This system is designed to enhance personal safety in vehicles, particularly focusing on features like airbags. However, it often overlooks proactive measures to prevent accidents from occurring in the first place. The driver-based eye-tracking fatigue alarm system, implemented using FPGA technology, offers a more advanced solution compared to traditional DSP-based systems. It provides higher integration, faster processing speed, enhanced functionality, and easier internal design modifications, making it a superior choice for real-time monitoring of driver alertness.
Real-time video tracking has become an essential technology with widespread applications across various fields, including military operations, aviation, security systems, and video conferencing. In critical scenarios, such as traffic monitoring, it plays a vital role in ensuring safety. By applying this technology to detect driver fatigue, the system can significantly reduce the risk of accidents caused by drowsiness or inattention. As the saying goes, "Traffic accidents are fiercer than tigers." With the growing number of private vehicles globally, the frequency of traffic accidents has also risen, making vehicle safety a major societal concern.
Studies show that fatigue-related accidents account for a significant percentage of all traffic incidents. For example, in some regions, up to 20% of total accidents and over 40% of severe ones are attributed to driver fatigue. In Japan, fatigue-related accidents make up about 1% to 1.5%, while in France, they account for 14.9% of personal injury accidents and 20.6% of fatal ones. According to the U.S. National Highway Traffic Safety Administration, around 100,000 accidents occur annually due to fatigue driving. This clearly highlights the urgent need for effective solutions to combat driver fatigue.
Current vehicle safety systems primarily focus on protecting occupants during accidents, rather than preventing them. The driver eye-tracking fatigue alarm system addresses this gap by continuously monitoring the driver's eye activity. Traditional systems rely on DSP for image processing, which involves complex wiring and is sensitive to design changes. These limitations hinder performance and usability. To overcome these challenges, a more advanced system with high integration, powerful functions, and flexible updates is necessary.
The system uses real-time video tracking to capture the driver’s face, identify the eyes, and analyze their closure duration to determine if an alarm should be triggered. It consists of four main components: a camera and video decoding module, a display, an LCD screen, and a development board. The system is built on an FPGA platform, incorporating Xilinx’s MicroBlaze soft-core processor. Image processing algorithms and dynamic object recognition are integrated, supported by necessary peripheral circuits. Most of the processing tasks are handled by hardware, ensuring fast and efficient operation.
This system is ideal for long-haul drivers, car manufacturers, and traffic safety authorities who seek to improve road safety through early detection of driver fatigue. It not only enhances driver awareness but also provides valuable data for accident analysis and prevention strategies.
The system is divided into four key modules: image acquisition, feature extraction, data storage, and human-computer interaction. The image acquisition module captures real-time video from a camera, which is then processed by a video decoding chip to convert analog signals into digital format for further analysis. The image processing module extracts eye features and determines if the driver is fatigued. The data storage module records video when the eye closure time exceeds a set threshold, allowing for later review in case of an accident. Finally, the human-computer interaction interface provides a visual display and touch controls, enabling users to manage and view stored data efficiently.
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