Abstract
With the continuous development of the automobile industry, the subsequent social problems have become increasingly serious. Not only traffic accidents cause huge harm to people, but also impose a heavy burden and impact on society. Fatigue driving is a major reason of traffic accidents, therefore it is essential to develop a reasonable and effective non-contact vehicle-mounted device that can accurately detect whether the driver is fatigued at the current time for cutting down traffic accidents and ensuring road safety. This paper proposes a new type of fatigue driving detection system. Firstly, it collects five kinds of face information such as PERCLOS value, blink frequency, and closed eye duration through Openmv. Secondly, the Technique for Order Preference by Similarity to Ideal Solution algorithm is used to fuse the standardized fatigue index with data. Finally, the quantification of the driver’s fatigue value is realized. Experimental results show that the system can control the alarm more accurately to remind the driver to improve the driving state in time.
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Ma, J., Wang, J., Wang, J., Yu, F., Tian, Y., Pan, B. (2020). Fatigue Detection System Based on Facial Information and Data Fusion. In: Qian, J., Liu, H., Cao, J., Zhou, D. (eds) Robotics and Rehabilitation Intelligence. ICRRI 2020. Communications in Computer and Information Science, vol 1336. Springer, Singapore. https://doi.org/10.1007/978-981-33-4932-2_5
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DOI: https://doi.org/10.1007/978-981-33-4932-2_5
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