Analytical Test Effort Estimation for Multisensor Driver Assistance Systems

Modern driver assistance systems are often using a wide range of equipped sensors as primary data source. The reliability of each sensor is specified by the manufacturer and influences the system reliability distinctly. To prevent potential fatal system failures, diverse failure prevention mechanisms are included. Nevertheless, a certain level of reliability of the system has to be guaranteed to meet legal regulations. For this, extensive testing is required, which is costly due to the involved resources. To estimate and simulate the required test effort, an exact analytical method based on Markov Chains and an implementation realized in a common simulation framework is presented in this paper. It enables real automotive projects to estimate the test costs and simulate changes for various sensor setups.