A method for monitoring and adapting the performance of a fusion system of an autonomous road vehicle equipped with an autonomous drive system comprising a positioning system and multiple sensors for supervising the internal state of the autonomous road vehicle and the surrounding environment, wherein a localization function of the fusion system is provided by fusing data from the positioning system and the sensors; an environmental perception function of the fusion system is provided by fusing data from the sensors supervising the surrounding environment; and where the localization and environmental perception functions of the fusion system are implemented using parallel algorithms based on alternative concepts and using different sets of sensor information, the method further comprises: determining a drivable area in front of the autonomous road vehicle by combining the localization function and high density map data for a current position; determining information on surrounding objects, the information determination comprising determining the localization of the surrounding objects, classifying the surrounding objects, estimating their physical property states, and assigning them extension descriptions and a highly automated drive confidence; condensing information on the drivable area and surrounding objects into information on observed areas and prioritized objects, specifying observed areas as the volume around the autonomous road vehicle that has been monitored by the sensors of the environmental perception function with a predetermined degree of certainty, and representing prioritized objects by classes, state estimates, extension descriptions and highly automated drive confidences; and having the fusion system monitor itself retrospectively by evaluating its current determinations of drivable area, prioritized objects and observed areas against its previous determinations thereof, and if a previous determination differs more than a predetermined amount from a current determination, adapting the fusion system to account for that discrepancy. determining a drivable area in front of the autonomous road vehicle by combining the localization function and high density map data for a current position; determining information on surrounding objects, the information determination comprising determining the localization of the surrounding objects, classifying the surrounding objects, estimating their physical property states, and assigning them extension descriptions and a highly automated drive confidence; condensing information on the drivable area and surrounding objects into information on observed areas and prioritized objects, specifying observed areas as the volume around the autonomous road vehicle that has been monitored by the sensors of the environmental perception function with a predetermined degree of certainty, and representing prioritized objects by classes, state estimates, extension descriptions and highly automated drive confidences; and having the fusion system monitor itself retrospectively by evaluating its current determinations of drivable area, prioritized objects and observed areas against its previous determinations thereof, and if a previous determination differs more than a predetermined amount from a current determination, adapting the fusion system to account for that discrepancy.