Vehicle Safety Automation Using Hands off Detection

In the age of intelligent transportation systems, ensuring driver engagement during semi-autonomous driving is critical for road safety. This project presents a vehicle safety automation system based on hands-off detection (HoD) technology, designed to monitor driver interaction with the steering wheel and initiate safety protocols in case of disengagement. The proposed system integrates capacitive touch sensors and microcontroller-based logic to detect the presence or absence of the driver’s hands in real time. Upon detecting prolonged hands-off conditions, the system generates visual and audio alerts and can trigger vehicle deceleration or stop mechanisms to prevent accidents. The implementation emphasizes reliability, low cost, and ease of integration with existing automotive systems. The study demonstrates that hands-off detection can significantly reduce the risk of driver inattention and improve overall vehicle safety, especially in Level 2 and Level 3 autonomous systems.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-04-28
DOI
https://doi.org/10.5281/zenodo.15295772
Primary Topic
IoT and GPS-based Vehicle Safety Systems
Type
article
Field-Weighted Citation Impact
0.00
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article

Vehicle Safety Automation Using Hands off Detection

Zenodo (CERN European Organization for Nuclear Research)
IoT and GPS-based Vehicle Safety Systems
article

Vehicle Safety Automation Using Hands off Detection

article en

Abstract

In the age of intelligent transportation systems, ensuring driver engagement during semi-autonomous driving is critical for road safety. This project presents a vehicle safety automation system based on hands-off detection (HoD) technology, designed to monitor driver interaction with the steering wheel and initiate safety protocols in case of disengagement. The proposed system integrates capacitive touch sensors and microcontroller-based logic to detect the presence or absence of the driver’s hands in real time. Upon detecting prolonged hands-off conditions, the system generates visual and audio alerts and can trigger vehicle deceleration or stop mechanisms to prevent accidents. The implementation emphasizes reliability, low cost, and ease of integration with existing automotive systems. The study demonstrates that hands-off detection can significantly reduce the risk of driver inattention and improve overall vehicle safety, especially in Level 2 and Level 3 autonomous systems.

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 54%
IoT and GPS-based Vehicle Safety Systems
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