Multi-modal Safe Driving System for New Energy Vehicles based on Microcontrollers

Shengbo Zhang; Jingwen Song; Yuhan Chen; Wenzhe Ni; Chen Hu; Boyu Shan; Chunrong Jia

doi:10.6919/ICJE.202511_11(11).0022

Authors

Shengbo Zhang
Jingwen Song
Yuhan Chen
Wenzhe Ni
Chen Hu
Boyu Shan
Chunrong Jia

DOI:

https://doi.org/10.6919/ICJE.202511_11(11).0022

Keywords:

New Energy Vehicles; Multimodal Safety Driving System; A-pillar Blind Spot Monitoring; Fatigue Driving Detection; Visual Algorithms.

Abstract

This paper presents a multimodal intelligent safety driving system for new energy vehicles, developed based on STM32 microcontrollers and multimodal visual algorithms. The system integrates real-time dynamic monitoring of the A-pillar blind spot, fatigue driving detection, and battery spontaneous combustion detection. Through optimized distortion correction algorithms, dynamic display solutions, fatigue detection models, and the construction of spontaneous combustion sensors with information transmission systems, it achieves multidimensional safety monitoring. The system innovatively employs object detection and Zhang Dingyou calibration for dynamic A-pillar blind spot monitoring, combines deep learning for fatigue driving detection, and implements battery spontaneous combustion risk warnings through dual data module feedback. In practical application, it reduces the risk of accidents caused by blind spots and fatigue driving, decreases the probability of battery spontaneous combustion, and provides technical support for intelligent cockpits, assisted driving, and new energy vehicle safety, demonstrating broad potential for in-vehicle applications.

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