Real-Time Controlled Safety Metric for Use in Autonomous Systems of Safety Relevance Using the Example of the Operation of an Autonomous Inland Waterway Vessel

The idea of understanding safety- or reliability-related variables as an output variable of a continuously operating control loop and thus regulating them has been known and formulated for about two to three decades and can nowadays also be found in automation systems, e.g., to extend the service life in the case of unpredictable, future performance requirements. Up to now, classical, deterministically determined and known fixed relationships have been used to exploit the relationship between, for example, realized stress and actual service life to achieve specific goals such as remaining service life. In this article, statistically known correlations are used, e.g., for the data-based determination of relevant, safety-related variables, to adjust operating variables online, i.e., continuously in real time, in such a way that minimum safety and/or reliability requirements for those variables are maintained. As a relevant, important, and practice relevant application example, the determination of objects in the path of vessels is used, the reliable determination of which is essentially determined both by sensor quality and by data-based estimation methods used. Both are significantly influenced in their capabilities by environmental conditions. Based on a Probability of Detection reltion statistical measurement data for the overall behavior, the driving speed, and thus the resulting braking distance are automatically adjusted so that the safety requirements are controlled. The methodology provides the basics for the establishment of classic risk regulations as proof of the maintenance of safety in automated vehicles.

Keywords: Autonomous systems, Inland waterway transport, Probability of detection, Sensor fusion, Real-time control, Dependent functionality.