TRUST in human-robot interactions (HRI) is essential for effective collaboration and user acceptance of robotic systems. However, trust can be challenged by conflicting goals between the user and the system, such as in the context of proxemics when a robot invades a human’s personal space. As robotic systems increasingly adapt their actions autonomously, intelligent conflict resolution is necessary to not undermine humans’ trust in the robot’s decisions due to a decreased sense of control and understanding. Therefore, this study investigates how humans can be involved and supported during automated conflict resolution to maintain their trust by exploring different degrees of explainability and automation. We applied a within-subjects experimental design, where 20 participants experienced four conditions varying in levels of automation and explainability during a simulated conflict between their need to preserve their personal space and the robot’s requirement to approach to perform a task. We measured the participants’ trust through questionnaires and interviews. Our findings suggest that trust is positively influenced by the level of control users have during conflict situations. However, the robot’s explanations did not significantly impact trust. Our insights highlight the need for conflict management strategies in HRI that balance automation with user involvement to foster greater levels of trust when collaborating with robots.

Security assurance cases (SACs) consist of arguments that are supported by evidence to justify that a system is acceptably secure. However, they are a relatively static representation of the system’s security and therefore currently not effective at runtime which make them difficult to maintain and unable to support users during threats. The aim of this paper is to investigate how SACs can be adapted to become more effective at runtime and increase confidence in the system’s security. We extend an example SAC with game theory, which models the interaction between the system and attacker and identifies their optimal strategies based on their payoffs and likelihoods. The extension was added as a security control in the assurance case, where a security claim indicates what strategy should be taken at runtime. This claim changes dynamically with the recommended strategy output by the game-theoretic model at runtime. Based on the results of the evaluation, the extension was considered to be potentially effective, however this would further depend on how it is implemented in practice.

Requirement conflicts commonly o ccur i n soft-ware development, especially for complex systems that involve many requirements. Resolving these conflicts c an b every time-consuming and costly. Moreover, due to the contextual nature of requirements conflicts, resolutionstrategies a re n eeded that can be tailored to a specific conflict an d it s co ntext. Currently, there is a lack of research on what categories of conflicts exist and how practitioners manage these conflicts. Toe nable more adaptive resolution strategies, the aim of this research is to map what types of requirement conflicts a re e ncountered a nd how they are managed in practice. Through an interview study with eleven participants from eight companies in six domains, we identified three levels of conflict ty pes th at co nnect to four types of causes. These types and causes revealed two main dimensions that impact conflict management. One dimension is related to the nature of the conflict, either technical or social, a nd the other dimension is related to the nature of the requirement scope, which is either too constraining or too undefined resulting in stakeholders making assumptions that create conflicts. We found that these two dimensions impact what conflict resolution strategies are most commonly used for different types of conflicts.