Technological advancements have resulted in vehicles gaining the ability to effortlessly compile data required to generate Situational Awareness. Situational Awareness is defined as the continuous (re-)processing of information leading to an intangible spatial representation of the environment. While vehicles effortlessly compile Situational Awareness, drivers are only able to generate it through complex cognitive processes that are highly demanding. This thesis introduces an overall framework for an interaction concept for research purposes. This interaction concept aims to actively support the driver in generating Situational Awareness (SA) to reduce the demands on the driver.

The presented approach is an interaction concept that exploits the vehicle’s ability to support drivers in the SA process. This supportive concept aims to support the driver by assessing the driver’s SA and responding in an intervening or informative manner when required. By doing so, the solution aims to reduce the demand on the driver and sequentially enhances the driver’s user experience.

To introduce such a supportive interaction concept, the future context has been considered which revolves around Conditional Autonomous Vehicles. The introduction of such vehicles results in a shifting role allocation between human drivers and automated driving systems. As a result, three driving modes can be encountered in the driving task. Based on the frameworks of information processing and human factors in automation and SA, several aspects are identified that have shaped the aim of the interaction concept in each driving mode.