Method for enabling a sensor system for detecting objects in an environment of a vehicle, the method comprising the steps of: • providing a joint probability distribution for deviations (a) between output data of the sensor system and reference data at the level of program sections for detecting objects of the sensor system, at the level of sensors of the sensor system and/or at the fusion level of the sensor system, wherein the output data and reference data are data from respectively taken measurements and wherein the joint probability distribution is a multidimensional probability distribution based on a mathematically stochastic model and obtained from individual probability distributions of the deviations (a), • sampling combinations of deviations (a) of the output data from sensors of the sensor system and calculating probabilities of occurrence (p) of the respective combinations by means of the joint probability distribution, • supplying the sampled deviation combinations to the reference data in order to assess a criticality of error patterns regarding recognition errors, using a fusion unit of the sensor system to process the reference data which have been supplied with said sampled deviation combinations, and obtaining fusion results, • removing from the joint probability distribution those occurrence probabilities (p) whose underlying deviation combinations result in such fusion results which meet a predefined requirement, and obtaining a residual probability distribution, wherein deviations between the fusion results and the reference data are evaluated using a limit state function in order to remove the occurrence probabilities (p) from the probability distribution, wherein the limit state function delivers a first value in the event that a requirement is met and a second value, which is different from the first, in the event that the requirement is not met, and the statistical error margin of the sensor system regarding a residual risk is assessed using the limit state function, • integrating the residual probability distribution and obtaining an absolute error probability and • enabling the sensor system on the basis of the absolute error probability, wherein, in the method, a confidence of the output data is determined from actual driving of a sufficient distance or time. • providing a joint probability distribution for deviations (a) between output data of the sensor system and reference data at the level of program sections for detecting objects of the sensor system, at the level of sensors of the sensor system and/or at the fusion level of the sensor system, wherein the output data and reference data are data from respectively taken measurements and wherein the joint probability distribution is a multidimensional probability distribution based on a mathematically stochastic model and obtained from individual probability distributions of the deviations (a), • sampling combinations of deviations (a) of the output data from sensors of the sensor system and calculating probabilities of occurrence (p) of the respective combinations by means of the joint probability distribution, • supplying the sampled deviation combinations to the reference data in order to assess a criticality of error patterns regarding recognition errors, using a fusion unit of the sensor system to process the reference data which have been supplied with said sampled deviation combinations, and obtaining fusion results, • removing from the joint probability distribution those occurrence probabilities (p) whose underlying deviation combinations result in such fusion results which meet a predefined requirement, and obtaining a residual probability distribution, wherein deviations between the fusion results and the reference data are evaluated using a limit state function in order to remove the occurrence probabilities (p) from the probability distribution, wherein the limit state function delivers a first value in the event that a requirement is met and a second value, which is different from the first, in the event that the requirement is not met, and the statistical error margin of the sensor system regarding a residual risk is assessed using the limit state function, • integrating the residual probability distribution and obtaining an absolute error probability and • enabling the sensor system on the basis of the absolute error probability,