現在自駕車的發展日新月異，即使自駕車的技術一天比一天進步，但是要真正達到完全自動駕駛還有很長一段路要發展，尤其是在發展2-3級的自駕車時，反而更為困難，尤其在第3級的自駕車時，有些鴐駛人誤以為現在已經到了完整自駕的時代，把操控完全交給車子，而自己因為疲勞，則開始睡覺，這樣對駕駛人及用路人來說很容易發生危險，因此需要開發相關的系統來減少駕駛人在疲勞狀態繼續行駛，好讓駕駛人在遇到問題時，能快速的反應過來，保護用路人的安全。疲勞駕駛的偵測需要高準確度，因此我們提出了一個新穎的做法。首先，透過物件偵測的技術來偵測駕駛員的人臉。再來，透過本研究開發的疲勞狀態檢測的網路來進行檢測，該網路會基於NTHU-Drowsy Driver Detection(NTHU-DDD)中來進行開發及驗證。

Nowadays, the development of self-driving cars is changing with each passing day. Even if the technology of self-driving cars is improving day by day, there is still a long way to go to achieve fully autonomous driving, especially during the level 2-3 self-driving cars, especially in the third-level self-driving car, some drivers mistakenly think that the era of complete self-driving has come, and completely hand over the control to the car, and they start to rest because of fatigue. This is very dangerous for drivers and road users, so it is necessary to develop a system to reduce the number of drivers who continue to drive in a fatigued state, so that drivers can react quickly when they encounter problems and protect the safety of road users. Fatigue detection requires a high degree of accuracy, so we propose a novel approach. First, the driver's face is detected by object detection technology. Then, the detection is performed through a fatigue detection network developed in this study, which will be based on the NTHU-Drowsy Driver Detection (NTHU-DDD) for development and validation.

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