Development of a Cost Model for ADAS and AD Functions

Computer-aided synthesis and development tools are essential for discovering and optimizing innovative concepts. Evaluating different concepts and making informed decisions relies heavily on accurate assessments of system properties. Estimating these properties in the early stages of vehicle development is challenging due to the depth of modelling required. In order to enable a cost prognosis for driving assistance and automated driving functions including software and hardware properties a cost model was developed at the Institute of Automotive Engineering. The methodology and cost model focuses on multiple combined approaches. This includes a bottom-up approach for the hardware. The costs of the software components are integrated into the model with the help of existing literature data and an exponential regression. For a comprehensive view of the total costs, the model is the model is also supplemented by a top-down approach for estimating the costs of other hardware components. The cost model was utilized for a market forecast and cost analysis. In the coming years, a significant reduction in costs can be seen, particularly for software, due to economies of scale. In contrast, the costs for control units are expected to increase proportionally, making this component the biggest cost driver. The forecast market development suggests that there is significant economic potential of advanced driver assistance systems. The market value of control units, LiDAR sensors and cameras in particular is expected to rise.