The key benefits of the ever so more evident driving automation include improvements in terms of road safety and driving comfort. The safety improvements are based on the expectation of reduced number and effect of road accidents, the majority of which are resulting from human errors. Driving automation offers superior performance over human reaction times, distraction levels, tiredness, or influence of (legal/illegal) performance altering substances.
TEACHING tackles complex driving scenarios through improved control strategies based on the human perception of comfort and safety. The perception is the decisive factor for the user acceptance and ability to take over control from the autonomous driving system. The system functions seek cooperation between autonomous safety-critical CPSoS, IoT, and vehicle’s advanced control strategies.
The combination of functional interactions highlights the challenge of creating a reliable solution for autonomous and safety-critical distributed systems of networking computing elements and humans in the autonomous driving context. The human-centred approach is supported through the integration of AI techniques at the edge leveraging the physiological, emotional and cognitive state of vehicle occupants for the adaptation and optimisation of the AD applications. While AI algorithms are extremely promising contributors to the success of AD, they are unlikely to replace the entire human decision-making soon, due to the need to ensure critical safety and due to a lack of standardised certification methods.
Innovation capacity: As the societal expectations towards mobility are evolving, there is a need for a firmer link and an improved interface between humans and machines. TEACHING offers insights needed for strengthening that link, which is also forming the basis for further improvements of autonomous driving functionalities. The improvements are also offering an added benefit of customization to the needs of either specific groups or even to individuals. Such an offer is also contributing to the improvement of mobility as a service proposition. The automotive application is directly contributing towards human-centred enhancements to driving automation by improved involvement of human modes into the safety-critical systems. It also contributes towards balancing the equilibrium between AI and automotive safety.
