ecosystem that monitor physiological parameters like heart rate, skin conductance and muscle activity. These signals go through a hybrid deep learning system, composed of convolutional neural networks (CNNs) for image inputs and recurrent neural networks (RNNs) for time series. Additionally, Transformer architectures are used for multi-modal data fusion for a complete view of the driver’s state. It adjusts vehicle settings, like acceleration and steering response, on the fly and provides live feedback to help you stay in control and comfortable. The system proposes a number of important contributions to the discipline. It goes beyond the traditional driver monitoring system by integrating real-time emotion detection, stress evaluation, and fatigue detection to give users more situational awareness. AI-BICS also facilitates adaptive control, seamlessly morphing from manual to autonomous driving and provides tailored driving experience through learning and responding to the user’s preferences. The intended effects of this research are the enormous increases in road safety and driver wellbeing. In combatting important problems including impaired driving and brain overload, the system is set to reshape the frontiers of end-user car technology. Further, it can be used for fleet management and insurance schemes to offer a complete set of safer and smarter transportation solutions.

Paper Citation

in Harvard Style

Revappa R., Vasudevan S. and Rukmangadan J. (2025). AI Driven Biointegrated Control Systems for Enhancing Driver Safety and Personalized Vehicle Adaptation. In Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - ICRDICCT`25; ISBN 978-989-758-777-1, SciTePress, pages 669-675. DOI: 10.5220/0013888300004919

in Bibtex Style

@conference{icrdicct`2525,
author={Raju Revappa and Seema Vasudevan and Jaideep Rukmangadan},
title={AI Driven Biointegrated Control Systems for Enhancing Driver Safety and Personalized Vehicle Adaptation},
booktitle={Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - ICRDICCT`25},
year={2025},
pages={669-675},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013888300004919},
isbn={978-989-758-777-1},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - ICRDICCT`25
TI - AI Driven Biointegrated Control Systems for Enhancing Driver Safety and Personalized Vehicle Adaptation
SN - 978-989-758-777-1
AU - Revappa R.
AU - Vasudevan S.
AU - Rukmangadan J.
PY - 2025
SP - 669
EP - 675
DO - 10.5220/0013888300004919
PB - SciTePress