Table 1.

Common methods of evaluating drowsiness and their advantages and disadvantages

Method name	Advantages	Disadvantages
Based on physiological measures (EEG)	By using brain waves, drowsiness can be efficiently and accurately detected.	It is not realistic, because to get these signs, electrodes must be attached to the body, which is unpleasant or annoying to drivers.
Based on vehicle measures	Lane tracking, vehicle steering wheel changes, the number of lane crossings, and the distance from the front vehicle can be used in detecting.	Having restrictions against some changes, including vehicle type, driver experience, road topology, road quality, and ambient light; in addition, the processing of these methods requires considerable time to analyze the drivers’ behaviors that cause them to be unaware of micro-sleep.
Based on behavioral measures (image processing)	In drowsiness, sensible changes can be seen in appearance and face of people, and the most important changes are in the eyes, head, mouth, and sitting posture. By taking a picture of the driver and using image processing techniques, signs of drowsiness can be extracted.	Sudden changes in the head and eyes and changes in light intensity can decrease the percentage of drowsiness that is detected.
Based on behavioral and vehicle-based measurements (Hybrid methods)	In this method, infrared radiation is used for imaging, which allows imaging at night without disturbing the driver.	This method requires different categories in terms of image processing and status of eyes and face.