Driver physiological condition assessment system based on image-based photoplethysmography

Automated driving is in the stage of development and industry standardization. In order to ensure the safety of autonomous driving, intervention by the driver is required at any time to address unexpected situations during the autonomous driving process. Due to the fatigue and other factors, drivers are often unable to intervene in time to respond to unexpected situations, and autonomous driving accidents occur from time to time. Some companies have already installed DMS in their vehicles, however, many physiological conditions caused by fatigue vary from person to person, and there is still a need for a more reliable and cost-effective method to monitor the driver's condition. Based on the study of a large number of driver monitoring systems (DMS), we propose the use of image-based photoplethysmography (iPPG) for driver physiological condition monitoring, which can effectively solve most of the pain points of the DMS. In this paper, we present an innovative dual-camera measurement system designed to tackle measurement errors arising from environmental variability and motion artifacts. This dual-camera configuration aims to improve the accuracy of physiological signal monitoring, thereby providing more reliable assessments of the driver's condition during autonomous driving.