The field of AI ethics and autonomous systems is rapidly evolving, with a growing focus on developing systems that can incorporate human values and ethical preferences. Recent research has highlighted the importance of considering the social and contextual factors that influence human decision-making, and developing systems that can adapt to these factors. One key area of development is the creation of frameworks for ethical decision-making in autonomous vehicles, which can balance competing priorities such as safety, efficiency, and rule compliance. Another area of focus is the development of systems that can negotiate and adapt to different ethical preferences, such as the RobEthiChor approach. Notable papers in this area include the proposal of a novel human reasons-based supervision framework for automated vehicles, which detects when AV behaviour misaligns with expected human reasons and prompts replanning. Additionally, the development of a reasons-based trajectory evaluation framework that operationalises the tracking condition of Meaningful Human Control (MHC) has shown promise in assessing the alignment of automated vehicle decisions with human reasons.