Driver Monitoring Systems in automated interactions: A realtime, thermographic-based algorithm

Due to the progressive shift of responsibility from the driver to the vehicle itself in automated vehicle technologies, driver-centered innovations represent a key point for its advance. The socalled Driver Monitoring Systems (DMS) are therefore increasingly gaining importance in this context. One of the main aims of DMS is to estimate the driver’s arousal levels in order to infer their cognitive state and capabilities. Even though the scientific literature is riddled with useful psychophysiological indices to estimate arousal levels [1], nowadays, arousal estimation is based on broad, mostly blink/gaze-related, indices. The reason is that actual implementation of reliable sensors in a feasible system able to collect, analyze, and interpret measurements in real-life conditions is still an open challenge. One of the alternatives to signal different cognitive states is facial skin temperature [2][3]. Infrared sensors that monitor heat loss have been shown useful to track facial skin temperature that indicate arousal modulations while driving [2][3]. Such intensive, laborious work to extract and analyze temperature changes in some facial landmarks is not reasonable in real-life applications [2]. Here, we present the preliminary results obtained with a new software able to track, in real-time, drivers’ facial-skin temperature changes