User-specific Information Design and Acceptance Concerning Highly Automated Driving
The increasing urbanisation and the changed social mobility imply new challenges for the individual and customizable mobility. Developments within the automotive sector are particularly characterised by information and communication technologies as for example in the field of highly automated driving, which shows an enormous potential for the comfort and efficiency of social mobility.
Due to the immense technological progress of the last years, first partial automated systems, which still need permanent supervision by the driver, have been introduced into today’s traffic. In parallel, the technological development towards high automation is ongoing. Beyond technological progress, the user-centred and socially compatible introduction of new technologies in the automotive sector is a major challenge. This is especially true for automated driving: Even though there are many undeniable advantages for society, users have concerns about loss of control or an external encroachment. Additionally, users may struggle with varying responsibilities due to different system designs and automation levels.
What has been lacking so far is a processing of those factors that determine the acceptance of and the behaviour towards automated systems. The goal of this project is to establish influences of information design before and during interaction with automated systems as well as acceptance-relevant factors for users concerning data sharing, data storage and data protection. Within the project, characteristics of the driver (e.g. attitudes, prior knowledge, mental models), different driving scenarios (e.g. regarding their criticality) and different system characteristics (e.g. responsibility sharing between human and machine) are considered.
Within the first project phase, user expectations regarding displayed information during driving, e.g. the HMI design, as well as the willingness to share data with different levels of automation (partial vs. high automation) were evaluated. One research focus within the current project is the effect of initial system information provided with regard to driver expectations and behaviour in mixed traffic for selected situations of use.