This system is designed to enhance personal safety by focusing on the prevention of accidents, rather than just protecting passengers after an incident, as many current vehicle safety systems do. Traditional systems, such as airbags, are reactive rather than proactive. The driver-based eye-tracking fatigue alarm system based on FPGA offers a more advanced solution, with benefits like higher integration, faster processing speed, enhanced functionality, and easier internal design modifications compared to traditional DSP-based implementations.
Real-time video tracking has become a vital technology in various fields, including military operations, aviation, security, and video conferencing. In particular, it's increasingly being applied in critical areas like traffic safety. This system specifically uses real-time video tracking to monitor drivers for signs of fatigue, aiming to prevent traffic accidents before they occur. As the saying goes, "Traffic accidents are fiercer than tigers." With the rising number of private vehicles globally, road accidents have also increased significantly. Fatigue driving is a major cause, contributing to about 20% of all traffic accidents and over 40% of serious ones. In Japan, fatigue-related accidents account for 1-1.5%, while in France, 14.9% of personal injury accidents and 20.6% of fatal accidents are linked to drowsiness. According to the National Highway Traffic Safety Administration, around 100,000 accidents annually are caused by fatigue. Clearly, fatigue has become one of the biggest threats to safe driving.
Current vehicle safety systems focus on post-accident protection, but neglect proactive measures to avoid accidents altogether. The driver’s eye-tracking fatigue alarm system addresses this issue effectively. Previously, video tracking was implemented using DSPs, which had high wiring complexity and were sensitive to external interference, making them less reliable. Additionally, their design and debugging were challenging, especially in limited internal spaces, where changes to parameters were often required. This made them difficult to adapt in real-world applications. To overcome these limitations, there is a growing need for a more powerful, integrated, and flexible system that can be easily updated and maintained.
The driver eye-tracking fatigue alarm system works by capturing real-time video of the driver's face, identifying the eyes through facial image tracking and eyeball recognition, and analyzing the duration of eye closure to determine if an alarm should be triggered. The system consists of four main components: a camera and video decoding module, a display, an LCD screen, and a development board. It is built using an FPGA as the core hardware, combined with Xilinx's MicroBlaze embedded soft-core processor. This allows for efficient implementation of image processing and dynamic target recognition algorithms, along with necessary peripheral circuits. To improve performance, most of the key processing tasks—such as video acquisition, median filtering, and FIR filtering—are handled directly in hardware.
This system is particularly suitable for long-haul drivers, car manufacturers looking to integrate safety features, or traffic authorities aiming to reduce accident rates. Its design ensures both reliability and scalability, making it ideal for a wide range of applications.
The system is divided into four main modules: image acquisition, feature extraction, data storage, and the human-computer interaction interface.
(1) Real-time facial image collection
A camera captures the driver's video stream, which is then converted from analog to digital format via an external video decoding chip. This digital signal is sent to the FPGA for further processing.
(2) Image processing function
Extracting eye features is the core part of the system. Using the powerful computing capabilities of the MicroBlaze soft-core processor, most of the algorithms are implemented in C code, allowing accurate detection of eye closure states.
(3) Data storage
An internal user-defined module within the FPGA stores video footage when the driver’s eye closure time exceeds a set threshold. This stored data can serve as crucial evidence in accident investigations. Users can also view the recorded videos on the display by selecting the appropriate option.
(4) Human-computer interaction interface
The system includes a high-resolution color LCD screen to provide a clear visual interface. When an alarm is triggered, relevant information is displayed. A touch screen allows users to interact with the system, such as managing video data storage and accessing different functions.
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