Advanced optical methods for safe image reproduction on automotive displays

Modern cars are equipped with camera monitor systems (CMSs), such as a backup camera or side-mirror replacement. These systems are expected to perform optimally and achieve high safety levels (ASIL). Currently, only digital data are supervised in CMSs and safety mechanisms for such systems are individually derived on a case-by-case basis which is not effective. This study proposes generic optical supervision for displays of automotive CMS. This paper introduces "light-to-light" (camera to display output) protection for both in-car CMS and remote operator monitors used in autonomous car fleet operation centers. The first method is based on photodiodes attached to the display to optically supervise, for instance, the speedometer of vehicles. By combining intensities of photodiodes with calibration data, we can compare the measured speed with the value from CAN (Controller Area Network) data. The second method that entails capturing the display content using a camera enables top safety levels for both in-car displays and remote operator monitors. This safeguarding was successfully verified by conventional image processing and artificial intelligence (AI)-based analysis methods. Our results demonstrate that AI methods allow a substantial reduction in the wireless transmission bandwidth from a car to a remote operator compared with conventional image processing.