Traffic Awareness Driver Assistance based on Stereovision, Eye-tracking, and Head-Up Display
Tobias Langner, Daniel Seifert, Bennet Fischer, Daniel Goehring, Tinosch Ganjineh, and Raúl Rojas – 2016
This paper presents a system which constantly monitors the level of attention of a driver in traffic. The vehicle is instrumented and can identify the state of traffic-lights, as well as obstacles on the road. If the driver is inattentive and fails to recognize a threat, the assistance system produces a warning. Therefore, the system helps the driver to focus on crucial traffic situations. Our system consists of three components: computer vision detection of traffic-lights and other traffic participants, an eye tracking device used also for head localization, and finally, a human machine interface consisting of a head-up display and an acoustic module used to provide warnings to the driver. The orientation of the driver's head is detected using fiducial markers visible in video frames. We describe how the system was integrated using an autonomous car as experimental ADAS platform.