Automated driving systems (ADSs) beyond a technology centered perspective

All global players of the automotive industry (e.g., BMW, VW, JLR, Ford, Tesla, etc.) are focusing on the development of automated driving systems (SAE J3016: ADS) [1]. Beside car manufacturers, also technology companies like Google, Apple, Nvidia and Intel are working hard to bring the technology to the market. The automated driving race to commercialization is funded on the premises that this technological breakthrough will bring universal mobility access, reduced traffic flow, lower emissions, and especially increased safety.

ADS are a radical innovation, inspired by new technology (e.g., advanced algorithms, cameras, sensors, etc.). To further increase the product quality, incremental innovation is necessary. This can be achieved by applying the philosophy of the User-Centered-Design (UCD) Process. This established design process centers on the user by utilizing a problem-solving iterative framework: analysis, design, evaluation and implementation. Users are observed in the context to be able to create ideas and requirements, to develop prototypes, and especially to evaluate and test concepts with real users [2]. Norman and Verganti [3] compare this process with the way of hill climbing of a blindfolded person, scanning the environment till sensing the next higher position. The mountain peak is a metaphor for the ideal quality of a product.

As researchers, we face several challenges to the application of UCD to ADS. User assessment is hindered by restricted access to latest technology, by the cost of fully functional prototypes, and by the potential risk of real world evaluations. On the other side, low-fidelity environments such as driving simulators that can provide controlled settings for testing ADS experiences might lack the required realism to break through existing misconceptions or mental models that users have. As interactions and responsibilities are transferred from users to systems, a wide-spread acceptance of the technology and optimal user experience can only be reached by fulfilling users' needs and values in their real life situations. Thus, user research, (instant) feedback and continuous evaluation are imperative. The application of special methods are essential to understand users and the context of automated vehicles.